AAPM REPORT NO. 40
RADIOLABELED ANTIBODY
TUMOR DOSIMETRY
REPORT OF
TASK GROUP NO. 2
AAPM NUCLEAR MEDICINE COMMITTEE
Members
Barry W. Wessels, Chairman
A. Bertrand Brill
Donald J. Buchsbaum
Laurence P. Clarke
Darrell R. Fisher
John L. Humm
Timothy K. Johnson
Jerry L. Klein
Kenneth F. Koral
Cheuk S. Kwok
Virginia Langmuir
Peter K. Leichner
Daniel J. Macey
George Sgouros
Jeffry A. Siegel
Edward A. Silverstein
Mike Stabin
Sven-Erik Strand
Evelyn E. Watson
Lawrence E. Williams
Latresla A. Wilson
Ellen D. Yorke
Pat Zanzonico
April 1993
Published for the
American Association of Physicists in Medicine
by the American Institute of Physics
DISCLAIMER: This publication is based on sources and information believed to be
reliable, but the AAPM and the editors disclaim any warranty or liability based on or
relating to the contents of this publication.
The AAPM does not endorse any products, manufacturers, or suppliers. Nothing in
this publication should be interpreted as implying such endorsement.
Further copies of this report ($10 prepaid) may be obtained from:
American Institute of Physics
c/o AIDC
64 Depot Road
Colchester, Vermont 05446
(l-800-488-2665)
International Standard Book Number: 1-56396-233-0
International Standard Serial Number: 0271-7344
©1993 by the American Association of Physicists in Medicine
All rights reserved. No part of this publication may be reproduced, stored in a retrieval
system, or transmitted in any form or by any means (electronic, mechanical, photocopying, recording, or otherwise) without the prior written permission of the publisher.
Published by the American Institute of Physics, Inc.
336 East 45th Street, New York, NY 10017-3463
Printed in the United States of America
CONTENTS
Journal Editor’s Preface
JohnS.Laughlin......................................................................................
497
Co-Editors’ Preface
David A. Weber and Amin I. Kassis........................................................................................................................................
497
Introduction: Radiolabeled antibody tumor dosimetry
Donald J. Buchsbaum and Barry W. Wessels.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
499
Selection of radionuclides for radioimmunotherapy
Leonard F. Mausner and Suresh C. Srivastava..................................................................................................................
503
MIRD formulation
Evelyn E. Watson, Michael G. Stabin, and Jeffry A. Siegel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
511
Pharmacokinetic modeling
Sven-Erik Strand, Pat Zanzonico, and Timothy K. Johnson.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
515
Tumor dosimetry in radioimmunotherapy: Methods of calculation for beta particles
Peter K. Leichnerand Cheuk S. Kwok.................................................................................................................................
529
Microdosimetric concepts in radioimmunotherapy
J. L. Humm, J. C. Roeske, D. R. Fisher, and G. T. Y. Chen.. . . . . . . . . . . . . . . . . . . . . , . . . . . . . . . . , . . . . . . . . . . . . . . .
535
Multicellular dosimetry for beta-emitting radionuclides: Autoradiography, thermoluminescent
dosimetry and three-dimensional dose calculations
E. D. Yorke, L. E. Williams, A. J. Demidecki, D. B. Heidorn, P. L. Roberson, and B. W. Wessels.. . . . . . . . . . . . . . .
543
Experimental radioimmunotherapy
Donald J. Buchsbaum, Virginia K. Langmuir, and Barry W. Wessels . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
551
An overview of imaging techniques and physical aspects of treatment planning in
radioimmunotherapy
Peter K. Leichner, Kenneth F. Koral, Ronald J. Jaszczak, Alan J. Green, George T. Y. Chen, and
JohnC.Roeske......................................................................................,
569
Radioimmunotherapy dose estimation in patients with B-cell lymphoma
J. A. Siegel, D. M. Goldenberg, and C. C. Badger.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
579
Dosimetry of solid tumors
Ruby F. Meredith, Timothy K. Johnson, Gene Plott, Daniel J. Macey, Robert L. Vessella, Latresia A. Wilson,
Hazel B. Breitz, and Lawrence E. Williams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
583
Dosimetry of intraperitoneally administered radiolabeled antibodies
John C. Roeske, George T. Y. Chen, and A. Bertrand Brill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
593
Radiobiology of radiolabeled antibody therapy as applied to tumor dosimetry
V. K. Langmuir, J. F. Fowler, S. J. Knox, B. W. Wessels, R. M. Sutherland, and J. Y. C. Wong . . . . . . . . . . . . . . . . .
601
Journal Editor’s Preface
The AAPM, through its Science Council, asked Medical Physics to accept the
responsibility for the scientific review of all of the manuscripts proposed for this report
and to consider the final manuscripts for publication in Medical Physics. This responsibility was accepted by the Editor and Editorial Board. The Editor then asked Dr.
David A. Weber, Associate Editor and Head of Nuclear Medicine Research at the
Brookhaven National Laboratory, and one of his scientific colleagues, Dr. Amin I.
Kassis, Director of Radiation Biology, Brigham and Women’s Hospital, Harvard
Medical School, to accept the responsibility for scientific reviews of the material to be
provided for the report and to serve as the Co-Editors of a special issue of the journal.
This arrangement was approved by the Science Council of the AAPM and by the
Editorial Board.
This review, a major task, has been carried out in a comprehensive and scientifically
rigorous manner by the Editors for this special issue with the vital assistance of the
expert referees, authors and Task Group members. Medical Physics appreciates the
decision of the Task Group to offer this important collection of articles written by
authorities in the field of radiolabeled antibody tumor dosimetry for publication in the
AAPM journal.
John S. Laughlin
Co-Editors’ Preface
Monoclonal antibodies have been considered particularly appealing as selective
carriers of diagnostic and therapeutic radionuclides in vivo. Their target specificity
continues to attract investigators to identify and produce new agents for clinical use.
In spite of the limited number of clinical applications at present, it is extremely
important that factors influencing the localization and clearance properties of radioimmunoconjugates, especially tumor-associated, antigen-specific antibodies, be considered and understood by those administering them to patients so as to assess those
variables that influence the absorbed radiation dose from internal emitters. The absorbed radiation dose has been, and will continue to be, a pivotal factor in assessing the
risks and therapeutic utilities of radiopharmaceuticals.
The AAPM Nuclear Medicine Task Group, under the leadership of Dr. Barry
Wessels, sought qualified experts in various specialties concerned with the dosimetry
of radiolabeled antibodies to develop a well-balanced review of the multiple concerns
and factors that influence the clinical use of radiolabeled anti-tumor antibodies. Dr.
Donald J. Buchsbaum, a member of the Task Group, chaired a subcommittee responsible for coordinating and overseeing the preparation of all manuscripts. In the 13
manuscripts produced, many of the approaches employed to estimate absorbed radiation dose in radioimmunotherapy have been evaluated, and the physical, physiologic,
chemical, and biologic parameters affecting tumor dosimetry presented. In addition,
the decay properties of various radionuclides and their radiobiologic effects have been
discussed, and dose calculations at the organ, tissue, cellular, and subcellular levels
compared. The manuscripts, containing extensive, up-to-date reference lists, will be
very useful to those interested in the use of radiolabeled antibodies in the diagnosis and
treatment of disease.
We are pleased to have had the opportunity to explore with the authors the multifaceted topic of radiolabeled-antibody tumor dosimetry. Since many of the experts in
this field are contributors to this supplement, it required some extra attention to find
equally qualified referees. Having accomplished this, we would like to express our
sincere gratitude to those who have volunteered their time to review and comment on
the manuscripts.
David A. Weber and Amin I. Kassis
Introduction: Radiolabeled antibody tumor dosimetry
Donald J. Buchsbauma)
Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham,
Alabama 35233-6832
Barry W. Wessels
Department of Radiology, George Washington University Medical Center, Washington, DC 20037
(Received 18 March 1992; accepted for publication 8 January 1993)
I. INTRODUCTION
Through the sponsorship of the Nuclear Medicine Committee of the American Association of Physicists in Medicine (AAPM), a Nuclear Medicine Task Group 2, “Dosimetry of Radiolabeled Antibodies” was established in
July 1987 under the Chairmanship of Dr. Barry Wessels to
produce reports on radiolabeled antibody dosimetry, which
would include an extensive literature search and an analysis of how to approach the dosimetry to normal tissues and
tumor of radiolabeled antibody therapy (radioimmunotherapy). The first report published in 1990 1 summarized a
“Bone Marrow Dosimetry and Toxicity for Radiolabeled
Antibodies” symposium held in conjunction with the 1988
American Society for Therapeutic Radiology and Oncology (ASTRO) annual meeting. In 1989, the Steering Committee on the Nuclear Medicine Task Group 2 decided at
the Society of Nuclear Medicine (SNM) Annual Meeting
that the new focus area for the Task Group would be tumor dosimetry for radiolabeled antibody therapy. The
Task Group members and invited guests active in radiolabeled antibody research from the physics, radiation biology, nuclear medicine, and oncology communities had
been invited to attend meetings to plan and prepare this
report on “Radiolabeled Antibody Tumor Dosimetry.”
These meetings were held in conjunction with the annual
meetings of the ASTRO, the AAPM, the SNM, the “International Conference on Monoclonal Antibody Immunoconjugates for Cancer” and the “Third Conference on RaRadioimmunotherapy of
and
dioimmunodetection
Cancer.” The purpose of this report is to provide an extensive literature search and review the various approaches
that are being pursued in preclinical and clinical studies to
estimate tumor dosimetry associated with radioimmunotherapy (RIT), and to suggest future directions for dosimetry research in this field. Included in this report is a discussion of the radiobiological aspects of tumor dosimetry
of radiolabeled antibody therapy.
Radiolabeled monoclonal antibodies (MoAbs) offer the
potential of highly localized, targeted radiation treatment
of cancer. The effectiveness of radiation treatment of malignant disease is correlated with the total dose delivered,
with increasing dose producing increasing cell kill. Similarly, normal tissue damage is also directly related to the
total dose deposited. The ability to quantify the dose delivered to tumor and normal tissues when using radiolabeled MoAbs has been a perplexing problem.
As noted in the review of a National Cancer Institute
workshop, 2 techniques for evaluating the dosimetry of ra499
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
diolabeled antibody therapy are essential to support the
development of RIT in the treatment of neoplastic diseases.
Radiation dosimetry is important for treatment planning
and the assessment of results. It is necessary to determine
the quantity of radiolabeled antibody to administer to maximize the radiation dose to the tumor while not exceeding
tolerance levels of critical normal tissues, In contrast to
external beam radiation therapy dosimetry, the tumor dosimetry for radiolabeled antibody therapy is dependent on
a number of variables including: ( 1) kinetics of biodistribution, tumor uptake and retention of the radiolabeled antibody, (2) the uniformity of distribution of the radiolabeled antibody within tumor, (3) the radionuclide
attached to the antibody, and (4) the radiobiological response of tumor cells to continuously decreasing low-doserate radiation.
The 12 papers in this special issue of Medical Physics
summarize the problems, various techniques that are being
used to estimate the tumor dosimetry associated with radiolabeled antibody therapy, and future directions as highlighted below.
II. TOPICS DISCUSSED IN THIS REPORT
A. Selection of radionuclides for RIT
The contribution by Mausner and Srivastava 3 to this
special issue reviews the factors that influence the choice of
a radionuclide for RIT. A potential advantage of some of
the radionuclides would be a higher tumor/whole-body
dose, resulting in less toxicity to normal tissue, particularly
bone marrow. It is essential to carefully consider the choice
of radionuclide in conjunction with the in vivo pharmacokinetic (localization and clearance in tumor and normal
tissues) properties of the radiolabeled MoAb, the physical
half-life of the radionuclide, the chemistry of conjugation
to MoAbs, and the toxicity of free radionuclide.
The choice of radionuclide also depends on the microdistribution of the radiolabeled MoAb relative to the radiosensitive target sites, involving uniform versus nonuniform deposition in tumors or localization on cell surfaces
versus internalization of radionuclides to the cell cytoplasm
or nuclei.
To optimize the efficacy of RIT, it will be necessary to
develop combinations of MoAbs or antibody fragments
and radionuclides whose pharmacokinetics, physical halflives and emissions are matched to give the largest possible
tumor dose and the least normal tissue toxicity, i.e., the
largest possible therapeutic ratio.
0094-2405/93/020499-04$01.20
© 1993 Am. Assoc. Phys. Med.
499
500
D. J. Buchsbaum and B. W. Wessels: Introduction: Radiolabeled antibody tumor dosimetry
B. MIRD formulation
The approach developed by the Medical Internal Radiation Dose (MIRD) Committee of the Society of Nuclear
Medicine for the estimation of average absorbed dose from
internally deposited radionuclides has been applied to radiolabeled MoAb therapy in animals and humans, as described in the paper by Watson et al. 4 in this report. The
classic MIRD formulation widely used for macroscopic
dosimetry problems assumes a uniform distribution of cumulated activities of radiolabeled MoAbs within each
source region and a uniform deposition of energy within
each target region. The experimental animal and clinical
patient studies clearly demonstrate that radiolabeled
MoAbs are not uniformly distributed within solid tumors.
There are point-source calculations available within the
MIRD pamphlets to deal with the problem of dose heterogeneity encountered in RIT.
In addition to the problem of nonuniform uptake of
radiolabeled MoAbs in solid tumors, the macroscopic
MIRD approach does not distinguish between a uniform
distribution of radiolabeled MoAb that binds to the cell
surface and a uniform distribution of nonspecific radiolabeled MoAb.
Conventional MIRD type calculations for radiolabeled
MoAbs give approximate average dose estimates which
may not be sufficiently accurate, especially for alpha and
Auger emitters. With these types of radionuclides, a microdosimetric approach will be required, as described below.
C. Pharmacokinetics modeling
Pharmacokinetics modeling involves an attempt to estimate the biokinetics of tumor and normal organ uptake of
radiolabeled MoAbs on both a macroscopic and microscopic level, and then to perform the dosimetric calculations. It is an essential component for estimation of cumulated activities in the various source regions of the body.
Research is still required to find accurate and predictive
models of both macroscopic and microscopic pharmacokinetics. This subject is reviewed by Strand et al. 5
D. Calculation techniques for RIT
Leichner and Kwok6 in this report provide a critical
analysis of the calculational approaches that have been
used for beta particle tumor dosimetry in RIT. In modeling
of absorbed dose distributions, analytical, numerical, and
Monte Carlo methods have been used to investigate the
effects of uniform and nonuniform activity distributions
associated with RIT.
E. Microdosimetry
Alpha emitters and internalized Auger electron emitters
may be useful in RIT because of their high LET and RBE.
However, the methodology to calculate dosimetry for short
range alpha emitters and internalized Auger emitters must
consider energy deposition at the cellular and subcellular
level. Such a microdosimetric approach which analyzes the
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
500
effect of source microdistribution on individual cells has
been taken by a number of investigators, because of the
limitations of the macroscopic MIRD formulation and the
nonuniformity of the radiolabeled antibody in tumor.
Humm et al.7 in this report summarize approaches that
are being used to estimate the microdosimetry of RIT. It
should be noted, however, that microdosimetry estimates
are based on modeling and are difficult to substantiate experimentally.
F. Autoradiography, thermoluminescent dosimetry,
and three-dimensional dose calculations
Radionuclide activity variations within tumors can be
measured by quantitative autoradiography. However,
quantitative autoradiography alone cannot provide total
dose measurements, because of the temporal change in radiolabeled antibody uptake, penetration, and clearance.’
Yorke et al.8 note that autoradiography and thermoluminescent dosimetry are complementary techniques. Autoradiography shows the activity distribution at a particular point in time, whereas TLDs are integrating dosimeters
performing spatial and temporal integrations within the
volume they occupy, and can be used to calibrate the autoradiographs.
Griffith et al9 and Roberson et al.10 c o n v e r t e d d a t a
from serial autoradiographs to derive three-dimensional
activity matrices in animal tumor xenografts. Using point
source function calculation techniques, two-dimensional
isodose curves’ or three-dimensional dose-rate curves 1 0
were generated showing marked dose heterogeneity in
most tumor systems examined. Further studies remain to
be performed to be able to relate the dose-rate distributions
to time averaged dose distributions, cell kill, and eventually
to therapeutic efficacy.
G. Experimental RIT
Radiolabeled MoAbs have been used for RIT of spheroids and a variety of murine syngeneic tumors and human
tumor xenografts. The results are summarized in the paper
by Buchsbaum et al. in this report.” The approaches taken
to estimate tumor dosimetry in the experimental animal
studies include the MIRD approach, thermoluminescent
dosimetry, autoradiography, and comparison to external
beam irradiation. The uniform geometry of the spheroid
has facilitated the estimation of radiation dose. The two
most important factors for therapeutic efficacy in the
spheroid model are good penetration of the radiolabeled
MoAb and an adequate half-life of the radionuclide to exceed the time of penetration. The results in animal studies
indicate that MoAbs radiolabeled with a variety of radionuclides have been effective in inhibiting tumor growth or
producing cures against a variety of tumor types. The majority of investigators have estimated the dose to tumor
using the MIRD formalism. A few investigators have estimated the dose to tumor using TLDs and autoradiography.
The effectiveness of RIT depends on a variety of factors
including antibody specificity, affinity and immunoreactivity, tumor vascularity, and differential radiation sensitivity
501
D. J. Buchsbaum and B. W. Wessels: Introduction: Radiolabeled antibody tumor dosimetry
of the various tumor types. It must be kept in mind that
there are limitations of spheroid and animal models in
modeling what occurs in the clinical situation. 11,12
501
is a potential advantage in therapeutic ratio predicted for
alpha particle radiation when bone marrow (high linearquadratic alpha/beta ratio) is considered as the critical
organ. 17
H. Imaging techniques and treatment planning
Leichner et al. 13 in another section of this report have
reviewed the various imaging techniques that have been
used for RIT treatment planning. They discuss tumor and
normal organ volume computations from CT and MRI
data, correlative image analysis, and treatment planning
for RIT.
I. Clinical studies with dosimetry
There have been a large number of clinical RIT studies
that have included tumor dosimetry estimates. The approaches that have been taken in lymphoma, solid tumors,
and intraperitoneal therapy are described in three manuscripts in this report. 14-16
Radiation dosimetry in B-cell lymphoma patients has
been done using the MIRD approach. Organ and tumor
radionuclide activity measurements have usually been done
with conjugate view planar scintillation camera imaging. 14
Organ and tumor volumes have been obtained by CT,
SPECT, or the published values of the MIRD committee.
The range of tumor absorbed dose estimates in five clinical
lymphoma studies is reported.1 4
For solid tumors, the MIRD approach, planar imaging
and tumor volumetrics have been performed in a similar
manner as in lymphoma studies. 15 There have been wide
variations in estimated tumor doses in different studies,
and no definite dose-response relationship has been observed. The spatial resolution limits of planar or SPECT
imaging devices prevents detection of the nonuniformity of
radiolabeled MoAb deposition, and thus permits only the
estimation of average dose to tumor.
Regional administration of radiolabeled MoAbs has
been used in the peritoneum, the cerebral spinal fluid, the
pleural/pericardial cavity, and within cystic brain tumors.
Roeske et al.16 have reviewed the methods and results that
have been used for intraperitoneal dosimetry.
J. Radiobiology of RIT
Langmuir et al.17 elsewhere in this report reviewed the
information available on the radiobiology of low-dose- rate
external beam irradiation and RIT as applied to tumor
dosimetry, and have discussed comparisons between the
two. Langmuir et al. 17 have concluded that tumors most
likely to respond to RIT would be those types that are
inherently radiosensitive, those with a poor capacity to repair radiation damage or with long repair half-times, those
tumors that are susceptible to blockade in sensitive phases
of the cell cycle, and tumors that reoxygenate rapidly.
A comparison of alpha and beta emitters for RIT indicates an advantage for beta emitters if the linear-quadratic
alpha/beta ratio for tumors is greater than that of the critical organ of toxicity, as is the usual case. However, there
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
ACKNOWLEDGMENTS
We thank Donell Berry for typing the manuscript. Supported by NIH Grant CA44173 and the Elaine Snyder
Cancer Research Award.
“Correspondence should be sent to: Donald J. Buchsbaum, Ph.D., Department of Radiation Oncology, University of Alabama at Birmingham, 619 South 19th Street. Birmingham, AL 35233-6832.
1
J. A. Siegel, B. W. Wessels, E. E. Watson, M. G. Stabin. H. M. Vriesendorp, E. W. Bradley, C. C. Badger, A. B. Brill, C. S. Kwok, D. R.
Stickney, K. F. Eckerman. D. R. Fisher, D. J. Buchsbaum, and S. E.
Order, “Bone marrow dosimetry and toxicity for radioimmunotherapy,” Antib. Immunoconj. Radiopharm. 3, 213-233 (1990).
2
S. A. Leibel, S. E. Order, D. R. Fisher, J. R. Williams, and R. J.
Morton, “Physics and biology of radiolabeled antibodies workshop,
sponsored by the Radiation Research Branch, National Cancer Institute, Division of Cancer Treatment, February 12-13, 1987, Bethesda,
Maryland,” Antib. Immunoconj. Radiopharm. 1, 271-282 (1988).
‘L. F. Mausner and S. C. Srivastava, “Selection of radionuclides for
radioimmunotherapy,” Med. Phys. 20, 503-509 (1993).
4
E. E. Watson, M. G. Stabin, and J. A. Siegel, “MIRD formulation,”
Med. Phys. 20, 511-514 (1993).
5
S.-E. Strand, P. Zanzonico, and T. K. Johnson, “Pharmacokinetic
modeling,” Med. Phys. 20, 515-527 (1993).
6
P. K. Leichner and C. S. Kwok, “Tumor dosimetry in radioimmunotherapy: Methods of calculation for beta particles,” Med. Phys. 20,
529-534 (1993).
7
J. L. Humm, J. C. Roeske, D. R. Fisher, and G. T. Y. Chen, “Microdosimetric concepts in radioimmunotherapy,” Med. Phys. 20, 535-541
(1993).
8
E. D. Yorke, L. E. Williams, A. J. Demidecki, D. B. Heidorn, P. L.
Roberson, and B. W. Wessels, “Multicellular dosimetry for betaemitting radionuclides: Autoradiography, thermoluminescent dosimetry and three-dimensional dose calculations,” Med. Phys. 20, 543-550
(1993).
9
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
10
P. L. Roberson, D. J. Buchsbaum, D. B. Heidom, and R. K. Ten
Haken, “Three-dimensional tumor dosimetry for radioimmunotherapy
using serial autoradiography,” Int. J. Radiat. Oncol. Biol. Phys. 24,
329-334 (1992).
11
D. J. Buchsbaum, V. K. Langmuir, and B. W. Wessels, “Experimental
radioimmunotherapy,” Med. Phys. 20, 551-567 ( 1993).
12
B. W. Wessels, “Current status of animal radioimmunotherapy,” Cancer Res. (Suppl.) 50, 970s-973s (1990).
13
P. K. Leichner, K. F. Koral, R. J. Jaszczak, A. J. Green, G. T. Y.
Chen, and J. C. Roeske, “An overview of imaging techniques and
physical aspects of treatment planning in radioimmunotherapy,” Med.
Phys. 20, 569-577 (1993).
14
J. A. Siegel, D. M. Goldenberg, and C. C. Badger, “Radioimmunotherapy dose estimation in patients with B-cell lymphoma,” Med. Phys.
20, 579-582 (1993).
15
R. F. Meredith, T. K. Johnson, G. Plott, D. J. Macey, R. L. Vessella,
L. A. Wilson, H. B. Breitz, and L. E. Williams, “Dosimetry of solid
tumors,” Med. Phys. 20, 583-592 (1993).
16
J. C. Roeske, G. T. Y. Chen, M. Reese, and A. B. Brill, “Dosimetry of
intraperitoncally administered radiolabeled antibodies,” Med. Phys. 20,
593-600 (1993).
17
V. K. Langmuir, J. F. Fowler, S. J. Knox, B. W. Wessels, R. M.
Sutherland, and J. Y. C. Wong, “Radiobiology and radiolabeled antibody therapy as applied to tumor dosimetry,” Med. Phys. 20, 601-610
(1993).
Selection of radionuclides for radioimmunotherapy
Leonard F. Mausner and Suresh C. Srivastava
Medical Department, Brookhaven National Laboratory, Upton. New York I I973
(Received 18 March 1992; accepted 6 October 1992)
I. INTRODUCTION
The potential of utilizing monoclonal antibodies (MoAb)
as carriers of radionuclides for the selective destruction of
tumors (radioimmunotherapy, RIT) has stimulated much
research activity. The approach should be specially beneficial for treatment of tumors not easily amenable to surgical control, for treatment of early recurrence and of distant metastases. However, from dosimetric and other
considerations, the choice of radiolabel is an important
factor that needs to be optimized for maximum effectiveness of RIT. Most therapeutic trials to date have utilized
131
I, largely due to its ready availability at moderate cost,
the ease of halogenation techniques for proteins, and its
long history of use in treating thyroid malignancy, rather
than any careful analysis of its suitability for RIT. This
paper briefly reviews the present and future radionuclides
that are considered particularly suitable for RIT.
II. SELECTION CRITERIA
The selection criteria must be based on the physical data
about the radionuclide, its production and chemistry and
the biological variables governing its use. The important
physical variables to consider include the radionuclide
half-life, the type, energy, and branching ratio of particulate radiation and the gamma-ray energies and abundances. It is important to match the physical half-life with
the antibody in vivo pharmacokinetics. If the half-life is too
short, most decay will have occurred before the MoAb has
reached maximum tumor/background ratio.
Conversely, considerations of tumor radiobiology and
low radionuclide/antibody specific activity may also limit
the use of long-lived radionuclides. For equal radioactivity
concentrations in the target, radionuclides with long half
lives will produce a lower absorbed dose rate than those
with short lifetimes. If the maximum absorbed dose rate
from beta particles is much lower than that typical in
brachytherapy (40-64 cGy/h), cell kill per cGy is
decreased.1,2 The theoretical low specific activity of longer
lived radionuclides would thus require a large mass of radionuclide, ligand, and antibody to achieve adequate dose
rate. This can make the use of long-lived radiolabels less
desirable. However, if a two or three-stage therapy approach is utilized,3 it becomes useful to consider the use of
long-lived beta emitters, e.g., 3 2P and others. To some extent the problem of low target dose rate may be counteracted by a number of factors including high nonpenetrating equilibrium dose constant, high target to nontarget
ratio, high carrier labeling efficiency, and the ability to
administer a large protein mass (tumor saturation effect).
The type of particulate emission also must be considered. The potent lethality of Auger and low-energy conver503
Med. Phys. 20 (2). Pt. 2, Mar/Apr 1993
sion electrons has been demonstrated. 4-8 This effect can
best be realized with intranuclear localization of the radionuclide, which does not generally occur with radiolabeled
MoAb. Of course, a particles have a high linear energy
transfer (LET) effective in cell killing and a range of several cell diameters, 40-80 µm. The short ranges will accentuate inhomogeneous absorbed dose particularly when the
MoAb deposition is inhomogeneous. Beta particles are less
densely ionizing and have a range longer than a’s so that
the distribution requirements are less restrictive for RIT of
bulky disease. On the other hand, for micrometastases, the
absorbed fraction for higher energy beta particles (range
> tumor size) is decreased, leading to a less favorable tumor absorbed dose. The gamma-ray energies and abundances are also important physical properties, because the
presence of gamma rays offers the possibility of external
imaging but also adds to the whole body dose. These physical properties alone can be used to calculate radiation absorbed dose at the cellular level. This approach has been
used by Jungerman et al. 9 to estimate delivered doses for
RIT. An approach which explicitly includes biodistribution and kinetic data by using an idealized time-dependent
averaged target-to-nontarget uptake ratio is that of Wessels
and Rogus.1 0 Although the quantitative dose ratios are
highly dependent on the input biodistribution data, a comparison of the relative effectiveness of the radiolabels was
demonstrated. This relative efficacy was approximately
constant for reasonable variation of model parameters in
accordance with observed biological data. A similar approach was used recently by Yorke et al. 11 Also, Humm1 2
has considered the effect on MoAb dosimetry of varying
tumor size and of cold regions. These papers underscore
the importance for therapy of a high ratio of nonpenetrating to penetrating (γ) radiations. The complex relationship between tumor curability with different radionuclides
and tumor size has been reviewed by Wheldon and
O’Donoghue. 13
The main chemical variables to be considered in choosing a radionuclide for therapy with monoclonal antibodies
are the radionuclide specific activity achievable, metal-ion
contamination, the number of labels per MoAb molecule
obtainable without loss of immunological activity, and the
stability of the radionuclide-protein attachment. The specific activity, or amount of activity per mass of the element
in question (MBq/mg), depends primarily on the method
of production. Simple neutron absorption reactions (e.g.,
n ,γ) generally give low specific activity since the radionuclide cannot be chemically separated from a target of the
same element. Accelerator-based proton, deuteron, or
alpha-induced reactions are intrinsically no-carrier-added
(NCA) methods that do allow chemical separation of
0094-2405/93/020503-08$01.20
© 1993
Am. Assoc. Phys. Med.
503
504
L F. Mausner and S. C. Srivastava: Radionuclides for radioimmunotherapy
product from the target. This can also be achieved at reactors by neutron absorption reactions leading to an intermediate product with a beta decay to the desired final
product, or by fast neutron reactions such as (n,p). The
achievable specific activity of these NCA methods then
largely depends on the impurity levels of the product element in the target or in various reagents used in processing.
An often overlooked source of carrier is due to the direct
production of stable isotopes of the product element. Although this effect is often negligible compared to carrier
introduced with the target, it can become significant with
very pure targets and high bombarding energies. With increasing energy, the typical peaks in nuclear excitation
functions broaden, usually reaching a plateau at approximately 150-200 MeV and reaction cross sections for neighboring isotopes become comparable over large energy
ranges. Some of these issues have been reviewed recently
for therapeutic radionuclides.1 4
The presence of metal ions other than the product is a
concern as they can compete for binding sites on chelateMoAb conjugates. It is largely controlled by the selectivity
of the chemical separation scheme, but this process is not
perfect. For example, a normally adequate separation factor of 10-7 on a 10 g target still leaves 1 µg of target in the
product which may be of concern when labeling at low
protein concentrations. Indeed, measurement of these stable species at low concentration in radioactive solutions is
often a very difficult practical problem. Although various
analytical procedures exist for detecting ions at subpart per
million levels, for example atomic absorption, emission
spectroscopy, and x-ray fluorescence, these techniques often take time, utilize expensive instrumentation, and may
require a large fraction of the final product solution for the
measurement. Generally, the sooner the radionuclide is
used the better, because its specific activity is highest, and
this need competes with the desire to measure the specific
activity and the impurity levels. Also, it is typical for many
research groups that the expensive analytical apparatus is
not wholly owned. Instead, access is through a shared-use
facility whose operators are very reluctant to introduce
radioactive material into their equipment. Thus the fastest,
albeit indirect method, of determining carrier levels may
simply be by titration with chelate during labeling.
The convenience, efficiency, and gentleness of various
radiolabeling procedures as well as the stability of the radionuclide attachment to the antibody are all very important factors which are being actively investigated by many
groups. They will not be considered further here as these
topics are beyond the scope of this paper and have been
reviewed several times.15-18 While recognizing the difficulties in designing new conjugation schemes, at this point, it
is simply assumed that adequate radiolabeling techniques
either exist or will become available for use with radionuclides to be discussed.18 However, another practical aspect
to be considered is that of radionuclide production-the
routine availability, at reasonable cost, of quantities of radioactivity suitable for therapy. At present, only 131 I truly
meets all of these production criteria. However, this situMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
504
ation is changing for several other attractive radionuclides
to be discussed below.
These physical and chemical factors must then be
viewed in light of available biological information. There is
substantial variation in antibody uptake, macro- and
micro-distribution, kinetics and processing (metabolism/
catabolism) depending on the particular antibody, antibody dose, the variability of antigenic expression in the
tumor, its size and stage, etc. Limitations due to normal
tissue radiotoxicity are not entirely the function of radionuclide emissions but are largely governed by the pharmacokinetics of the antibody. For many of the MoAbs and
MoAb fragments currently being investigated for immunotherapy some generalities emerge. It is generally believed
that one-half to three days is usually required to reach
maximum tumor uptake19-22 although optimum contrast
with whole MoAbs may take longer. Despite the presence
of numerous antigen sites on cancer cells, evidence from
tumor implanted microthermoluminescent dosimeter
25
p r o b e s 2 3 , 2 4 and autoradiography indicates a nonuniform
cellular distribution of the MoAb in most cases. This may
be due to cell type heterogeneity, 26 heterogeneity of antigenic expression,27 poor delivery, and spatial inaccessibility. These factors considerably reduce the attractiveness of
short-ranged alpha-emitting radionuclides for radioimmunotherapy. A role for alpha emitters may be feasible in
specific cases such as for micrometastases or intracavitary
administration for some types of cancers, such as peritoneal injection for ovarian carcinoma. 28,29 The longer range
of beta particles can still permit uniform tumor irradiation
despite a marked heterogeneity of distribution of radioactivity within the tumor. It appears desirable to deliver ionizing radiation with a range of one to several millimeters in
tissue, as from intermediate to high-energy beta particles.
Ill. CANDIDATE RADIONUCLIDES
Relatively few alpha emitting radionuclides have been
considered for RIT. Bismuth-212 (t1/2= 60.5 min, E α = 7.8
MeV) and 2 1 1At ( t1/2 = 7.2 h, E α = 6.8 MeV) are the two
nuclides that have been most studied. 30-36 The 212 Bi can be
available via a 2 2 4Ra generator system,37 while 2 1 1At is accelerator produced.38,39 The short half-life of 2 1 2 Bi is not
well matched to MoAb uptake kinetics but it might be
possible to conjugate its parent 212 Pb, with a 10.6 h halflife, to a MoAb or MoAb fragment and thus generate the
alpha emitter in vivo. The feasibility of this approach is
212
under investigation.4 0 Nevertheless, the peak of B i
growth occurs at 3.8 h which is probably still too short for
the peak in tumor uptake. The short life time of 211 At and
limited availability may impede its use except in very special situations.4 1
It has been suggested 28 that the 20.1 h half-life of 255 F m
is more appropriate for RIT. Unfortunately this nuclide
and similar alpha emitting heavy radionuclides (atomic
number > 82) are the parents or members of long decay
chains involving both alpha and beta emission. Because the
nuclear recoil from the alpha (and some of the beta) decays are considerably more energetic than chemical bond
strengths, these transitions are capable of rupturing the
505
L. F. Mausner and S. C. Srivastava: Radionuclides for radioimmunotherapy
505
199
radionuclide-ligand bond. Unless the daughter half-life is
less than a few minutes it will be free to diffuse away from
the tumor. Worse still, most of these heavy elements tend
to irreversibly lodge in bone.
Beta emitters offer a much wider choice of candidates
with a selection of particle ranges and chemical properties.
The use of radionuclides with some gamma emission would
allow diagnostic low-dose experiments to determine biodistribution prior to administering a therapeutic dose of the
exact same preparation. This is a real advantage because it
has been observed 42,43 that the biodistribution can be influenced by the choice of radionuclide alone, even with the
same chelate-antibody complex. It is possible that these
differences reflect the redistribution of the radioactivity following catabolism of the antibody after localization. Clinically it may be necessary to image each patient prior to
therapy in order to assess antigenic status and to calculate
tumor and sensitive tissue doses from the observed biodistribution. The disadvantage of this choice is that, because
of the penetrating nature of the gamma radiation, a less
than optimum target/nontarget dose ratio may result.
Preferably, the g energy should be below 300 keV and the
g abundance sufficient for visualization in vivo A number
of attractive radionuclides and their properties are listed in
Table I.44 Of these, 6 7 Cu has been previously identified as
possessing attractive physical properties for RIT,10 and is
being actively investigated by several groups. 45-47 Another
advantage is that 67Cu, upon eventual dissociation from its
ligand in vivo, does not preferentially localize in bone, kidney, or liver, in contrast to many other radiometals. Al153
though the pharmaceutical Sm-ethylenediaminetetramethylenephosphonic acid (EDTMP) shows potential as a
bone cancer agent,48,49 very little has been reported on the
use of 1 5 3 Sm as an antibody label. 50 However, as can be
seen from Table I its physical properties fulfill many criteria discussed above. Similarly, 1 0 5Rh has received some
attention,” and more recently 4 7S C (Refs. 52,53) and
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
Au.54,55 Iodine-131 is in the therapeutic class but clearly
its long half-life and high abundance of 364 keV photons
make for less attractive tumor/nontarget dose ratios than
the other candidates. Nevertheless, due to its ready availability, ease of labeling, and more rapid clearance from
kidney and liver than most metal chelates particularly
when using methods that produce negligible dehalogenation in vivo,56-59 it has been widely used for RIT (e.g., Refs.
60 and 61).
When radionuclides with little or no γ emission that
produce better target/nontarget dose ratios are used, preliminary biodistribution studies must often be performed
with other diagnostic radionuclides, and these studies are
often radionuclide dependent. Alternatives which can be
investigated include bremsstrahlung imaging or substituting a better y-emitting isotope of the same element. Unfortunately, scintigraphic resolution from bremsstrahlung
may be poor, making quantitation for dosimetry difficult.
Because of its high-energy beta particle, suitable half-life,
good chelation properties and availability, several groups
are currently studying the use of 9 0Y as a RIT labe1.62-64
Since 9 0Y is unsuitable for quantitative imaging, many
111
groups are utilizing In biodistribution data to predict
90
dose from Y administrations. However, even though
there are similarities in tumor uptake, blood clearance, and
other tissue uptakes, often there are substantial differences
in retention and clearance from kidney and the reticuloendothelial system. For example, it was recently shown that
although intravascular kinetics in patients are similar for
90
Y and 111 In labeled T101 antibody using isothiocyanatobenzyl DTPA, the two preparations differ in their tissue
biodistribution. 65 Yttrium-88 is a suitable stand-in for studies in animals but it is not widely available and cannot be
used in humans because of undesirable decay properties.
Even though imaging photons in 186 Re can be used particularly at therapeutic dose levels 66,67 the “matched pair”
186
approach using 9 9 m Tc and Re, the former for imaging
and the latter for therapy is a very attractive option. 6 7
These can both be attached to antibodies via similar
c h e m i s t r y6 7 , 6 9 and generally produce similar biodistributions. Additionally, 109 Pd (Ref. 70) has also been investigated for immunotherapy. Although 1 0 9 Pd, 1 4 2 Pr, and
159
Gd all have half-lives of somewhat less than one day,
they could be useful for MoAb or MoAb fragment systems
that demonstrate a more rapid tumor uptake. Genetic engineering of antibodies with functionalities for binding of
99m
gamma emitters (e.g., Tc) inserted into their structure
may allow imaging with the same preparations prior to
therapeutic administration of the beta emitter. 3
IV. RADIONUCLIDE PRODUCTION
The criteria for the isotopes listed in Table I were the
match between the radionuclide physical properties and
the biological model used. Obviously, the possible production techniques and resultant specific activity must also be
considered. In a reactor, uranium fission, radiative neutron
capture and fast-neutron reactions can be employed. In
accelerators, a wide range of particles (p,d,a, etc.) of varying energy is available. Table II gives recommended pro-
506
L. F. Mausner and S. C. Srivastrva: Radionuclides for radioimmunotherapy
duction routes for the various radionuclides of Table I. The
nuclear reactions have acceptable cross sections for producing therapeutic quantities. There is a large range in the
total activity and specific activity achievable for these radionuclides. For therapy, it is reasonable to assume that a
minimum of 1.8 GBq will be required per treatment. It is
more difficult to place a lower limit on the required specific
activity. This depends on the chemical sensitivity of the
particular antibody system to labeling conditions and on
protein concentration requirements due to the presence of
carrier. The availability and cost of the antibody becomes a
factor, since larger amounts of antibody are required to
bind enough radioactivity as well as the chemically identical cold atoms. This concern has become less critical recently as production techniques have improved and since
many clinical protocols already use large (>50mg)
amounts of antibody. A specific activity of approximately
100 GBq/mg will nonetheless be a highly desirable goal.
Adequate quantity and quality of 131I are available commercially. Copper-67 is produced by high energy spallation
reactions in the Brookhaven Linac Isotope Producer
(BLIP) at Brookhaven National Laboratory” and the Los
Alamos Meson Physics Facility (LAMPF) at Los Alamos
National Laboratory and is available from these institutions most of the year. Although this is intrinsically a nocarrier-added method, ubiquitous trace Cu impurities limit
achievable specific a c t i v i t y t o a p p r o x i m a t e l y 2 5 0
G B q / m g . 71,72 The fast neutron reaction on enriched 6 7Z n
can be used to fill in the gaps in the operating schedules of
the large accelerators. Large quantities of 1 5 3Sm can be
produced very simply by thermal neutron activation because of its large cross section (σ= 208 barns) and epitherma1 resonance integral (3000 barns).73 A similar situation
exists for 1 7 7Lu (σ=2100 barns). Nevertheless, adequate
specific activity can probably only be achieved at nuclear
reactors with neutron fluxes of greater than 3 x 10 14 n/cm2
s [e.g., the High Flux Beam Reactor (HFBR) at
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
506
Brookhaven National Laboratory, High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, and U.
Missouri Research Reactor]. With a neutron capture crosssection of 111 barns, 194 Ir production is not as attractive as
153
Sm and 1 7 7 Lu but still feasible at the above reactors.
Samarium and lutetium are rare earth elements which can
be readily chelated for linkage to antibodies. However, the
in vivo stability of these preparations will need to be carefully investigated due to the high affinity of these metals for
bone and the well-known tendency of rare earth elements
to form colloids in vivo and thence concentrate in the reticuloendothelial system including bone marrow.
There are two possible routes for the production of
199
Au. The double neutron capture reaction on natural
gold leads to high yield because of the enormous cross
section of 198 Au (26000 barns), but the specific activity is
inadequate for RIT. Thus the indirect reaction on 198Pt
f o l l o w e d b y β d e c a y t o 1 9 9A u h a s r e c e n t l y b e e n
investigated 54,74 and appears to be practical. A similar
method for 1 0 5 Rh can be used. For both these radionuclides, production at a high flux reactor will be advantageous. Rhenium-188 is especially interesting because it can
be prepared in high specific activity from a convenient
188
W /1 8 8 R e g e n e r a t o r s y s t e m . T h e 1 8 8 W /1 8 8 R e s y s t e m
could be considered a therapeutic analog to the
99
M o /9 9 m Tc generator since the chemistry of rhenium in
many ways is similar to that of technetium. 68,69 Unfortunately the 188W parent can only be produced in low specific
activity by a double neutron capture reaction, which limits
the total activity of 188 W that can be loaded on an alumina
column.” A gel-type generator partially overcomes this
limitation. 7 6
One of the most widely used radionuclides is actually
produced via a generator system, i.e., 90Sr/90Y. This allows
repeated use of the 9 0Y for a lifetime since the half-life of
90
Sr is 29 years; a great convenience. The 9 0Sr/9 0Y generator (e.g., Refs. 77 and 78), is not available commercially
as a system but 90Y alone can be purchased commercially.
Without any gamma emissions, in vivo biodistribution
studies remain a problem. Also, the in vivo stability of
earlier DTPA-based chelates for use with 9 0Y is not
o p t i m u m . 7 9 , 8 0 Recent studies with macrocyclic ligands 81-83
and certain carbon backbone substituted DTPA ligands, 8 4
however, show enhanced stability in serum and improved
biodistribution. The safety of research personnel is a concern with 90Sr because of its high toxicity. The high energy
beta emission, long life, and propensity to concentrate in
bone make the maximum permissible body burden of 9 0S r
only 2 µCi. Further, contamination monitoring for 9 0S r
and 9 0Y are complicated due to the lack of gamma emissions.
Rhenium-186 is an attractive alternative but requires a
high flux reactor to achieve adequate specific activity.
Therapeutic quantities of “As may be quite difficult to
produce because of the instability of selenide targets at
high beam current. Various alloy targets have been
developed 85 but can be used only up to 20 µA. Additionally, existing chelation methods are not suitable for attaching arsenic to MoAbs. The production of large quantities
507
L F. Mausner and S. C. Srivastava: Radionuclides for radioimmunotherapy
o f 1 0 9Pd is straightforward, but with a specific activity at
the lower end of this compilation. Since this may not be a
serious problem in the future, its ease of production and
favorable labeling chemistry” make it a possible candidate
for RIT.
The remaining entries in Table II are rare earth elements and would be expected to have chemical behavior
similar to 153Sm. There are two possible reactions to make
142
Pr, offering either high yield or high specific activity, a
situation analogous to 199 Au. Promethium-149, 166 Ho, and
159
Gd could be produced in adequate yield and high specific activity and so are also reasonable candidates.
ACKNOWLEDGMENTS
We would like to acknowledge the valuable discussions
and critical review contributed by E. D. Yorke and B. W.
Wessels. The comments of D. J. Buchsbaum, K. E. Britton, J. Humm, and W. A. Volkert were also helpful in the
preparation of this manuscript. This work was supported
by the Office of Health and Environmental Research, U.S.
Department of Energy, under Contract No. DE-AC0276CH00016. Thanks are due to Ms. S. Cataldo for help
with the preparation of this manuscript.
1
J. F. Fowler, “Radiobiological aspects of low dose rates in radioimmunotherapy,” Int. J. Radiat. Oncol. Biol. Phys. 18, 1261-1269 (1991).
2
R. G. Dale, “The application of the linearquadratic dose-effect equation to fractionated and protracted radiotherapy,” Br. J. Radiol. 58,
515-528 (1985).
3
K. E. Britton, S. J. Mather, and M. Granowska, “Radiolabelled monoclonal antibodies in oncology III. Radioimmunotherapy,” Nucl. Med.
Commun. 12, 333-347 ( 1991).
4
E. W. Bradley, P. C. Chan, and S. J. Adelstein, “The radiotoxicity of
I-125 in mammalian cells. I. Effects on the survival curve of radioiodine
incorporated into DNA,” Radiat. Res. 64, 555-563 (1975).
5
P. C. Chan, E. Lisco, H. Lisco, and S. J. Adelstein, “The radiotoxicity
of I-125 in mammalian cells. II. A comparative study on cell survival
and cytotoxic responses to IUdR-125, IUdR-132, and HTdR-3,” Radiat. Res. 67, 332-343 (1976).
6
A. I. Kassis, S. J. Adelstein, C. Haycock, K. S. R. Sastry, K. D.
McElvany, and M. J. Welch, “Lethality of Auger electrons from the
decay of Br-77 in the DNA of mammalian cells,” Radiat. Res. 90,
362-373 (1982).
7
S. J. Adelstein and A. I. Kassis, “Radiobiologic implications of the
microscopic distribution of energy from radionuclides,” Nucl. Med.
Biol. 14, 165-169 (1987).
8
L. E. Feinendegen, “Biological damage from the Auger effect: Possible
benefits,” Radiat. Environ. Biophys. 12, 85-99 (1975).
9
J. A. Jungerman, P. Yu Kin-Hung, and C. I. Zanelli, “Radiation absorbed dose estimates at the cellular level for some electron emitting
radionuclides for radioimmunotherapy,” Int. J. Appl. Radiat. Isot. 35,
883-888 (1984).
10
B. W. Wessels and R. D. Rogus, “Radionuclide selection and model
absorbed dose calculations for radiolabeled tumor-associated antibodies,” Med. Phys. 11, 638-645 (1984).
11
E. D. Yorke, P. L. Beaumier, B. W. Wessels, A. R. Fritzberg, and A.
C. Morgan, Jr., “Optimal antibody-radionuclide combinations for clinical radioimmunotherapy: A predictive model based on mouse pharmacokinetics,” Nucl. Med. Biol. 18, 827-835 ( 1991).
12
J. L. Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
13
T. E. Wheldon and J. A. O'Donoghue, “The radiobiology of targeted
radiotherapy,” Int. J. Radiat. Biol. 58, 1-21 (1990).
14
W. A. Volkert, W. F. Goeckeler, G. J. Ehrhardt, and A. R. Ketring,
“Therapeutic radionuclides: Production and decay property considerations,” J. Nucl. Med. 32, 174-185 (1991).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
507
“A. R. Fritzberg, R. W. Berninger, S. W. Hadley. and D. W. Webster,
“Approaches to radiolabeling of antibodies for diagnosis and therapy of
cancer,"
Pharm. Res. 5, 325 (1988).
16
D. I. Hnatowich, “Antibody radiolabeling, problems and promises,”
Nucl. Med. Biol. 17, 49-55 (1990).
17
O. A. Gansow, “Newer approaches to the radiolabeling of monoclonal
antibodies by use of metal chelates,” Nucl. Med. Biol. 18, 369-381
(1991).
18
S. C. Srivastava and R. C. Mease, “Progress in research on ligands,
nuclides and techniques for labeling monoclonal antibodies,” Nucl.
Med. Biol. 18, 589-603 (1991).
19
S.J. DeNardo, K. Erickson, E. Benjamini, H. Hines, R. Scibienski, and
G, DeNardo, “Monoclonal antibodies for radiation therapy of melanoma,” in Nuclear Medicine and Biology, edited by C. Raynaud (Pergamon, Paris, 1982), p. 182.
20
S. Larson. J. Carrasquillo, J. Reynolds, A. Keenan, P. Sugarbaker, D.
Colcher, J. Schlom, R. Neumann, I. Hellstrom, K. Hellstrom, J.
Mulshine, M. Lotz, and P. Strudler, “The National Institutes of Health
experience with radiolabeled monoclonal antibodies: Lymphoma, melanoma and colon cancer,” in Radiolabeled Monoclonal Antibodies for
Imaging and Therapy, edited by S. C. Srivastava Vol. 152 (Plenum,
New York, 1988). pp. 393-407.
21
G. DeNardo, S. J. DeNardo, and D. J. Macey, “Quantitative pharmacokinetics of radiolabeled monoclonal antibodies for imaging and therapy in patients,” in Radiolabeled Monoclonal Antibodies for Imaging
and Therapy, edited by S. C. Srivastava (Plenum, New York, 1988),
pp. 293-3 10.
22
D. A. Scheinberg and M. A. Strand, “Kinetic and catabolic considerations of monoclonal antibody targeting in erythroleukemia mice,”
Cancer Res. 43, 265-272 (1983).
23
B.W. Wessels, M. H. Griffith, E. W. Bradley, and B. Skibinski, “Dosimetric measurements and radiobiological consequences of radioimmunotherapy in tumor bearing mice,” in Fourth International Radiopharmaceutical Dosimetry Symposium, edited by A. T. Schlafek-Stelson
and E. E. Watson (Oak Ridge Associated Universities, Oak Ridge,
1985), pp. 446-457.
24
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy. “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
25
F. Buchegger, A. Vacca, S. Carrel, M. Schreyer, and131J. P. Mach, “Radioimmunotherapy of human colon carcinoma by I-labeled monoclonal anti-CEA antibodies in a nude mouse model,” Int. J. Cancer 41,
127-134 (1988).
26
N.Buick, R. Pullam, J. B. Bizzari, and W. J. Mackillop, “The
phenotypic heterogeneity of human ovarian tumor cells in relation to
cell function,” in Radioimmunoimaging and Radioimmunotherapy, edited by S. W. Burchiel and B. A. Rhodes (Elsevier, New York, 1983),
pp. 3-10.
27
J.W. Fabre and A. S. Daar, “Expression of normal epithelial membrane antigens on human colorectal and breast carcinomas,” in Radioimmunoimaging and Radioimmunotherapy, edited by S. W. Burchiel
and B. A. Rhodes (Elsevier, New York, 1983), pp. 143-157.
28
R. E. Bigler and P. B. Zanzonico, “Adjuvant radioimmunotherapy for
micrometases,” in Radiolabeled MonoclonaI Antibodies for Imaging
and Therapy, edited by S. C. Srivastava (Plenum, New York, 1988),
pp. 409-428.
29
D. S. Wilbur, “Potential use of alpha emitting radionuclides in the
treatment of cancer,” Antib. Immunoconj. Radiopharm. 4, 85-97
(1990).
30
C. L. Ruegg, W. T. Anderson-Berg, M. Brechbiel, S. Mirzadeh, O. A.
Gansow, and M. Strand, “Improved in-vivo stability and targeting of
bismuth labeled antibody,” Cancer Res. 50, 4221-4226 (1990).
31
R. W. Kozak, R. W. Atcher, O. A. Gansow, A. M. Friedman, J. J.
Hines, and T. A. Waldman, “Bismuth-212 labeled anti-TAC monoclonal antibody: a particle emitting radionuclides as modalities for
radioimmunotherapy,” Proc. Natl. Acad. Sci. 83, 474-478 (1986).
32
R. M. Macklis, W. D. Kaplan, J. L. M. Ferrara, R. W. Atcher, J. J.
Hines, S. J. Burakoff, and N. C. Coleman, “Alpha particle radioimmunotherapy: animal models and clinical prospects,” Int. J. Radiat. Oncol. Biol. Phys. 16, 1377a-1387a (1989).
“A. Harrison and L. Royle, “Preparation of a 211At-IgG conjugate
which is stable in-vivo,” Int. J. Appl. Radiat. Isot. 35, 1005-1008
(1984).
“A. T. M. Vaughan, W. J. Bateman, and D. R. Fisher, “The in-vivo fate
508
L. F. Mausner and S. C. Srivastava: Radionuclides for radioimmunotherapy
of At labeled monoclonal antibody with known specificity in a murine
system,” Int. J. Radiat. Oncol. Biol. Phys. 8. 1943-1946 (1982).
35
D. S. Wilbur, M. D. Hylarides, and A. R. Fritzberg, “Reactions of
organometallic compounds with astatine-211 and applications to protein labeling,” Radiochemica Acta 47, 137-142 (1989).
36
I. Brown, “Astatine radiopharmaceuticals. Astatine-211: its possible
applications in cancer therapy,” Int. J. Appl. Radiat. Isot. 37, 789-798
(1986).
37
R. W. Atcher, A. M. Friedman,
and J. J. Hines, “An improved generator for the production of 212Pb and 212Bi from 224Ra,” Int. J. Appl.
Radiat. Isot. 39, 283-286 (1988).
38
R. M. Lambrecht, and S. Mirzadeh, “Cyclotron isotopes and
radiopharmaceuticals-XXXV Astatine-211I,” Int. J. Appl. Radiat.
Isot. 36, 443-450 (1985).
39
R. D. Neirinckx and J. A. Smit, “Separation of Astatine-211 from
bismuth metal,” Anal. Chim. Acta. 63, 201-204 ( 1973).
40
C. Wu, S. Mirzadeh, A. Raubitschek,
K. Kumar, D. Parker, and O.
212
Gansow,
“The
chemical
fate
of
Bi-chelates
formed by β decay of
212
Pb-chelates in solution and localized in cells by linkage to internalizing monoclonal antibodies,” American Chemical Society National
Meeting, 23-28 August 1992 (abstract).
41
M. R. Zalutsky, P. K. Garg, H. S. Friedman, and D. D. Bigner, “Labeling monoclonal antibodies and F(ab’) 2 with the a-particle-emitting
nuclide astatine-211: Preservation of immunoreactivity and in-vivo localizing capacity,” Proc. Natl. Acad. Sci. USA 86, 7149-7153 (1989).
42
D. J. Hnatowich, F. Virzi, and P. W. Doherty, “DTPA-coupled antibodies labeled with Y-90,” J. Nucl. Med. 26, 503-509 (1985).
43S. C. Srivastava and G. E. Meinken, “Correlating labeling chemistry
and in vitro test results with the biological behavior of radiolabeled
proteins,” Int. J. Biol. Markers 1, 111 l-120 ( 1986).
“D. C. Kocher, “Radioactive decay data tables,” DOE/TIC-11026
(1981).
45
S. Mirzadeh, L. F. Mausner, and S. C. Srivastava, “Production of
no-carrier-added Cu-67,” Int. J. Appl. Radiat. Isot. 37, 29-36 (1986).
46
S. V. Deshpande, S. J. DeNardo, C. F. Meares, M. J. McCall, G. P.
Adams, M. K. Moi, and G. L. DeNardo, “Copper-67-labeled monoclonal antibody LYM-1, a potential radiopharmaceutical for cancer
therapy: Labeling and biodistribution in RAJI tumored mice,” J. Nucl.
Med. 29, 217-225 (1988).
47
J.A. Mercer Smith, N. J. Segura, F. J. Steinkruger, Z. V. Svitra, W. A.
Taylor, and P. M. Wanek, “Synthesis and biodistribution of Cu-67
meso-tetra (4-carboxyphenyl) porphine,” Los Alamos National Lab.
Rep., LA-10429-PR, p. 145 (1984).
48
J. Simon, W. F. Goeckler, B. Edwards, L. Stringham, W. A. Volkert,
D. E. Troutner, R. A. Holmes, and S. Harry, “Sm-153-EDTMP, a
potential therapeutic bone agent,” J. Labelled Comp. Radiopharm. 23,
1344-1346 (1986).
49
J. H. Turner, P. G. Caringbold, E. L.
Hetherington, P. Sorby, and A.
A. Martindale, “A phase I study of 153Sm-EDTMP therapy for disseminated skeletal metastases,” J. Clin. Oncol. 30, 1814-1818 (1989).
50
G. R. Boniface, M. E. Izard, K. Z. Walken, D. R. McKay, P. Sorby, J.
H.
Turner, and J. G. Morris, ‘Labeling of monoclonal antibodies with
153
Srn for combined radioimmunoscintigraphy and radioimmunotherapy,” J. Nucl. Med. 30, 683-691 (1989).
51
B. Grazman and D. E. Troutner, “Rh-105 as a potential radiotherapeutic agent,” J. Labelled Comp. Radiopharm. 23, 1371-1373 (1986).
52
K.L. Kolsky, L. Pietrelli, L. F. Mausner, and S. C. Srivastava, “Preparation of carrier-free scandium-47,” J. Nucl. Med. 32, 945 ( 1991)
(abstract).
53
L. Pietrelli, L.47 F. Mausner, and K. L. Kolsky. “Chemical separation of
carrier-free Sc from titanium targets,” J. Radioanal. Nucl. Chem.
157, 335 (1992).
54
P. Anderson,
A. T. Vaughan, and N. R. Varley, “Antibodies labeled
with 199Au: Potential of l99Au for radioimmunotherapy,” Nucl. Med.
Biol. 15, 293-297 ( 1988).
55
J. F. Hainfeld, C. J. Foley, S. C. Srivastava, L. F. Mausner, N. I. Feng,
G. E. Meinken, and Z. Steplewski, ‘Radioactive gold cluster immunoconjugates: Potential agents for cancer therapy,” Nucl. Med. Biol. 17,
287-294 (1990).
56
M. R. Zalutsky, M. A. Nosh, E. V. Colapinto, P. K. Garg, and D. D.
Bigner, “Enhanced tumor localization and in vivo stability of a monoclonal antibody radioiodinated using N-succinimidyl-3-(tri-nbutylstannyl)benzoate,” Cancer Res. 49, 5543-5549 (1989).
57
D. S. Wilbur, S. W. Hadley, M. D. Hylarides, P. G. Abrams, P. A.
Beaumier, A. C. Morgan, J. M. Reno, and A. R. Fritzberg, “Develop
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
508
ment of a stable radioiodinating reagent to label monoclonal antibodies
for
radiotherapy of cancer,” J. Nucl. Med. 30. 216-226 (1989).
58
L. A. Khawli and A. I. Kassis. “Synthesis of 125 I labeled
N-succinimidyl p-iodobenzoate for use in radiolabeling antibodies,”
Nucl. Med. Biol. 16, 727-733 (1989).
59
G. Vaidyanathan and M. R. Zalutsky, “Protein radiohalogenation observations on the design of N-succinimidyl ester acylation agents,”
Bioconjugate Chem. 1, 269-273 (1990).
60
J. F. Eary. O. W. Press, C. C. Badger, L. D. Durack. K. Y. Richter, S.
J. Addison, K. A. Krohn. D. R. Fisher, B. A. Porter, D. L. Williams,
P. J. Martin, F. R. Appelbaum, R. Levy, S. L. Brown, R. A. Miller, W.
B. Nelp, and I. D. Bernstein. “Imaging and treatment of B-cell lymphoma.”
J. Nucl. Med. 31. 1257-1268 (1990).
61
S. M. Larson, A. Raubitschek. J. C. Reynolds, R. D. Neumann, K.
Erik-Hellstrom, I Hellstrom, D. Colcher, J. Schlom, E. Glatstein, and
J. A. Carrasquillo, “Comparison
of bone marrow dosimetry and toxic
131
effect of high dose I-labeled monoclonal antibodies administered to
man.” Nucl. Med. Biol. 16, 153-158 (1989).
62
L. C. Washburn, T. T. Hwa Sun, J. E. Crook, B. L. Byrd, J. E. Carlton,
Y. W. Hung, and Z. S. Steplewski. “Y-90-labeled monoclonal antibodies for cancer therapy,” Nucl. Med. Biol. 13, 453-456 (1986).
63
S. E. Order, J. L. Klein, P. K. Leichner, J. Frinke, C. Lollo, and J.
Carlo, “Yttrium-90 antiferritin. A new therapeutic radiolabeled antibody,” Int. J. Radiat. Oncol. Biol. Phys. 12, 227-281 (1986).
64
D. J. Hnatowitch, M. Chinol, D. A. Siebecker, M. Gionet, T. Griffin, P.
W. Doherty, R. Hunter, and K. R. Kase, “Patient biodistribution of
intraperitoneally administered yttrium-90 labeled antibody,” J. Nucl.
Med. 29, 1428-1435 (1988).
65
J. A. Carrasquillo, B. Kramer, T. Fleisher, P. Perentesis, C. J. Boland,
F. Foss, M. Rotman, J. C. Reynolds, J. L. Mulshine, L. Camera, J.
Frincke, C. Lollo, R. D. Neumann, S. M. Larson, and A. Raubitschek,
“In-111 versus Y-90 T101 biodistribution in patients with hematopoietic
malignancies,” J. Nucl. Med. 32, 970 (1991) (abstract).
66
J. F. Eary, L. Durak, D. Williams, and J-L. Vanderheyden, “Considerations for imaging Re-188 and Re-186 isotopes,” Clin. Nucl. Med.
15, 911-916 (1990).
67
H. B. Breitz, P. L. Weiden, J-L Vanderheyden, J. W. Appelbaum, M.
J. Bjorn, M. F. Fer, S. B. Wolf, B. A. Ratliff, C. A. Seiler, D. C. Foisie,
D. R. Fisher, R. W. Schroff, A. R. Fritzberg, and P. G. Abrams,
“Clinical experience with rhenium-186-labeled monoclonal antibodies
for radioimmunotherapy: Results of phase I trials,” J. Nucl. Med. 33,
1099-1112 (1992).
68
S. M. Quadri and B. W. Wessels, “Radiolabeled biomolecules with
Re- 186: Potential for radioimmunotherapy,” Nucl. Med. Biol. 13, 447451 (1986).
69
H. Breitz, B. Ratliff, R. Schroff, J. L. Vanderheyden, A. Fritzberg, J.
Appelbaum, D. R. Fisher, P. Abrams, and P. Weiden, “Phase I studies
of 186Re whole MoAb and F(ab’)2 fragment for radioimmunotherapy
in solid tumors,” J. Nucl. Med. 31, 724-725 ( 1990).
70
R. A. Fawwaz, T. S. T. Wang, S. C. Srivastava, J. M. Rosen, S. Ferrone, M. A. Hardy, and P. O. Alderson, “Potential of Pd-109-labeled
antimelanoma monoclonal antibody for tumor therapy,” J. Nucl. Med.
25, 796-799 (1984).
71
A. K. DasGupta, L. F. Mausner, and S. C. Srivastava, “A new separation procedure for Cu from proton irradiated Zn,” Int. J. Appl.
Radiat. Isot. 42, 371-376 (1991).
72
D. W. McPherson, T. W. Lee, and F. F. Knapp, “A simple colorimettic method for determination of the specific activity of spallation produced copper-67 using phenylglyoxal (PG) bis-(4N-methyl)
thiosemicarbazone (TSC) derivatives,” Int. J. Appl. Radiat. Isot. 41,
689-692 (1990).
73
Chart of the Nuclides (Knoll Atomic Power Lab., General Electric Co.,
San Jose, CA, 1988), 14th ed.
74
K. L. Kolsky,199L. F. Mausner, J. F. Hainfeld. G. E. Meinken, and S. C.
Srivastava, “ Au production for use as a radiolabel of gold cluster
immunoconjugates,” J. Label. Compds. Radiopharm. 30, 211-213
(1990).
75
A. P. Callahan, D. E. Rice, and F. F.188Knapp,
“ 188Re for therapeutic
188
applications from an alumina-based W/ Re radionuclide generator,” Nucl. Compact. 1, 3-5 (1989).
76
G. J. Ehrhardt, A. R. Ketring, T. A. Turpin, M. S. Razavi, J. L.
Vanderheyden,
F. M. Su, and A. R. Fritzberg, , “A convenient
188
W/188188
Re generator for therapeutic applications using low specific
activity W,” in Technetium and Rhenium in Chemistry and Nuclear
509
L. F. Mausner and S. C. Srivastava: Radionuclides for radioimmunotherapy
Medicine edited by M. Nicolini, G. Bandoli, and U. Maggi (Raven,
New York, 1990). 3rd ed.. pp. 631-634.
R. Doering, W. Tucker, and L. Stang, “A simple device for milking
high purity Y-90 from Sr-90,” J. Nucl. Med. 4, 55-59 (1963).
78
M. Chino1 and D. Hnatowich, “Generator produced 90Y for radioimmunotherapy,” J. Nucl. Med. 29, 1465-1470 ( 1987).
79
D. J. Hnatowich, “Antibody radiolabeling: Problems and promises,”
Nucl. Med. Biol. 17, 49-55 ( 1990).
80
L.C. Washburn, T. T. H. Sun, Y.-C.C. Lee, B. L. Byrd, E. C. Holloway, J. E. Crook, J. B. Stubbs, M. G. Stabin, M. W. Brechbiel, O. A.
Gansow, and Z. Steplewski, “Comparison of five bifunctional chelate
techniques for 90Y-labeled monoclonal antibody CO17-1A,” Nucl.
Med. Biol. 18, 313-321 (1991).
81
S. V. Deshpande, S. J. DeNardo, D. L. Kukis, M. K. Moi, M. J.
McCall, G. L. DeNardo, and C. F. Meares, “Yttrium-90-labeled mon77
Medical Physics, Vol. 20. No. 2, Pt. 2, Mar/Apr 1993
509
oclonal antibody for therapy: Labeling by a new macrocyclic bifunctional chelating agent.” J. Nucl. Med. 31, 473-479 ( 1990).
O. A. Gansow, “Newer approaches to the radiolabeling of monoclonal
antibodies by use of metal chelates,” Nucl. Med. Biol. 18, 369-381
(1991).
83
C. F. Meares, M. K. Moi, H. Diril, D. L. Kukis, M. J. McCall, S. V.
Deshpande, S. J. DeNardo, D. Snook, and A. Epenetos, “Macrocyclic
chelates of radiometals for diagnosis and therapy.” Br. J. Cancer 62,
21-26 (1990).
84
M. W. Brechbiel
and O. A. Gansow, “Backbone substituted DTPA
ligands for 90Du radioimmunotherapy,” Biconjugate Chem. 2, 187-194
(1991).
85
W. Vaalburg, A. M. J. Paans, J. W. Terpstra, T. Weigman, K. Dekens,
A. Rikamp, and M. G. Woldring, “Fast recovery by dry distillation of
Br-75 induced in reusable metal selenide targets via Se-76 (p,2n) Br-75
reaction,” Int. J. Appl. Radiat. Isot. 36, 961-964 (1985).
82
MIRDformulation
Evelyn E. Watson and Michael G. Stabin
Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee 37831
Jeffry A. Siegel
Cooper Hospital, Camden, New Jersey 08103
(Received 18 March 1992; accepted for publication 15 September 1992)
The Medical Internal Radiation Dose (MIRD) Committee of the Society of Nuclear Medicine has provided guidance on methods for calculating radiation absorbed dose
estimates since 1968. The MIRD Primer 1 gives a complete
explanation of the schema which is a series of general equations adaptable for use with either simple or complex anatomical and kinetic models. By definition, the absorbed
dose is the energy absorbed from ionizing radiation per
unit mass of tissue. Because absorbed dose from internally
distributed radionuclides is never completely uniform,’ the
MIRD equations give the average, or mean, absorbed dose
to a volume of tissue.
The schema is useful for estimating absorbed dose to
volumes as small as a cluster of cells or as large as the total
body. Microdosimetric techniques that account for statistical aspects of particle track structures and energy distribution patterns in microscopic volumes can be used to express energy deposition in tissues from materials labeled
with alpha-particle or Auger-electron emitters, particularly
those incorporated within cells.
The equation for calculating the absorbed dose may be
written in various forms depending on available information. An example is shown in Eq. (1):
where D(rk ← r h ) is the mean absorbed dose in-a target
region r k from activity in a source region r h , Ah is the
cumulated activity (time integral of activity over the time
interval of interest) in the source, ∆ ι is the mean energy
emitted by a radionuclide per nuclear transition, φ i ( rk ← rh)
is the absorbed fraction (fraction of energy emitted in region rh that is absorbed in region r k ), and mk is the mass of
the target r k . The absorbed fraction divided by the mass
may be represented by Φ (rk ← r h ), the specific absorbed
fraction. The total mean absorbed dose in a target region is
calculated by summing the doses from all source regions to
the target. Equation ( 1) can be divided into two types of
parameters-physical and biological.
I. PHYSICAL PARAMETERS
A. Mean energy emitted per transition (A)
The most readily obtainable and the most accurate values required for dose calculation are probably those related
to the energy emitted from a radioactive source. Each type
of radiation emitted by a radionuclide is characterized by
its own mean energy per particle E i and its own intensity or
number of particles emitted per transition n i. The mean
511
Med. Phys. 20 (2). pt. 2, Mar/Apr 1993
energy emitted per transition ∆ i is equal to k ni E i where k
is a constant that depends on the units used for the terms
in Eq. (1). The Brookhaven National Laboratory maintains a file of decay information that can be used to determine the intensities and energies of the different emissions
associated with the transformation of any known radionuclide. In 1989, the MIRD Committee published this information on 242 radionuclides in a form that can be easily
used for dose calculation.* In addition to intensities and
energies, delta (A) values are given in both traditional
(rad g/µCi h) and SI (Gy kg/Bq s) units. Diagrammatic
decay schemes are provided along with the physical halflives, daughter products, and other related data.
B. Absorbed fraction (φ)
The absorbed fraction varies with the type and energy of
the radiation, the type of material through which the radiation passes, and the geometric configuration and the composition of the source and the target. Its value cannot be
less than 0 or greater than 1. For convenience in estimating
absorbed fractions, radiation types are sometimes classified
as penetrating and nonpenetrating. If the amount of energy
imparted to any target other than the source is so insignificant as to have little effect on the absorbed dose, the radiation is considered to be nonpenetrating. The absorbed
fraction in the source is equal to one, and absorbed fractions for all other targets are zero. The classification of
radiation as penetrating or nonpenetrating is determined
by the absorption properties of the radiation, the nature of
the model describing the source and target, and the type of
calculation. Radiations may be considered nonpenetrating
in the calculation of mean absorbed dose to a source volume but penetrating when the spatial distribution of absorbed dose is required, such as in tumor dosimetry.
Several techniques have been used to calculate absorbed
fractions, such as Monte Carlo and buildup factor
methods. 3-8 Software for determining energy deposition in
tissue include the ALGAMP code which has been used to
calculate absorbed fractions for humans at various ages
and the Electron Gamma Shower package, commonly
called EGS4, which is particularly useful for calculating
the spatial distribution of absorbed dose from electrons and
beta particles. In some instances, the reciprocity principle’
has been applied when absorbed fractions could not be
calculated to the desired level of accuracy by other techniques. Symbolically, the reciprocity relationship can be
illustrated as follows:
0094-2405/93/020511-04$01.20
© 1993 Am. Assoc. Phys. Med.
511
512
512
Watson, Stabin, and Siegel: MIRD formulation
Frequently specific absorbed fractions Φ ( rk ← r h ), or
φ ( rk ← r h)/m k, are calculated rather than absorbed fractions. By reciprocity,
Absorbed fractions and specific absorbed fractions for photons in organs of a 70-kg Reference Man have been published by the MIRD Committee. 3,4 The committee has also
provided absorbed fractions for photons in spheres, cylinders, and ellipsoids from one gram to 200 kg in mass. 5,6 In
MIRD Pamphlet No. 7,8 Berger provided information on
absorbed dose distributions around point sources that can
be used in calculating specific absorbed fractions from beta
particles and electrons. Leichner et al.9 developed a generalized, empirical point-source function for calculating absorbed doses in tumors from beta particles based on Berger’s tabulated absorbed-dose distributions. 8
C. Mean dose per unit cumulated activity (S)
The product of ∆ and Φ is a constant for a given radionuclide and a given source-target combination, a value
designated by the MIRD Committee as the S value. The
mean absorbed dose equation can thus be written as
(3)
where S(rk ← r h ) = Σ ι∆ ιΦ ι ( rk + rh ). Values Of S have been
published in MIRD Pamphlet No. 11 10 for a mathematical
model representing an adult male (Reference Man) with
most of the important organs. Absorbed fractions and specific absorbed fractions for other mathematical models can
be used to calculate S values as needed. Cristy and
Eckerman11 have developed models and calculated specific
absorbed fractions from internal photon sources for Reference Woman (also used to represent a 15-yr-old male) as
well as a 10-yr-old, a 5-yr-old, a 1-yr-old, and a newborn
child. Mathematical descriptions of organs and regions of
the body have been designed to supplement or improve
those included in the original models. Of particular interest
for monoclonal antibody dosimetry are models of the blood
vessels12,13 and the peritoneal cavity. 1 4
Absorbed fractions and S values have also been calculated for small or irregularly shaped structures in the
b o d y ? ‘ * Johnson et al. determined the radiation dose
from 1 6 6 H o , 1 8 6 Re and 1 5 3 Sm at a bone-to-marrow interface using the EGS4 code and including the contribution of
backscattered radiation to the marrow dose. 15 H u m m1 6
calculated absorbed fractions and dose rates for solid tumors with “cold-regions” surrounded by uniform distribution of radiolabeled monoclonal antibodies to illustrate the
absorbed dose-rate profile for different radionuclides. Howell et al. 17 published dose-rate profiles for 3 2P, 6 7Cu. 9 0Y ,
111
AG, 1 3 1I, 1 8 8Re, and 1 9 3 mPt in spherical “tumors” with
radii of 0.05 and 0.5 cm. Akabani et al. have published beta
absorbed fractions for a large number of radionuclides in
spheres with radii ranging from 0.1-2.0 cm (Ref. 18).
Most absorbed dose calculations are based on the assumption that the absorbed fractions and the mass of the
target remain constant during the time of irradiation. This
Medical Physics. Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
is not always the situation. Howell et al. have studied
changes in absorbed dose for rapidly growing tumors.” In
radionuclide therapy, the volumes of the tumors may
change greatly during the period over which the dose is
delivered. Folding the tumor masses into the calculation
may result in more accurate doses and a more meaningful
determination of the dose-response relationships.
Several investigators have calculated absorbed fractions
for cellular configurations.20-22 A few examples will suffice
to illustrate this. Kassis et al. determined absorbed fractions and absorbed dose rates to cells for nuclear transitions occurring inside the cell, in other cells, and in the
extracellular medium.20 Makrigiorgos et al. 21 used this
technique to calculate absorbed doses for cell clusters with
different cellular diameters and different fractions of the
cell volume that are labeled. Bardies and Myers have presented a model for cellular and cell cluster dosimetry for
use in targeted radionuclide therapy. 22 Some of these models have been proposed as evidence of the limitations of the
MIRD technique; however, the components of the calculations are the same as those in the MIRD schema. For
example, the absorbed dose may be given as a function of
distance along a defined axis, but the calculation is based
on absorbed fractions or specific absorbed fractions defined
as a function of distance along the axis.
II. BIOLOGICAL PARAMETERS
A. Cumulated activity (A)
The cumulated activity A h represents the total number
of nuclear transformations occurring during the time of
interest in the source region r h and may be expressed in
units of microcurie hours, Becquerel seconds, or an appropriate multiple of these units. A compilation of cumulated
activities for various radionuclides or radioactive compounds has not been published by the MIRD Committee
because the source regions differ for each radiolabeled material, and the source regions and their cumulated activities
often change as new research results become available.
The residence time τ of a radionuclide in a source region
is equal to the cumulated activity in the source divided by
the administered activity; that is
(4)
Although activity can sometimes be measured directly by
external measurements with a scintillation camera in either
the planar or SPECT modes, cumulated activities and residence times are not always available because of difficulties
in directly measuring the activity in organs or regions of
the body. Frequently, these values are determined indirectly through measurements that can be made, such as
total body retention, excretion, blood clearance, etc., and
the use of compartmental analysis techniques. 23 Computer
software has been developed that permits the application of
compartmental analysis to the development of models that
will yield residence times in the organs or regions of interest. One such program is the Simulation, Analysis, and
Modeling (SAAM) program.24 This software is available
without cost from the Resource Facility for Kinetic Anal-
513
513
Watson, Stabin, and Siegel: MIRD formulation
ysis, Center for Bioengineering, FL-20, University of
Washington, Seattle, WA 98195. Versions of the software
are available for use on several computers such as the
VAX, IBM-compatible personal computers, and many
others.
Although data collected in humans are always preferable, data collected in animals may sometimes be extrapolated to give estimates of the time-activity behavior of a
radionuclide in humans.2 5 No single technique for such
extrapolation has been generally accepted; however, great
care must be taken in collecting the data and in performing
the extrapolation to assure that these extrapolations are
performed as accurately as possible. 26 Data should be presented in a manner that will allow other investigators to
make use of the information and possibly recalculate if
better extrapolation techniques are determined.
The MIRD Committee has published 15 dose estimate
reports 1,27-29 for nuclear medicine radiopharmaceuticals.
Each report includes the biological models used for calculating cumulated activities needed for the dose estimate.
These models can sometimes be adapted for other situations and other radionuclides. They also can be useful in
determining how models may be developed and how data
should be collected.
III. EXTENSION OF MIRD SCHEMA TO
MONOCLONAL ANTIBODY DOSIMETRY
The MIRD schema is accepted as a useful technique for
estimating the radiation dose from radioactive material
within the human body. With respect to the dosimetry of
radiolabeled antibodies, the MIRD Committee has provided a description of the ingredients that produce an absorbed dose estimate. The basic equations are applicable to
tissues of various sizes and shapes and in different geometric relationships with each other. The committee has published data for calculating the mean absorbed dose in targets from activity that can be considered to be uniformly
distributed in source organs or in small spheres and
ellipsoids. 3-7
Absorbed fractions or specific absorbed fractions for
nonuniform activity distributions or for nonstandard geometries will need to be calculated for some situations.
Investigators have already generated absorbed fractions
and specific absorbed fractions of energy from alpha and
beta particles and electrons for some spherical tumors at
the macroscopic or millimeter level 16-18 and for nonuniform distribution within cell clusters. 20-22 Such values are
not usually required for photon radiations.
Autoradiographic studies have clearly shown nonuniform distribution of radiolabeled monoclonal antibodies in
tumors. The MIRD schema can be used to estimate absorbed doses for nonuniform distributions if the necessary
data are obtained. The limitation is in the lack of an adequate model rather than in the schema. As the volume for
which the absorbed dose is calculated becomes smaller, the
nonuniformity of dose within that volume also becomes
smaller.
From the standpoint of absorbed dose, localization of
activity in individual structures of a cell or in parts of a
Medical Physics. Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
tumor mass is analogous to localization of activity in organs of the body. The greatest obstacles to estimating absorbed doses for radiotherapy agents are the measurement
of activity distributions over time and the assessment of
geometric relationships among sources and targets within
the tissue. Calculating residence times or cumulated activities is not difficult if necessary biological data are obtained,
and computer software is available to calculate absorbed
fractions of energy if the tissue volumes of interest are
defined.
A possible technique for circumventing these problems
may be to calculate a range of doses as well as a mean
absorbed dose for a region as presented by Roberson
et al. 30 for radiolabeled microsphere therapy. This gives an
estimate of the variations in absorbed dose that exist in
regions where the activity distributions are significantly
nonuniform.
IV. SUMMARY
The MIRD schema is not restricted to calculating mean
absorbed doses in organs but can be extended to any tissue
for which distribution and retention data can be obtained
and for which a reasonably accurate mathematical description of the source and target tissues can be determined.
The development of more accurate absorbed dose estimates and the correlation of these estimates with radiation
effects will lead to a better understanding of the results
from radiotherapeutic agents such as radiolabeled monoclonal antibodies. Therefore, radiobiologists and internal
dosimetrists need to combine their efforts and work toward
the common goal of improving the treatment of malignant
diseases.
1
R. Loevinger, T. F. Budinger, and E. E. Watson, MIRD Primer for
Absorbed Dose Calculations (Society of Nuclear Medicine, New York,
NY, 1988).
2
D. A. Weber, K. F. Eckerman, L. T. Dillman, and J. C. Ryman,
MIRD: Radionuclide Data and Decay Schemes (Society of Nuclear
Medicine, New York, NY, 1989).
3
W. S. Snyder, M. R. Ford, G. G. Warner, and H. L. Fisher, Jr.,
‘Estimates of absorbed fractions for monoenergetic photon sources
uniformly distributed in various organs of a heterogeneous phantom,
MIRD Pamphlet No. 5,” J. Nucl. Med. 10, Suppl. 3 (1969).
4
W. S. Snyder, M. R. Ford, and G. G. Warner, Estimates of Specific
Absorbed Fractions for Photon Sources Uniformly Distributed in Various
Organs of a Heterogeneous Phantom, MIRD Pamphlet No. 5, Revised
(Society of Nuclear Medicine, New York, NY, 1978).
5
G. L. Brownell, W. H. Ellett, and A. R. Reddy, “Absorbed fractions
for photon dosimetry, MIRD Pamphlet No. 3,” J. Nucl. Med. 9, Suppl.
No. 1, 27-39 (1968).
6
W. H. Ellett and R. M. Humes, “Absorbed fractions for small volumes
containing photon-emitting radioactivity, MIRD Pamphlet No. 8,” J.
Nucl. Med. 12, Suppl. No. 5, 25-32 ( 1971).
7
M. J. Berger, “Energy deposition in water by photons from point isotropic sources, MIRD Pamphlet No. 2,” J. Nucl. Med. 9, Suppl. No. 1,
15-25 (1968).
8
M. J. Berger, “Distribution of absorbed dose around point sources of
electrons and beta particles in water and other media, MIRD Pamphlet
No. 7,” J. Nucl. Med. 12, Suppl. No. 5, 1-23 (1971).
9
P. K. Leichner, W. G. Hawkins, and N.-C. Yang, “A generalized,
empirical point-source function for beta-particle dosimetry,” Antib.
Immunoconjug. Radiopharm. 2, 125-144 (1989).
514
Watson, Stabin, and Siegel: MIRD formulation
10
W. S. Snyder, M. R. Ford, G. G. Warner, and S. B. Watson, "S"
Absorbed Dose Per Unit Cumulated Activity for Selected Radionuclides
and Organs, MIRD Pamphlet No. 11 (Society of Nuclear Medicine,
New York, NY, 1975).
11
M. Cristy and K. F. Eckerman, “Specific absorbed fractions of energy
at various ages from internal photon sources,” ORNL/TM-8381, Vols.
1-7 (1987).
12
G. Akabani and J. W. Poston, Sr., “Absorbed dose calculations to
blood and blood vessels for internally deposited radionuclides,” J.
Nucl. Med. 32, 830-834 (1991).
13
R. E. Faw and J. K. Shultis, “Dosimetry calculations for concentric
cylindrical source and target regions with application to blood vessels,”
Health Phys. 62, 344-350 (1992).
14
E. Watson, M. G. Stabin, J. L. Davis, and K. F. Eckerman, “A
model of the peritoneal cavity for use in internal dosimetry,” J. Nucl.
Med. 30, 2002-2011 (1989).
15
J. C. Johnson, S. M. Langhorst, S. K. Loyalka, W. A. Volkert. and A.
R. Ketring, “Calculation of radiation dose at a bone-to-marrow interface using Monte Carlo modeling techniques (EGS4),” J. Nucl. Med.
33, 623-628 (1992).
16
J. L. Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
17
R.W. Howell, D. V. Rao, and K. S. R. Sastry, “Macroscopic dosimetry for radioimmunotherapy: Nonuniform activity distributions in
solid
tumors,” Med. Phys. 16, 66-74 (1989).
18
G. Akabani, J. W. Poston, Sr., and W. E. Belch, “Estimates of beta
absorbed fractions in small tissue volumes for selected radionuchdes.”
J.
Nucl. Med. 32, 835-839 (1991).
19
R. W. Howell, V. R. Narra, and D. V. Rao, “Absorbed dose calculations for rapidly growing tumors,” J. Nucl. Med. 33, 277-281 (1992).
20
A. I. Kassis, S. J. Adelstein, C. Haydock, and K. S. R. Sastry,
“Thallium-201: An experimental and a theoretical radiobiological approach to dosimetry,” J. Nucl. Med. 24, 1164-1175 (1983).
21
G. M. Makrigiorgos, S. J. Adelstein, and A. I. Kassis, “Limitations of
conventional internal dosimetry at the cellular level,” J. Nucl. Med. 30,
1856-1864 (1989).
22
M. Bardies and M. J. Myers, “Development and validation of a simple
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
514
model for cellular and ceil cluster dosimetry with practical application
in targeted radionuclide therapy," in Fifth International Radiopharmaceutical Dosimetry Symposium, CONF-910529. edited by E. E. Watson
and A. T. Schlafke-Stelson (Oak Ridge Associated Universities, Oak
Ridge, TN, 1992), pp. 531-543.
23
M. Berman, Kinetic Models for Absorbed Dose Calculalions. MIRD
Pamphlet No. 12 (Society of Nuclear Medicine, New York, NY,
1977).
24
M. Berman and M. F. Weiss, SAAM Manual (U.S. DHEW Publication
No. (NIH) 78-108, US. Government Printing Office, Washington,
DC,
1978).
25
H. D. Roedler, “Accuracy of internal dose calculations with special
consideration of radiopharmaceutical biokinetics,” in Third International Radiopharmaceutical Dosimetry Symposium, edited by E. E.
Watson, A. T. Schlafke-Stelson, J. L. Coffey, and R. J. Cloutier (Oak
Ridge Associated Universities, Oak Ridge, TN, 1981), pp. I-20.
26
K.A. Lathrop,” Collection and presentation of animal data relating to
internally distributed radionuclides,” Third International Radiopharmaceutical Dosimetry Symposium, edited by E. E. Watson, A. T.
Schlafke-Stelson, J. L. Coffey, and R. J. Cloutier (Oak Ridge Associated
Universities, Oak Ridge, TN, 1981). pp. 198-203.
27
D. A. Weber, P. Todd Makler, Jr., E. E. Watson, J. L. Coffey, S. R.
Thomas, and J. London, “MIRD Dose Estimate Report No. 13. Radiation absorbed dose from technetium-99m-labeled bone imaging
agents,” J. Nucl. Med. 30, 1117-I 122 (1989).
28
H. L. Atkins, S. R. Thomas, U. Buddemeyer, and L. R. Chervu,
“MIRD Dose Estimate Report No. 14. Radiation absorbed dose from
technetium-99 m-labeled red blood cells,” J. Nucl. Med. 31, 378-380
(1990).
29
J.S. Robertson, M. D. Exekowitz, M. K. Dewanjee, M. G. Lotter, and
E. E. Watson, “MIRD Dose Estimate Report No. 15. Radiation absorbed dose for radioindium-labeled autologous platelets,” J. Nucl.
Med. 33, 777-780 (1992).
30
P. L. Roberson, R. K. Ten Haken, D. L. McShan, P. E. McKeever, and
W. D. Ensminger, “Threedimensional tumor dosimetry for hepatic
yttrium-90-microsphere therapy,” J. Nucl. Med. 33, 735-738 (1992).
Pharmacokinetic modeling
Sven-Erik Strand
Department of Radiation Physics, Lund University, University Hospital, S-221 85, Lund, Sweden
Pat Zanzonico
Division of Nuclear Medicine. New York Hospital-Cornell Medical Center, New York. New York
Timothy K. Johnson
Department of Radiology. University of Colorado, Denver, Colorado
(Received 18 March 1992; accepted for publication 27 November 1992)
For radiation dosimetry calculations of radiolabeled monoclonal antibodies, (MAb), pharmacokinetics are critical. Specifically, pharmacokinetic modeling is a useful component of estimation of cumulated activity in various source organs in the body. It is thus important to formulate
general methods of pharmacokinetic modeling and of pharmacokinetic data reduction, leading
to cumulated activities. In this paper different types of models are characterized as “empirical,”
“analytical,” and “compartmental” pharmacokinetic models. There remains a pressing need for
quantitative studies in man for a proper understanding of the pharmacokinetics of MAb. Pharmacokinetic modeling of radiolabeled MAb in vivo has relied on relatively limited studies in man
and complementary detailed measurements in animals. In either case, any model chosen for
analysis of such data is inevitably based on measurements of limited accuracy and precision as
well as assumptions regarding human physiology. Very few macroscopic compartmental pharmacokinetic models for MAb, have been tested over a range of conditions to determine their
predictive ability. Extracorporeal immunoadsorption represents one approach for drastically
altering the biokinetics of antibody distribution, and may serve to validate a given pharmacokinetic model. In addition to macroscopic modeling, the microscopic evaluation of the timedependent distribution of radiolabeled MAb in tissues is of utmost importance for a proper
understanding of the kinetics and radiobiologic effect. Many tumors do not exhibit homogeneous
uptake. A mathematical understanding of that distribution is thus essential for accurate tumor
dosimetry estimates. This review summarizes methodologies for pharmacokinetic modeling,
critically reviews specific pharmacokinetic models and demonstrates the capability of modeling
for predictive calculations of altered pharmacokinetics, emphasizing its use in dosimetric
calculations.
1. INTRODUCTION
Epitomizing Ehrlich’s century-old conceptualization of the
“magic bullet,” radiolabeled monoclonal antibodies
(MAb) against tumor-specific and/or associated antigens
have spurred an unprecedented worldwide effort in nuclear
medicine research. A sound quantitative understanding of
the pharmacokinetics and thus a systematic approach to
the radiation dosimetry of these target tissue-specific radiopharmaceuticals has largely remained elusive, however.
Indeed, the general difficulties inherent in generating reasonably accurate and precise cumulated activity and absorbed dose estimates for internal radionuclides are exacerbated for radiolabeled MAb because of the marked
qualitative as well as quantitative differences in their pharmacokinetics among different species, different individuals,
different antibodies, different radionuclides, different
modes of administration, and different administered
amounts.
Accordingly, radiation dosimetry of sufficient accuracy
and precision for therapeutic application of radiolabeled
MAb, as dictated by the generally marginal therapeutic
index (i.e., the tumor-to-critical normal tissue absorbed
dose ratio), must be performed on an individualized basis.
Thus the general treatment planning paradigm used, for
515
Med. Phys. 20 (2). ft. 2, Mar/Apr 1993
example, in radioiodine treatment of metastatic thyroid
cancer’ should be considered for radioimmunotherapy: a
low-activity tracer administration, kinetic studies consisting of serial measurements of tissue activities, absorbed
dose estimation and projection to the maximum “safe” and
the minimum “therapeutically effective” administered activities, and a high-activity therapy administration (with
additional kinetic studies for verification of the actual therapeutic absorbed doses). Nonetheless, practical quantitative radionuclide imaging methods including planar,
single-photon emission computed tomography (SPECT),
and positron emission tomography (PET), as well as
probe-based organ and total. body activity measurements
and ex vivo blood activity concentration measurements
have been developed and published in detail; 1-36 the reader
is referred to the pertinent contributions in this volume for
additional information.
II. PRACTICAL SIGNIFICANCE OF
PHARMACOKINETIC MODELING
Pharmacokinetic modeling is a useful component of estimation of cumulated activities (i.e., the number of nuclear transformations) in the various source regions of the
body. Although a general concept in internal radionuclide
0094-2405/93/020515-14501.20
© 1993 Am. Assoc. Phys. Med.
515
516
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
radiation dosimetry, the precise meaning of “cumulated
activity” will be illustrated using the formalism promulgated by the Medical Internal Radiation Dosimetry
(MIRD) Committee, the International Commission on
Radiation Units and Measurements (ICRU), and the International Commission on Radiological Protection
( I C R P ) . 3 8 - 5 1 The mean absorbed dose, D(r k ← r h ), to a
target region, r k, from a radionuclide in a source region, r h,
is given by the following equations:
(1)
and
(2)
where Ah is the cumulated activity (e.g., in Bq-h) in source
region rh , Ah (t) is the radioactive decay-uncorrected activity (e.g., in Bq) in source region r h at time t p o s t administration (e.g., in h), and S(rk ← r h) is the “S factor”
(e.g., in Gy/Bq-h) for target region r k and source region
r h , that is, the absorbed dose to target region r k per unit
cumulated activity in source region r h .
Since there are generally multiple source regions, r h, for
an internally distributed radionuclide, the total absorbed
dose to the target region, r k , is given by the summation of
the expression on the right side of Eq. ( 1) over all of the
source regions, r h:
(3)
The S factor, S ( rk ← r h ), is a physical quantity related to
the nuclear properties (i.e., the number, type, and energy
of nuclear radiations and related emissions accompanying
radioactive decay) of a particular radionuclide, the geometric orientation of and distance between the target region, r k , and the source region, r h , and the electron and
mass densities, elemental composition, and effective atomic
number of the target region, r k , the source region, r h , and
the intervening tissues.” For specific anthropomorphic anatomic models (e.g., “Standard Man” 42,48 ), the values of S
factors, S ( r k ← r h ), for many radionuclides and target
region-source region pairs are tabulated and published.
On the other hand, knowing the physical half-life of a
radionuclide, the cumulated activities, A h , are biological
quantities related to the pharmacokinetics of a particular
radioactive material. In view of the practically infinite
number of combinations of materials, radionuclides, physiological and pathological conditions, and amounts and
modes of administration, it is obviously impractical to usefully tabulate pharmacokinetic parameters and/or cumulated activities of radioactive materials. It is therefore essential to formulate general methods of pharmacokinetic
modeling and of pharmacokinetic data reduction leading to
cumulated activities.
III. TYPES OF PHARMACOKINETIC MODELS
In the broadest sense, a pharmacokinetic model is simply a mathematical description of the distribution of some
material over time. Although the following distinctions are
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
516
neither rigorous nor standardized, it is didactically useful
to separately consider the various types of pharmacokinetic
models and their advantages and disadvantages. In radiation dosimetry practice, at least three general types of
pharmacokinetic models can be identified: “empirical,”
“analytic,” and “compartmental.”
Whatever approach to pharmacokinetic modeling one
adopts, the insightful admonition of Dr. Robert Loevinger
should be borne very much in mind. 5 2
“It is never possible to calculate the dose to a patient;
one can only calculate the dose to a model. The model,
of course, is the totality of the assumptions necessary to
make the calculation; these assumptions define a class of
patients, and the dose applies to this class. How well a
given patient fits the model is only conjectural...For internally distributed radionuclides, the models are crude,
and the difference between the patient and model is
vast...”
A. Empirical pharmacokinetic models
In applying radiotracer methodology, serial measurements of the amount or concentration of the radiotracer in
one or more tissues are typically graphed as a function of
time post-administration. (It is implicitly assumed that tissues of interest, including the target and/or critical organs,
are, in fact, “measurable.“) The resulting time-activity
curve itself may be characterized as an “empirical” pharmacokinetic model in that it is a mathematical description
of the distribution of the radiotracer incorporating information derived only by direct measurement. If the activity
measurements are not corrected for radioactive decay, then
the area under the time-activity curve represents the timeintegral of the activity, that is, the cumulated activity [Eq.
(2)]. The area under the time-activity curve may be evaluated by planimetry or some method of numeric integration (e.g., the trapezoidal rule, Simpson’s rule, etc.). However, the accuracy of such integration is highly dependent
on judicious timing and adequate frequency of the measured data. An important advantage of empirical pharmacokinetic models is that no simplifying assumptions are
introduced regarding the analytic form of the time-activity
data or the biology of the radiotracer distribution.
While it is difficult to measure the “zero-time” activity
(in percent of administered activity) in a given tissue, one
can reasonably equate this parameter with the percent of
the total body volume of distribution of the radiotracer
(e.g., plasma volume, extracellular water volume, etc.)
contained in that tissue. It is also impossible to measure the
activity or activity concentration indefinitely. It is therefore
desirable but often impractical to include a sufficiently
“late” final measurement (e.g., after five physical halflives, after the total body activity has decreased to less than
10% of the administered activity, etc.), to sufficiently minimize this source of error. Accordingly, one must generally
assume that after the final measurement in a given tissue,
its time-activity curve simply parallels that of the total
body or there is no biological elimination (i.e., there is
elimination only by radioactive decay in situ); this latter
approach, which is used for blood and for the total body in
517
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
the kinetic analysis of the low-activity tracer administration for planning radioiodine treatment of metastatic thyroid cancer,’ may result in overestimation of cumulated
activities.
517
function parameters [i.e., (Ah)j and (λ h )j ], related to the
deviation of the measured time-activity curve from the fitted distribution function, q h (t).
Incorporating the distribution function notation into the
expression for the cumulated activity, A h , Eq. (3) can be
reformulated as follows:
B. Analytic pharmacokinetic models
In part to overcome the inability of empirical pharmacokinetic models to reasonably extrapolate beyond the generally limited time-activity data, one may fit these data to
an analytic function (sometimes referred to as a “distribution function”). Implicit in such an “analytic” pharmacokinetic model is the assumption that the time-activity curve
follows the fitted time-dependent function before the first
measurement as well as after the final measurement. Since
biological processes (such as the exchange of material
among tissues) are generally assumed to follow first-order
kinetics, time-activity curves are generally fit to a sum of
exponentials (“by eye,” by exponential "curve stripping,”
or, more commonly, by a computerized “least-squares” fitting algorithm5 3):
where q h (t) is the distribution function for source region
r h, that is, the radioactive decay-corrected activity (e.g., in
Bq) in source region r h at time t post-administration (e.g.,
in h) of the radiotracer, (Ah ) j is the activity (e.g., in Bq)
for the jth exponential component in source region r h , at
time t=0, and (λ h )j is the biological disappearance constant (e.g., in h-1) of the jth exponential component of the
time-activity curve in source region r h, that is, the fraction
of activity eliminated per unit time for the jth exponential
component of the time-activity curve for source region r h .
Time-activity data are generally plotted in semilogarithmic graphs, that is, the activity or activity concentration is plotted on a logarithmic ordinate scale versus the
time on an arithmetic abscissa scale. In this way, each
exponential component of the distribution function, q h (t),
appears as a linear segment of the time-activity curve, and
the number of exponential components corresponds to the
identifiable number of linear segments. (If the “slopes” of
the linear segments are not widely different, however, the
resolution of the time-activity curve into distinct exponential components may be problematic). If the empirical
time-activity curve is monotonically decreasing, the biological disappearance constants, (λ h)j, are negative (See Appendix I). In this case, the generally rising initial portion
(i.e., the so-called “uptake phase”) of the time-activity
curve has not been sampled and will not be accurately
represented by the resulting distribution function, q h (t). If
the empirical time-activity curve is more complex, consisting of both increasing and decreasing segments, the respective biological disappearance constants, (λ h), are positive
and negative. Note that, in addition to the experimental
error, or uncertainty, associated with each activity measurement, fitting the time-activity curve to an analytic
function introduces an error in the estimated values of the
Medical Physics, Vol. 20, No. 2, pt. 2, Mar/Apr 1993
where λ is the physical decay constant (e.g., in h - 1) of the
radionuclide in the radiotracer, that is, the fraction of activity eliminated per unit time by radioactive decay.
Substituting the expression for the distribution function,
( qh (t), in Eq. (4) into the expression for the cumulated
activity, Ã h, in Eq. (5) and evaluating the resulting definite
integral yields the following expression:
C. Compartmental pharmacokinetic models
1. General aspects
An alternative, “physiological” approach to the determination of cumulated activities is based upon compartmental analysis,4 9 , 5 4 - 5 6 wherein a biological system is
treated as an assortment of interconnected compartments
each consisting of an ensemble of identical chemical or
physical units. Each such ensemble is somehow localized in
an identifiable anatomic entity (e.g., an organ such as the
liver), an identifiable functional entity (e.g., the reticuloendothelial system), or an identifiable physical entity (e.g.,
the extracellular water space). Any such anatomically,
functionally, or physically localized ensemble constitutes a
“compartment.” Such an ensemble may not, however, actually be localized in any such identifiable entity and its
existence as a discrete compartment is then purely conceptual. Normally, compartments tend to remain constant in
terms of the size of the ensemble (i.e., the number of chemical or physical units), while undergoing continual turnover, by the net rate of input equaling the net rate of output. The existence of such a dynamic equilibrium, or
“steady state,” the identifiability of specific compartments
and the detectability of the flux of a non-perturbing tracer
through various such compartments are implicit assumptions of compartmental analysis. A compartmental model
is thus characterized by the number of compartments and
by transition probabilities, or “exchange rates,” between
compartments and may be represented mathematically by
a set of coupled ordinary differential equations:
where dF(i,t)/dt is the flux of the tracer (e.g., in Bq/h
through compartment i, that is, the net amount of tracer
per unit time traversing compartment i, F(i,t),F(j,t) i s
the amount of tracer (e.g., in Bq) in compartments i and j,
respectively, at time t post-administration (e.g., in h),
L(i,j,t),L(j,i,t) are the fractional exchange rates (e.g., in
518
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
h -l) of the amount of tracer to compartment i from compartment j and to compartment j from compartment i,
respectively, and n is the number of compartments in the
model.
The exchange rates, L(i,j,t) and L(j,i,t), are generally
constant with time (i.e., time-invariant) and the flux of the
tracer, dF(i,t)/dt, is generally a linear (i.e., first-order)
function of the compartmental tracer contents, F(i,t) a n d
F(j,t), yielding a set of coupled linear differential equations (i.e., a=b=1) and a so-called linear model.
When solved, the time-dependent amount of tracer in
compartment i, F(i,t), is represented by a sum of exponentials.
2. MAb nonlinear compartment models
In a compartmental model of systemically administered
antibody, the finite antigen concentration and the resulting
saturability of antigenic binding sites requires a non-linear
compartmental model (i.e., a set of coupled differential
equations including at least one non-linear differential
equation), since the rates of association of the antigen and
antibody and of dissociation of the antigen-antibody complex are not constant but dependent on the instantaneous
concentrations of antigen, antibody, and antibody-antigen
c o m p l e x .57,58 If “Ag,” “Ab,” and “AgAb” represent antigen, antibody, and antibody-antigen complex, respectively,
then the antigen-antibody interaction can be represented
by the following chemical reaction, characteristic of reversible bimolecular binding reactions:
w h e r e k+ 1 is the association rate constant (e.g., in h - 1
M -1), that is, the fractional amount of antibody binding to
antigen per unit time per unit concentration of antigen and
k -1 is the dissociation rate constant (e.g., in h - 1), that is,
the fractional amount of antibody-antigen complex dissociating into free antigen and antibody per unit time.
Accordingly, the gross rate of antibody binding to antigen to form the antibody-antigen complex and the gross
rate of dissociation of the antibody-antigen complex to
yield free antibody and antigen are given by Eqs. (10) and
(11), respectively. (It is important to note that Eqs. (10)
and (11) represent the gross, not the net [as is usually
presented], binding and dissociation rates, respectively and
presented to demonstrate the mathematical relationship
between conventional antigen-antibody binding parameters
and compartmental model exchange rates.):
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
518
where [Ab] is the concentration (e.g., in M) of free antibody, [Ag] is the concentration (e.g., in M) of free antigen,
and [AbAg] is the concentration (e.g., in M) of antibodyantigen complex.
Equations (10) and (11) can be re-arranged to yield
Eqs. (12) and (13), respectively, giving the fractional rates
of antibody binding to antigen and of dissociation of the
antibody-antigen complex:
If one now identifies a free antibody compartment and a
bound antibody (i.e., an antibody-antigen complex) compartment, then the free antibody-to-bound antibody and
the bound antibody-to-free antibody exchange rates are
given, by definition, by Eqs. (12) and (13), respectively.
Because the free antigen concentration is not constant, the
free antibody-to-bound antibody exchange rate is not constant [Eq. (12)] and a nonlinearity is thereby introduced.
Nonetheless, Eq. (11) can be reformulated entirely in
terms of evaluable quantities to yield a time-varying expression for the gross free antibody-to-bound antibody exchange rate:
where [Ag] 0 is the total antigen concentration (e.g., in M)
in the antigen-positive tissue, F[AbAg,t] is the amount of
antibody (e.g., in mole) in the bound antibody compartment, and V d is the volume of distribution (e.g., in l) of the
antibody in the antigen-positive tissue. (This may be approximated by the total volume or, preferably, the extracellular water volume of the antigen-positive tissue.)
Note that if the amount of administered antibody is
sufficiently small, the total concentration of antigen, [Ag] 0,
will greatly exceed the concentration of antibody-antigen
complex, [AbAg] = F(AbAg,t)/V d. It is mathematically obvious that the gross exchange rate of antibody binding to
antigen is thus essentially constant and the overall compartmental model is thereby linearized.
3. Compartment model solution
To “solve” a compartmental model, that is, to derive a
compartmental model for which discrete values of the calculated compartmental contents, F(i,t), agree with the
corresponding experimental data, within the respective uncertainty of each datum, the number of compartments and
the values of the exchange rates, L(i,j,t), must be determined. There is actually no unique solution for a given set
of experimental data since any compartmental model can
be enlarged beyond the “resolution” possible from the data
519
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
by the introduction of additional compartments (i.e., degrees of freedom). In practice, the ambiguity, or “nonuniqueness,” of compartmental model solutions is highly
problematic because of the generally limited experimental
data available in terms of both number of compartments
sampled and the number and timing of data for each compartment. One generally adopts the compartmental model
having the minimum number of compartments and consistent with the known relevant “biology,” subject to the following criteria: the “sum of squares” deviation between the
calculated compartmental contents, F(i,t), and the corresponding experimental data should be minimized; the calculated compartmental contents, F(i,t), should be randomly,
not systematically,
dispersed about the
corresponding experimental data; and the standard error of
the parameter estimates should be reasonably small. 55,56 It
is important to recognize, however, that the existence of
compartmental model solution satisfying these criteria
does not in itself constitute a “validation,” or proof, of a
model. While difficult to define rigorously, validation of a
compartmental model is related to its ability to qualitatively and quantitatively predict the biodistribution of a
tracer in the system being modeled (i.e., yield calculated
compartmental contents equal to the corresponding experimental data with the respective uncertainty of each datum) in response to a quantifiable perturbation of the system. An elegant example of such a quantifiable
perturbation is extracorporeal immunoadsorption; its use
in the validation of compartmental models of MAb is discussed below.
The mathematical formalism for solving compartmental
models, whether analytic or numeric (i.e., iterative), is
formidable and, even for relatively simple models, outside
the scope of this chapter; the reader is referred to Ref.
54-56. CONSAAM , an interactive, or “conversational,” version of Berman’s SAAM (simulation, analysis, and modeling) program is an extremely powerful, widely used, and
fully supported compartmental modeling program. 5 7
The compartmental modeling-based calculation of cumulated activities can be performed by any number of
methods. Solving the series of differential equations that
define the model yield the model’s parameters (i.e., the
amplitude and decay constant for each exponential term).
Substitution of these parameters back into the defining differential equations, and integration from t=O to infinity,
yield the cumulative activity specific to each source organ.
Zanzonico et al.,58,59 have adapted the CONSAAM program
to calculate the cumulated activity in source region r h , Ah ,
by introducing "virtual" compartments. For internal radionuclide dosimetry for MAb, Johnson has published a
computer program, MABDOS .60
IV. PHYSIOLOGICAL CHARACTERISTICS OF MAb
Antibody molecules are complex molecular structures,
grouped into five distinct classes, IgG, IgA, IgM, IgE, and
IgD. An IgG molecule has two long and two short amino
acid chains called heavy and light chains, respectively. The
molecular weight of MAb lies between 150000 and
900000 kDa for the intact antibody and between 50000
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
519
and 100000 kDa for the various fragments. The size is
approximately 5-20 nm for intact antibody and l-3 nm for
fragments. 61 To alter the biokinetics of the antibodies, the
antibody molecule can be fragmented into Fab or F(ab’) 2
fragments.
Many experimental and clinical reports have demonstrated low neoplastic-to-normal tissue activity uptake ratios. This may be due to the formation of antibody-antigen
complexes, antibody metabolism in the reticuloendothelial
system (RES), variability of antigen expression and limited access of antibodies to the tumor tissue. 62-66 Moreover
complexes formed from the injected antibodies and host
antibodies or circulating antigen will accumulate in the
RES and the kidneys, although some reduction in circulating antigen can be obtained by plasmapheresis. 6 7
Many methods have been suggested to accelerate the
clearance of residual circulating antibodies from the blood,
including administration of second antibodies that will
form complexes and be cleared by the RES. 68 A second
approach is a two-stage method in which radiolabeled avidin is administered following the injection of a biotinylated
administration of avidin-antibody
a n t i b o d y6 9 o r
conjugates. 7 0 - 7 2
V. TRANSPORT OF MACROMOLECULES INTO
TISSUE
The transport of antibody molecules into a tissue is governed by perfusion, microvascular permeability, interstitial
transport, cell membrane permeability, concentration gradients, antigen concentration and antibody-antigen binding affinity. A summary of these factors and their implementation in pharmacokinetic modeling is given by
Zanzonico et al.58 and Eger et al. 7 3
The Mab are transported via the blood stream or the
lymph to tissues where they can cross the capillary endothelium to reach the interstitial fluid and thus to bind to
cell-surface antigens. Capillary filtration depends not only
upon the hydrostatic and colloid osmotic pressure, but on
the endothelial wall porosity as well. The difference in capillary protein permeability approximately parallels the difference in filtration coefficient. The results from Ingvar
et a1.74-76 confirm that so called “nonspecific binding” in
organs is, to some extent, the result of capillary protein
permeability and not to any active binding mechanism.
This step is probably the most important factor in explaining why monoclonal antibodies do not achieve the high
uptake ratios projected from in vitro experiments,
Because of the size of the MAb and closed basement
membrane of capillary endothelium in most normal tissues,
penetration from the blood is very slow. The antibodies,
however, have good access to liver (Kupffer cells), spleen
and bone marrow because of fenestration of the basement
membrane. The mean penetration time into extravascular
space occurs with a half-life of the order of 10-50 h in
normal tissue, whereas in solid tumors it is of the order of
10-20 h. The permeability, coupled with the possible expression of antigens on normal tissue, may limit tumor-tonormal tissue concentration ratios in vivo. However, Jain 77
noted that the neoplastic endothelium is much less struc-
520
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
tured and has a higher probability of being more permeable
to macromolecules than normal tissue endothelia.
In the study of Covell et al. the transcapillary movement of antibodies was greatest in the lung, liver and
spleen with the values 0.53, 0.35 and 0.20 ml min -1 g - 1,
respectively. For other organs, the values are: kidney, 0.09,
gut, 0.006, and carcass (skin, bone and muscle), 0.0003
m l m i n- 1 g - 1. A comparison was also made with other
d a t a79 in which the transport of Dextrans with different
molecular weights (equivalent Stoke’s radii for whole IgG
and fragments) had been measured: Dextran (110000),
0.0023 ml/min and IgG, 0.0036 ml/min; Dextran
(20000)) 0.0061 ml/min and F(ab’) 2, 0.0041 ml/min; and
Dextran (10000), 0.029 ml/min and Fab’, 0.050 ml/min.
The red bone marrow is characterized by large pores
(<100nm) and allows free flow of plasma through the
marrow parenchyma and rapid (i.e., within minutes after
i.v. injection) equilibration of large molecules. It was
found that there is rapid, high uptake of labeled antibodies
in the bone marrow. 80-82
These considerations were incorporated into a wholebody compartmental model of systemically administered
radioiodinated MAb, where Zanzonico et al. 58 postulated a
“rapidly exchanging tissue” (most visceral tissue) with an
exchange rate constant from the vascular space to the extravascular space of the order of 0.07 h - 1. For a “slowly
exchanging tissue” (most nonvisceral tissue), a rate constant of 0.02 h-1 was assumed. Plasma and reticuloendothelial tissue (bone marrow, lymph nodes, and spleen) were
combined into one compartment due to the rapid equilibration of plasma-borne antibodies with these tissues; for
clarification, the reader is referred to the definition of a
“compartment” presented above.
VI. TUMOR MAb UPTAKE
Human tumors and cultured human cells express antigenic heterogeneity, perhaps related to cell size, cell function, stage of cell cycle, invasiveness, etc. This will result in
a very uneven antibody distribution. 8 3
Ingvar et al.8 4 showed that in 58 metastases from 27
patients with malignant melanoma, evaluated by immunohistochemistry and three different MAb’s, all of the metastases were positive for at least one of the three antibodies. In 15 patients where more than one metastases was
removed, four patients showed both positive and negative
staining for two of the antibodies, in different metastases.
In autoradiographic studies large variations in the activity
distribution within tumors has been observed. 85-89
In a number of studies, it has been shown that there
exists an inverse relationship between the specific tumor
antibody uptake and tumor mass. 90-96 Data from the Lund
g r o u p9 6 for different labeling methods show such an inverse relationship for specific antibodies, whereas for unspecific antibodies, uptake is unrelated to the tumor size.
These results are in accordance with Cheung et al. 92 I n
contrast, however, Williams et al. 93 showed such a relationship for unspecific antibodies.
An explanation for these observations may be related to
tumor surface area,91 geometry of tumor blood flow, 93 o r
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
520
surface vascularization of tumor.94 Although all of these
data have been obtained in animals, there is evidence for
the same phenomenon occurring in man.
VII. MICROSCOPIC PHARMACOKINETIC MODELS
The principal factor affecting a favorable diffusion of
antibodies into tumors is the concentration gradient. 9 7
Theoretical studies of MAb penetration into tumors have
been undertaken by Weinstein et al. 97-99 They have developed a mathematical model incorporating capillary transport, tumor interstitial diffusion and antigen-antibody interaction. The time varying plasma concentration of MAb
is also modeled. The results have been evaluated as total
and free MAb distribution profiles, average total MAb concentration, and an index of nonuniformity of MAb distribution. They have found a “binding-site barrier” causing a
heterogeneous MAb distribution within the tumor nodule
because of retarding of the free MAb entering the nodule.
They also observed that a high affinity gives a high MAb
concentration close to the capillaries but with no increase
in the average concentration. Also, decreasing the
antibody-antigen binding affinity will result in a small decrease in average concentration, but will improve the percolation for a given MAb concentration. In addition by
increasing the MAb concentration in plasma the “bindingsite barrier” could by overcome at the expense of lower
uptake ratios between tumor and normal tissues. As
pointed out by the authors this is strictly a theoretical
model with no experimental verification. However, it suggests possible investigations on the micropharmacological
level are necessary for a better understanding of MAb behavior and therapeutic results. Combined with dosimetric
calculations, such a mathematical model may lead to absorbed dose profiles within tumors.
VIII. MACROSCOPIC PHARMACOKINETIC MODELS
A. Human models
As noted, a whole-body compartmental model for
systemically administered radioiodinated antibody has
been developed by Zanzonico et a1.58 based on theoretical
physiological considerations and literature data (Fig. 1). It
comprises a MAb-nonspecific part with “rapid” and
“slowly” exchangeable tissue compartments, and a
“humped” compartment of plasma and RES with a liver
compartment responsible for the rapid uptake of damaged
antibodies. The model also includes a MAb-specific binding part with nonlinear exchange rates dependent on the
Ag concentration. Thus compartments for tumor and normal tissue with free and bound Ab are included. Tumor is
represented as a rapidly exchanging tissue. Additionally a
compartment with lumped plasma and RES to model circulating antigen-antibody complexes is included. Finally
catabolism and deiodination were treated in a coupled linear compartment model for iodine kinetics. With this
model (see Fig. 1) the influence of administered amount of
antibody and size of tumor on the distribution of Ab-Ag
complexes in plasma, normal tissue and tumor were investigated. The theoretical model was then simplified (exclud-
521
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
FIG. 1. (a) A proposed whole-body compartmental model for systemically administered radioiodinated “anti-tumor” antibody 58 (b) The radioactive decay-corrected percent administered activity of radioiodinated
"anti-tumor” antibody at “equilibrium” (i.e., 100 h post-administration)
as antigen-antibody complex per gram of antigen-positive tissue as a
function of the amount58 of administered antibody for “Standard Man”
bearing a 100-g tumor, calculated using the compartmental model in
(a) and the hypothetical [but realistic for anticarcinoembryonic antigen
(CEA)] IgG parameters tabulated below.
Medical Physics, Vol. 20. No. 2, Pt. 2, Mar/Apr 1993
521
ing antigen-positive tissue and “rapidly exchanging tissue”) and used in colorectal cancer patient studies with
131
I-antiCEA MAb. The measured and the model-derived
percent administered activities in blood, liver, thyroid, and
urine were in reasonable agreement (typically within
10%), For a 2GBq administered activity dose, the modelderived absorbed doses to bone marrow, liver, thyroid, and
total body were 1.7, 2.0, 2.2, and 0.58 Gy, respectively. It
is noteworthy that the compartmental model-derived and
analytically (i.e., exponential curve fitting) derived cumulated activities and resulting absorbed doses were nearly
identical, demonstrating that, in general, any pharmacokinetic modeling approach can reliably be used for calculation of cumulated activities.
In another study linear and nonlinear parameters were
tested in different models for optimal fitting to observed
patient data (i.e., time-dependent amounts of intravascular
free intact antibody, iodine, and immunocomplex) of in123
100
jected 1-Lym-1 MAb. The final nonlinear model has
some resemblance to the Zanzonico model, although the
former tries to include more details and consequently has a
larger number of compartments. An important observation
was that published data for human immunoglobulin kinetics was not applicable, because of the foreign nature of
murine-MAb in man, causing an increased accumulation
in the liver. The nonlinear model could be treated as linear
when the amount of MAb was small compared to the number of receptors. The model was then used for calculating
blood time-activity curves for different plasma concentrations of MAb. The time-activity curves fit well with observed clinical data.
A nonlinear compartment model was developed for
111
In-9.2.27 MAb in patients by Eger et al. 101 M e a s u r e ments were performed in blood and urine and were supplemented with scintillation camera images over spleen
and liver. A minimum number of compartments was used:
one for labeled antibody containing saturable and unsaturable binding together with a plasma component and one
for labeled low-molecular weight components from antibody fragmentation. After fitting the experimental data to
the model, the rate constants were derived and the kinetics
at different MAb concentrations calculated.
In the three human studies above, kinetic measurements
of blood/plasma and urine activity with several scintillation camera measurements of, for example, liver and/or
spleen activity were successfully used to solve compartmental models, and, in the case of Zanzonico et al., 58 t o
perform dosimetric calculations. These studies demonstrate not only the practicality of compartmental
modeling-based radiation dosimetry, but, more importantly, the predictive capability of compartmental models
in potentially optimizing radioimmunotherapy through
simulations of systemic variation of, for example, the
amount of administered antibody (see Fig. 1.).
Modeling of the pharmacokinetics in man of 111 In antiCEA MAb has also been reported by Rescigno et al. 102 In
addition to external measurements they analyzed blood
and urine samples for multiple radiolabeled forms. The
SAAM derived compartment model revealed that immuno-
522
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
522
complexes were formed in the blood and that the rate of
uptake in the liver depends on the blood antibody concentration.
absorbed dose calculations, including therapeutic index,
and for prediction after hypothetical modifications of the
pharmacokinetics.
B. Animal models
IX. COMPARTMENTAL MODELING OF
EXTRACORPOREAL IMMUNO-ADSORPTION
(ECIA)
A pharmacological linear compartment model for IgG
and its fragments has been developed by Cove11 et al. 77 The
model was used to investigate the kinetics of MAb in a
system with no known antigen binding sites. The model
was fitted to experimental data from 131 I-labeled MAb. It
was a theoretical model with almost all parameters taken
from the literature. It included MAb extraction from
plasma with known plasma flow and plasma MAb concentration, with each organ having one interstitial and one
cell-associated compartment. The model (derived) and the
experimental data agreed well. Results showed that largest
levels of antibody cycling through the interstitial space
were in organs with the highest plasma flow and the largest
permeability-surface area product. Organs with the highest
capillary permeability (e.g., liver, spleen, kidney) had the
most rapid distribution of MAb into nonplasma spaces
whereas organs with lower capillary permeability (e.g., gut
and carcass) had a slower distribution.
The Lund group has evaluated rate constants for several
organs in a nude rat model. 103 The model was a linear
multicompartment model with exchange of MAb between
blood and different tissues including tumor. Rate constants
were derived by fitting the model to experimental data.
Activity was injected as a bolus into blood and distributed
to all organs. The model assumes back flow of activity from
the organs to the blood. The organs used in the model were
lymph nodes, lung, liver, spleen, bone marrow, kidney,
heart, tumors (subcutaneous and intramuscular), muscle,
remainder (tissues not dissected), and excretion (injected
activity minus whole body content measured by scintillation camera). There is good agreement between the curves
calculated in the model and the measured data. This rigorous model was used for analysis of image contrast, for
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
When examining the rationale for radioimmunotherapy,
Bigler et al.1 0 4 considered metastatic spread via the hematological system, with isolated metastatic tumor cells in
bone marrow (the dose-limiting organ). They evaluated a
“new” strategy based on calculation from a twocompartment nonlinear model for the plasma plus marrow
extracellular space and the MAb-Ag tumor cell binding
with a nearly instant equilibration of circulating MAb between plasma and marrow extracellular space and rapid
tumor cell binding of MAb. To theoretically simulate the
effect of ECIA on the distribution of MAb and the resulting tumor and marrow radiation dosimetry, an instant removal of 90% of the unbound MAb at 0.5 h postadministration was postulated; using Berman’s S A A M
program, such an instantaneous change in the contents of
a compartment can be effected mathematically using the
“time-interrupt” function (i.e., without altering any parameters of the model). As demonstrated in Table I, the
model demonstrated that much lower bone marrow doses
and greatly increased therapeutic indices were achieved
with ECIA. They projected using this strategy in combination with conventional localized cancer therapy, such as
surgery, for elimination of bulk tumor.
The use of extracorporeal immunoadsorption, was suggested by Strand et al. 105 for reducing the blood activity in
radioimmunodiagnosis and radioimmunotherapy. This
would result in the decrease of background and whole
body absorbed dose, and enhance contrast and therapeutic
ratios. ECIA is a well-established method in autoimmune
diseases, wherein circulating antibodies are removed from
the blood.106-108 Norrgren et al.103 used a linear multicompartment model to calculate contrast enhancement and ab-
523
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
523
FIG. 2. Linear multicompartment model with exchange between blood and different tissues. The calculated time-activity curves in the different tissues
after simulated single ECIA at 50 h p.i. are given. Note the rapid activity build up in the blood after ECIA (confirmed later experimentally in vivo).
sorbed dose reduction to critical organs after ECIA. ECIA
was assumed to start at a certain time after the injection of
labeled antibodies, and to instantaneously remove circulating antibodies from the blood. New time-activity curves
were then calculated, using the previously derived rate constants (Fig. 2). After a single ECIA, there was a slow
increase of blood activity until a steady state was reached.
This accurately simulates the in vivo situation where extravascular antibodies are not removed by the ECIA and
the antibodies can diffuse back from the tissues to the
blood. It can be seen that the ECIA results in an increased
outflow of activity from all organs. For the lung, liver,
kidney and heart the decrease was considerable, while for
the tumors, muscle and lymph nodes it was less pronounced. Absorbed dose calculations were performed and
therapeutic indices evaluated. It was then shown that the
tumor/whole body and tumor/bone marrow absorbed dose
ratios differed most for short-lived radionuclides where the
initial uptake in bone marrow is the critical factor.
X. IN VIVO VALIDATION OF COMPARTMENT
MODELLING OF ECIA
Pharmacokinetic modeling of ECIA has been validated
in a rat model using 125 I-labeled anti-OV albumin MAb.109
After the injection, the circulating antibody was adsorbed
on an affinity column. About 90%-95% of the antibodies
in the plasma were eliminated by the extracorporeal treatment. The activity is then redistributed, with the activity in
the organs equilibrating with the plasma activity, resulting
Medical Physics. Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
in an increase in the plasma activity 24 h after the ECIA as
compared to directly after the treatment. The whole-body
activity was reduced by 40%-50%. These experimental
results in vivo are thus consistent with the previous theoretical prediction of the MAb pharmacokinetics after
ECIA. Experimental studies with tumor-bearing nude rats
show similar results 110 as predicted by the model.
Xl. COMPARTMENT MODELING OF ECIA IN
HUMANS
ECIA to remove excess antibodies in the blood, as postulated by Bigler et al. and Strand et a1., 104,105 has been
performed by the Denver group. Patients with carcinomas
in the lung and breast were injected with 1 1 1 In-labeled
K C - 4 G 3 M A b .111-113 In nine patients at different times
post injection, immunoadsorption was performed with a
goat anti-mouse antibody treated column. 112 About 80% of
the circulating MAb could be removed,113 somewhat lower
than the theoretical and experimental predictions of the
Lund group.1 0 3 Also a 20%-40% whole-body absorbed
dose reduction was calculated by Johnson et al. 111 Importantly there was no alteration in the tumor kinetics. Thus
this procedure might enhance the therapeutic index as predicted by Norrgren et al. 1 0 3
Based on their patient studies, the Denver group has
developed a linear two compartment pharmacokinetic
model for ECIA and evaluated the effect of onset and duration of treatment.114 Numeric integration of the differential equations was performed, and patient data from
524
Strand, Zanzonico, and Johnson: Pharmacokinetic modelling
plasma and adsorption column were fit to the model to
obtain the unknown model parameters. The model was
then used to simulate plasma and ECIA-column data. Validation of the model was performed by adding noise to
simulated time-activity curves and compared to patient
data for goodness of fit. Statistical analysis indicated that
the model was reliable. Their model predicted the observed
redistribution of activity after ECIA. No data for tumor
was evaluated.
These results illustrate the usefulness of pharmacokinetic modeling for predictive calculations and for further
use in dosimetric calculations.
524
activity measurements of blood and/or plasma, solid tumors, one or more major organs, and the total body can be
performed in patients. Together with the in vitro measurement of the antigen-antibody binding parameters (which
should be part of the preclinical evaluation of all MAb
undergoing clinical testing), the necessary input data for
solution of a compartmental model should be available.
Compartmental modeling software and the necessary computer hardware are now almost universally available in
academic medical centers. Thus, as discussed above, compartmental analysis-based pharmacokinetic modeling and
cumulated activity distribution are a practical reality.
XII. SUMMARY
In general, any pharmacokinetic modeling approach
can reliably be used for reduction of kinetic data to cumulated activities. However, among the many potential advantages of compartmental analysis-based pharmacokinetic modeling and cumulated activity calculation are the
following. Available biological data (e.g., independently
determined antibody-antigen binding parameters in the
case of radiolabeled MAb) may be incorporated into a
compartmental model, constraining the model (i.e., minimizing the degrees of freedom), and thereby improving the
overall “goodness of fit” compared to curve fitting. “Conservation of mass” is implicitly incorporated into a compartmental model, also constraining the model, and
thereby likewise improving the overall “goodness of fit.”
Otherwise indeterminable cumulated activities in nonsampled microscopic source regions (e.g., extracellular
space, cell surface, cytoplasm, and nucleoplasm) can be
deduced. It is now clear that the activity, cumulated activity, and absorbed dose distributions of systemically administered radiolabeled MAb in tissue, particularly antigenpositive tissue such as tumor, is microscopically as well as
macroscopically nonuniform.116-122 And, perhaps most importantly, parameters of validated compartment models
can be systematically varied to elucidate the magnitude of
the effect of such variations on the pharmacokinetics of the
tracer and to determine optimum model parameter values
(e.g., to maximize the tumor-to-normal tissue activity concentration ratios in the case of radioimmunotherapy) 5 8’ 115
and optimum timing and frequency of data acquisition.
Simulated “parameter variation” studies can thus assist in
prioritizing research efforts (by identifying which model
parameters most dramatically affect the radiotracer tissue
distribution) and predicting the effects of various pathologies and other conditions on the outcome of future studies.
In practice (especially clinical practice), however, compartmental analysis-based pharmacokinetic modeling and
cumulated activity calculation is problematic. Besides being computer- and effort-intensive, a compartmental model
must be formulated and validated. In addition, for compartmental models as large and complex as those for systemically administered radiolabeled MAb 58,100 and for the
generally sparse kinetic data available in clinical studies,
the uncertainty of the model parameters and therefore of
any model-derived quantities (e.g., cumulated activities)
may be prohibitively large. Nonetheless, absolute timeMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
XIII. CONCLUSION
In concert with continuing efforts to find more tumorspecific MAb, more reliable and predictive modeling techniques and specific models of both microscopic and macroscopic pharmacokinetics must be pursued. Some of the
research areas to be addressed are more accurate and precise data on macroscopic and microscopic activity distributions measured in vivo, absolute quantitation of kinetic
data in clinical trials, and for the purpose of compartmental models, kinetic measurements under quantifiably perturbated conditions in vivo.
ACKNOWLEDGMENTS
This study has been supported by grants from John and
Augusta Perssons Foundation for Medical Research,
Lund, Swedish National Cancer Society, Grant No. 2353B91-05XAB, Swedish National Board for Technical Development, Grant No. 90-01878P, Mrs. Berta Kamprad’s
Foundation, Lund, Sweden, Nilssons’ Foundation, Helsingborg, Sweden and U.S. National Cancer Institute, Contract N01-CM37565.
APPENDIX I
In the completely general development of the analytic
theory of linear compartmental systems, the solution to a
system of linear differential equations with constant coefficients is exponential of the form q=ue λ t, u being the constant vector. q=ue λ t is a solution if A is an eigenvalue of f
and u is the corresponding eigenvector (i.e., fu= λ u). Convention has deemed that the appearance of substance in a
compartment is assigned to be positive, the disappearance
of substance to be negative. Thus we see that the eigenvalue
λ 1 for a simple two compartment system, with material
leaving compartment 1 and entering compartment 2, to be
equal to -ƒ2 1. - ƒ21 is the rate at which substance leaves
compartment 1 and enters compartment 2. The general
solution for this model is given by q=ue λ t where λ is negative and equal to -ƒ 2 1. 1 2 3
525
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
1
P. B. Zanzonico, C. Edwards, F. Sgouros. A. Strauss, R. E. Bigler, J. R.
Hurley, and D. V. Becker, “Practical dosimetry: Quantitative imaging
in radionuclide therapy, ” in Dosimetry of Administered Radionuclides,
edited by S. J. Adelstein, A. I. Kassis. and R. W. Burt (Society of
Nuclear Medicine-American College of Nuclear Physicians Joint
Symposium, Frontiers in Nuclear Medicine Series, Washington, DC,
Department of Energy, September 21-22. 1989), pp. 275-294.
2
J. R. Watts, R. E. Johnson, and A. Brill. “Methods of approach to
problems of absolute quantitation of radioactivity distributions in humans,”
J. Nucl. Med. 11, 374 (Abstract) (1970).
3
J. A. Sorenson, “Quantitation of radioactive content in vivo using combined emission-transmission,” J. Nucl. Med. 11, 401 (1970) (Abstract).
4
L. P. Clarke, J. S. Laughlin, and K. Mayer, “Quantitative organ-uptake
measurements,” Radiology 102, 375-382 (1972).
5
S. L. Graham and R. Neil, “In vivo quantitation using the Anger
camera,” Radiology 112, 441-442 (1974).
6
J. A. Sorenson, “Quantitative measurement of radioactivity in vivo by
whole-body counting,” in Instrumentation in Nuclear Medicine, edited
by G. J. Hine and J. A. Sorenson (Academic, New York, 1974), Vol.
2, pp. 31 1-348.
7
T. F. Budinger, “Quantitative nuclear medicine imaging: Applications
of computers to the gamma camera and whole-body scanning,” in Recent Advances in Nuclear Medicine, Progress in Atomic Medicine, edited
by J. H. Lawrence (Grune and Stratton, New York, 1974), Vol. 4, pp.
41-130.
8
S. R. Thomas, H. R. Maxon, J. G. Kereiakes, and E. L. Saenger,
“Quantitative external counting techniques enabling improved diagnostic and therapeutic decisions in patients with well-differentiated thyroid
cancer,” Radiology 122, 731-737 (1977).
9
A. Ferrant and F. Cauwe, “Quantitative organ-uptake measurement
with a gamma camera,” Eur. J. Nucl. Med. 4, 223-229 (1979).
10
J. S. Fleming, “A technique for the absolute measurement of activity
using a gamma camera and computer,” Phys. Med. Biol. 24, 176-180
(1979).
11
S.R Thomas, H. R. Maxon, and J. G. Kereiakes, “In vivo quantitation
of lesion radioactivity using external counting methods,” Med. Phys. 3,
253-255 (1976).
12
M. J. Myers, J. P. Lavender, J. B. de Oliveira, and A. Maseri, “A
simplified method of quantitating organ uptake using a gamma camera,” Br. J. Radiol. 54, 1062-1067 (1981).
13
D. J. Macey and R. Marshall, “Absolute quantitation of radiotracer
uptake in lungs using a gamma camera,” J. Nucl. Med. 23, 731-735
(1981).
14
S. R. Thomas, M. J. Gelfan, G. S. Bums, R. C. Purdom, J. G. Kereiakes, and H. R. Maxon, “Radiation absorbed-dose estimates for the
liver, spleen, and metaphyseal growth complexes in children undergoing gallium-67 citrate scanning,” Radiology 146, 817-820 (1983).
15
M. D. Hammond, P. J. Moldofsky, M. R. Beardsley, and C. B. Mulhem, Jr., “External imaging techniques for quantitation of distribution
of I-131 F(ab’)2 fragments of monoclonal antibody in humans,” Med.
Phys. 11, 778-783 (1984).
16
R. K. Wu and J. A. Siegel, “Absolute quantitation of radioactivity
using the buildup factor,” Med. Phys. 11, 189-192 (1984).
17
L. W. Grossman, M. Fernandes-Ulloa, S. J. Lukes. and J. Mantil,
“Gallium-67 lung uptake: Conjugate-view counting,” Radiology 157,
789-793 (1985).
18
K. A. Lathrop, R. D. Bartlett, C. T. Chen, J. S. Chou, P. F. Faulhaber,
P. V. Harper, and V. J. Stark, “Quantitative clinical uptake measurements using conjugate counting,” in Proceedings of the Fourth International Symposium on Radiopharmaceutical Dosimetry, edited by A. T.
Shlafke-Stelson and E. Watson [U.S. Department of Energy,
DE86010102 (CONF-851113), Oak Ridge, TN, 1985], pp. 135-147.
19
P. Doherty, R. Schwinger, M. King, and M. Gionet, “Distribution and
dosimetry of indium-111 labeled F(ab’)2 fragments in humans,” in
(Eds), Proceedings of the Fourth International Symposium on Radiopharmaceutical Dosimetry, edited by A. T. Shlafka-Stelson and E. Watson [U.S. Department of Energy, DE86010102 (CONF-851113), Oak
Ridge, TN, 1985], pp. 464-476.
20
R. J. Jaszczak, K. L. Greer, and R. E. Coleman, “SPECT quantification of regional radionuclide distributions,” in Proceedings of the
Fourth International Symposium on Radiopharmaceutical Dosimetry,
edited by A. T. Shlafke-Stelson and E. Watson [U.S. Department of
Energy, DE86010102 (CONF-851113), Oak Ridge, TN, 1985],
pp. 82-96.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
21
525
E. J. Hoffman, “Quantitation of radiopharmaceutical distributions for
use in dose estimates with positron emission tomography,” in Proceedings of the Fourth International Symposium on Radiopharmaceutical
Dosimetry, edited by A. T. Shlafke-Stelson and E. Watson [U.S. Department of Energy, DE86010102 (CONF-851113), Oak Ridge, TN,
1985], pp. 97-104.
22
T. E. Budinger, S. E. Derenzo, W. L. Greenberg, G. T. Gullberg, and
R. H. Huesman, “Quantitative potentials of dynamic emission computed tomography,” J. Nucl. Med. 19, 309-315 (1978).
23
R. J. Jaszczak, R. E. Coleman, and F. R. Whitehead. “Physical factors
affecting quantitative measurements using camera-based single photon
emission computed tomography (SPECT),” IEEE Trans. Nucl. Sci.
NS-28. 69-80 (1981).
24
R. J. Jaszczak, K. L. Greer, C. E. Floyd, C. C. Harris, and R. E.
Coleman, “Improved SPECT quantitation using compensation for
scattered photons,” J. Nucl. Med. 25, 893-900 (1984).
25
D. Osbom, R. I. Jaszczak. K. Greer, M. Lischko, and R. E. Coleman,
“SPECT quantification of technetium-99m microspheres within the canine lung,” J. Comput. Assist. Tomogr. 9, 73-77 ( 1985).
26
D. Osbom, R. J. Jaszczak, R. E. Coleman, K. Greer, and M. Lischko,
“In vivo regional quantitation of intrathoracic Tc-99 m using SPECT:
Concise communication,” J. Nucl. Med. 23, 446-450 (1982).
27
S. E. Strand, K. Norrgren, C. Ingvar, T. Brodin, L. Hallstadius, and M.
Ljungberg, “Parameters required in a dose planning model for radioimmunotherapy,” in Radionuclides for Therapy, Bottsteiner Colloquium
IV (Villigen, Switzerland, 1986), pp. 75-90.
28
M. Ljungberg and S. E. Strand, “Dose planning with SPECT,” Int. J.
Cancer Suppl. 2, 67-70 (1988).
29
M. Ljungberg and S. E. Strand, “Quantitative SPECT in oncological
nuclear medicine: Application in dose planning for radionuclide therapy,” Hospimedica 6, 17-21 (1988).
30
S. E. Strand and M. Ljungberg, “Absorbed dose planning in radionuclide therapy based on quantitative SPECT,” Antib. Immunoconj. Radiopharm, 4, 673-680 ( 1991).
31
L.T. Kircos, J. E. Carey, and J. W. Keyes, “Quantitative organ visualization using SPECT,” J. Nucl. Med. 28, 334-341 (1987).
32
G. L. DeNardo, D. J. Macey, S. J. DeNardo, C. G. Zhang, and T. R.
Custer, “Quantitative SPECT of uptake of monoclonal antibodies,”
Semin. Nucl. Med. 19, 22-32 (1989).
33
G. Iosilevsky, O. Israel, A. Frenkel, E. Even-Sapir, S. Ben-Haim, A.
Front, G. M. Kolodny, and D. Front, “A practical technique for quantitation of drug delivery to human tumors and organ absorbed radiation dose,” Semin. Nucl. Med. 19, 33-46 (1989).
34
P. B. Zanzonico, R. E. Bigler, G. Sgouros, and A. Strauss, “Quantitative SPECT in radiation dosimetry,” Semin. Nucl. Med. 19, 47-61
(1989).
35
K. F. Koral, “Calculating radiation absorbed dose for pheochromocytoma tumors in 131-I MIBG therapy,” Int. J. Oncol. Biol. Phys. 17,
211-218 (1989).
16
K. F. Koral, F. M. Swailem, S. Buchbinder, N. H. Clinthome, W. L.
Rogers, and B. M. W. Tsui, “SPECT dual-energy-window Compton
correction: Scatter multiplier required for quantification,” J. Nucl.
Med. 31, 90-98 (1990).
37
R. Loevinger and M. Berman, “A schema for absorbed dose calculations for biologically distributed radionuclides,” MIRD Pamphlet No
1, J. Nucl. Med. 9 (Suppl. l), 7-14 (1968).
38
R. Loevinger and M. Berman, “A schema for absorbed dose calculations for biologically distributed radionuclides,” MIRD Pamphlet No
1, Revised, Society of Nuclear Medicine, New York ( 1976).
39
M. J. Berger, “Energy deposition in water by photons from point isotropic sources,” MIRD Pamphlet No. 2, J. Nucl. Med. 9 (Suppl. l),
15-25 (1968).
40
G. L. Brownell, W. H. Ellett, and A. R. Reddy, “Absorbed fractions
for photon dosimetry,” MIRD Pamphlet No. 3, J. Nucl. Med. 9
(Suppl. 1), 27-39 (1968).
41
L.T. Dillman, “Radionuclide decay schemes and nuclear parameters
for use in radiation dose estimation,” MIRD Pamphlet No. 4, J. Nucl.
Med. 10 (Suppl. 2), 5-32 (1969).
42
W.S. Snyder, M. R. Ford, G. G. Warner, and H. L. Fisher Jr., “Estimates of absorbed fractions for monoenergetic photon sources uniformly distributed in various organs of a heterogeneous phantom,”
MIRD Pamphlet No. 5, J. Nucl. Med. 10 (Suppl. 3), 5-52 (1969).
43
W.S. Snyder, M. R. Ford, and G. G. Warner, “Estimates of absorbed
fractions for monoenergetic photon sources uniformly distributed in
various organs of a heterogeneous phantom,” MIRD Pamphlet No. 5,
526
Strand, Zanzonico, and Johnson: Pharmacokinetic modeling
Revised, Society of Nuclear Medicine, New York ( 1978).
L. T. Dillman, “Radionuclide decay schemes and nuclear parameters
for use in radiation dose estimation,” Part 2, MIRD Pamphlet No. 6,
J. Nucl. Med. 11 (Suppl. 4), 5-32 (1970).
45
M. J. Berger, “Distribution of absorbed doses around point sources of
electrons and beta particles in water and other media,” MIRD Pamphlet No. 7, J. Nucl. Med. 12 (Suppl. 5), 5-23 (1971).
46
W.H. Ellett and R. M. Humes, “Absorbed fractions for small volumes
containing photon-emitting radioactivity,” MIRD Pamphlet No. 8, J.
Nucl. Med. 12 (Suppl. 5). 25-32 (1971).
47
L. T. Dillman and F. C. Von der Lage, “Radionuclide decay schemes
and nuclear parameters for use in radiation dose estimation,” MIRD
Pamphlet No. 10, Society of Nuclear Medicine, New York (1975).
48
W.S. Snyder, M. R. Ford, G. G. Warner, and S. B. Watson, "'S',
absorbed dose per unit cumulated activity for selected radionuclides
and organs,” MIRD Pamphlet No. 11, Society of Nuclear Medicine,
New York (1975).
49
M. Berman, “Kinetic models for absorbed dose calculations,” MIRD
Pamphlet No. 12, Society of Nuclear Medicine, New York (1977).
50
International Commission on Radiation Units and Measurements,
ICRU Rep. 32, “Methods of assessment of absorbed dose in clinical use
of radionuclides,” Washington, D.C. (1979).
51
The International Commission on Radiobiological Protection, ICRP
Publication 53, Radiation Dose to Patients from Radiopharmaceuticals,
Pergamon, Oxford, England, 1987.
52
R. Loevinger, “Some remarks on the MIRD schema for absorbed-dose
calculations for biologically-distributed radionuclides,” in Medical Radionuclides: Radiation Dose and Effects, AEC Symposium Series 20,
edited by R. J. Cloutier, C. L. Edwards, and W. S. Snyder (Oak Ridge,
TN, 1969), pp. 481-489.
53
W. Per1 “A method for curve-fitting by exponential functions,” Int. J.
Appl. Radiat. Isotopes 8, 211-222 ( 1960).
54
R.A. Shipley and R. E. Clark, Tracer Methods for In Vivo Kinetics
(Academic, New York, 1972).
55
M. Berman, E. Shahn, and M. F. Weiss, “The routine fitting of kinetic
data to models-A mathematical formalism for digital computers,”
Biophys. J. 2, 275-287 ( 1962).
56
M. Berman, M. Weiss, and E. Shahn, “Some formal approaches to the
analysis of kinetic data in terms of linear compartmental systems,”
Biophys. J. 2, 289-298 (1962).
57
R. C. Boston, P. C. Greif, and M. Berman, “Conversational
SAAM-An interactive program for kinetic analysis of biological systems,” Comput. Program. Biomed. 13, 111-119 (1981).
58
P. B. Zanzonico, R. E. Bigler, F. J. Primus, E. Alger, R. De Jager, S.
Stowe, E. Ford, K. Brennan, and D. M. Goldenberg, “A compartmental modeling approach to the radiation dosimetry of radiolabeled antibody,” in Proceedings of the Fourth International Radiopharmaceutical
Dosimetry Symposium, A. T. Schlafke-Stelson and E. E. Watson P.S.
Department of Energy, DE86010102 (CONF-X51113), Oak Ridge,
TN, 1985], pp. 421-445.
59
G. Sgouros, R. E. Bigler, and P. B. Zanzonico, “Techniques for the
direct determination of cumulated activity from computer simulations
of linear and non-linear compartmental models,” Society of Nuclear
Medicine 34th Annual Meeting, Toronto, Canada ( 1987).
60
T. K. Johnson, “MABDOS: A generalized program for internal radionuclide dosimetry,” Computer Methods and Programs in Biomedicine 27, 159-167 (1988).
61
L. M. Cobb, “Intratumoural factors influencing the access of antibody
to tumor cells,” Cancer Immunol. Immunother. 28, 235-240 ( 1989).
62
A. M. Keenan, J. C. Harbert, and S. M. Larson, “Monoclonal antibodies in nuclear medicine,” J. Nucl. Med. 26, 531-537 ( 1985).
63
S. M. Larson, “Radiolabeled monoclonal anti-tumor antibodies in diagnosis and therapy,” J. Nucl. Med. 26, 53X-545 (1985).
64
A. R. Bradwell, D. S. Fairwether, P. W. Dykes, A. Keeling, A.
Vaughan, and J. Taylor, “Limiting factors in the localization of tumors
with radiolabelled antibodies,” Immunology Today 6, 163-170 (19X5).
65
A.J. Fishman, B. A. Khaw, and H. W. Strauss, “Quo vadis radioimmunk imaging?,” Editorial, J. Nucl. Med. 30, 1911-1915 (1989).
66
D. A. Goodwin, “Pharmacokinetics and antibodies,” Editorial, J.
Nucl. Med. 28, 135X-1362 (1987).
67
T.C.Meeker, J. Lowder, D. G. Maloney, R. A. Miller, K. Thielemans,
R. Warnke, and R. Levy, “A clinical trail of anti-idiotype therapy for
B
cell malignancy,” Blood 65, 1349-1363 (1985).
68
D. Goodwin, C. Meares, C. Diamanti, M. McCall, C. Lai, F. Torti, M.
McTigue, and B. Martin, “Use of specific antibody for rapid clearance
44
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
526
of circulating blood background from radiolabelled tumor imaging proteins.” Eur. J. Nucl. Med. 9, 210-215 (1984).
69
P. Oehr, J. Westermann, and H. J. Biersack. “Streptavidin and biotin
as potential tumor imaging agents,” J. Nucl. Med. 29.72x-729 ( 1988).
70
A. L. Klibanov, A. V. Martynov, M. A. Slinkin, I. Y. Sakharov, M. D.
Smirnov. V. R. Muzykantov, S. M. Danilov, and V. P. Torchilin,
“Blood clearance of radiolabelled antibody: enhancement by lactosamination and treatment with biotin-avidin or anti-mouse IgG antibodies,” J. Nucl. Med. 29. 1951-1956 (1988).
71
V. V. Sinitsyn, A. G. Mamontova, Y. Y. Checkneva, A. A. Shnyra. and
S. P. Domogaatsky, “Rapid blood clearance of biotinylated IgG after
infusion of avidin,” J. Nucl. Med. 30, 66-69 (1989).
72
D.J. Hnatowich, F. Virzi, and M. Rusckowski, “Investigations of
avidin and biotin for imaging applications,” J. Nucl. Med. 28, l2941304 (1987).
73
R.R. Eger D. G. Covell, and J. A. Carrasquillo, “Kinetic model for
the biodistribution of an 111-In-labeled monoclonal antibody in humans,”
Cancer Res. 47, 3328-3336 (1987).
74
C. Ingvar, K. Norrgren, S. E. Strand, T. Brodin, P. E. Jonsson, and H.
O. Sjogren, “Biokinetics of radiolabelled monoclonal antibodies in heterotransplanted nude rats: Evaluation of corrected specific tissue uptake,” J. Nucl. Med. 30, 1224-1234 (1989).
75
C. Ingvar, K. Norrgren, S. E. Strand, T. Brodin, P. E. Jonsson, and H.
O. Sjogren, “Subcutaneous injection of monoclonal antibody 96.5.
Biokinetics in the nude rat heterotransplanted with malignant melanoma,” Acta Oncologica 29, 1047-1053 ( 1990).
76
C. Ingvar, K. Norrgren, S. E. Strand, T. Brodin, P. E. Jonsson, and H.
O. Sjogren, “Tumor uptake of monoclononal antibody after regional
intraarterial injection. Biokinetics in the nude rat heterotransplanted
with malignant melanoma,” Acta Oncologica (1991).
77
R.K. Jain, “Transport of macromolecules in tumor microcirculation,”
Biotechnol. Prog. 1, 81-94 (1985).
78
D. C. Covell, J. Barbet, O. D. Holton, C. D. V. Black, R. I. Parker, and
J. N. Weinstein, “Pharmacokinetics of monoclonal immunoglobulin
Gl, F(ab’)2, and Fab’ in mice,” Cancer Res. 46, 3969-3978 (1986).
79
D.G. Garlick and E. M. Renkin, “Transport of large molecules from
plasma to interstitial fluid and lymph in dogs,” Am. J. Physiol. 219,
1595-1605
(1970).
80
R. E. Bigler, P. B. Zanzonico, R. Leonard, M. Cosma, F. J. Primus, E.
Alger, R. DeJager, S. Stowe, E. Ford, K. Brennan, and D. M. Goldenberg, “Bone marrow dosimetry for monoclonal antibody therapy,” in
Proceedings of the Fourth International Radiopharmaceutical Dosimetry
Symposium, edited by A. T. Schlafke-Stelson and E. E. Watson [U.S.
Department of Energy, DE86010102 (CONF-851113), Oak Ridge,
TN,
1985], pp. 535-544.
81
J. A. Siegel, B. W. Wessels, E. E. Watson, M. G. Stabin, H. M. Vriesendorp, E. W. Bradley, C. C. Badger, A. B. Brill, C. S. Kwok, D. R.
Stickney, F. K. Echerman, D. R. Fisher, D. J. Buchsbaum, and S. E.
Order, “Bone marrow dosimetry and toxicity for radioimmunotherapy,” Antib. Immunoconj. Radiopharm. 3, 213-233 (1990).
82
B. A. Jonsson, S. E. Strand, and L. Andersson, “Radiation dosimetry
for indium-111-labeled anti-CEA-F(ab’), fragments evaluated from
tissue distribution in rats,” J. Nucl. Med. 33, 1654-1660 (1992).
83
P. A. W. Edwards, “Heterogenous expression of cell surface antigens in
normal epithelia and their tumors revealed by monoclonal antibodies,”
Br. J. Cancer 51, 149 (1985).
84
C. Ingvar, B. Jacobsson, T. Brodin, P. E. Jonsson, and S. E. Strand,
“Tumor antigen heterogeneity within melanoma metastases-An evaluation by immunohistochemistry,” Anticancer Res. 10, 219-223
(1990).
85
C. Ingvar, K. Norrgren, S. E. Strand, and P. E. Jonsson, “Heterogeneous distribution of radiolabelled monoclonal antibody. Autoradiographic evaluation in the nude rat model,” AntiCancer Res. ( 1991).
86
S. E. Strand, K. Ljunggren, K. Kairemo, A. Svedberg, K. Norrgren, C.
Ingvar, and O. Wanying, “Functional imaging and dosimetric applications of beta camera in RID and RIT,” Antib. Immunoconj. Radiopharmarm. 4, 631-635 (1991).
87
P. L. Jones, B. M. Gallagher, and H. Sands, “ARG analysis of monoclonal antibody distribution in human colon and breast tumor xenografts,” Cancer Immunol. Immunothe. 22, 134-143 (1986).
“J. M. Esteban, J. Schlom, F. Mornex, and D. Colcher, “RIT of athymic
mice bearing human colon carcinomas with monoclonal antibody
B72.3. Histological and ARC) study of effects on tumors and normal
organs,” Eur. J. Cancer Clin. Oncol. 23, 643-655 (1987).
“M. H. Griffith, E. D. Yorke, and B. W. Wessels, “Direct dose confir-
527
Strand, Zanzonico, and Johnson: Pharmacokinstic modeling
mation of quantitative autoradiography with micro-TLD measurements for RIT,” J. Nucl. Med. 29, 1795-1809 (1988).
90
K. Ydstrom. S. E. Strand, C. Ingvar, P. E. Jonsson, T. Brodin, and H.
O. Sjogren, “Parameters influencing the uptake of radiolabelled monoclonal antibody 96.5 in heterotransplanted malignant melanoma in
nude rats,” in Proceeding of Advances in the Application of Monoclonal
Antibodies
in Clinical Oncology, London (abstract) (1984).
91
R. B. Pedley, J. Boden, P. J. Harwood, A. J. Green, and G. T. Rogers,
“Relationship between tumor size and uptake of radiolabelled antiCEA in colon tumor xenograft,” Eur. J. Nucl. Med. 13, 197-202
(1987).
92
N. K. V. Cheung, J. E. Neely, B. Landmeier, D. Nelson, and F. Miraldi, “Targeting of ganglioside GD2 monoclonal antibody to neuroblastoma,”
J. Nucl. Med. 28, 1577-1583 (1987).
93
L.E. Williams, R. B. Duda, R. T. Proflitt, B. G. Beatty, J. D. Beatty,
J. Y. C. Wong, J. E. Shively, and R. J. Paxton, “Tumor uptake as a
function of tumor mass: A mathematical model,” J. Nucl. Med. 29,
103-109 (1988).
94
E. A. Cornelius, “Analysis of monoclonal antibody uptake in tumors:
The significance of surface area,” in Proceeding of Third International
Conference on Monoclonal Antibody Immunoconjugates for Cancer
(1988).
95
V.J. Philben, J. G. Jakowatz, B. G. Beatty, W. G. Vlahos, R. J.
Paxton, L. E. Williams, J. E. Shively, and J. D. Beatty, “The effect of
tumor CEA content and tumor size on tissue uptake of indium 111
labelled anti-CEA monoclonal antibody,” Cancer 57, 571-576 ( 1986).
96
C. Ingvar, “Radiolabelled monoclonal antibodies,” Thesis, Lund University, Sweden (1990).
97
J. N. Weinstein, R. R. Eger, and D. G. Covell, “The pharmacology of
monoclonal antibodies,” Ann. N. Y. Acad. Sci. 199-210 (1988).
98
K. Fujimori, D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “Modeling analysis of the global and microscopic distribution of immunoglobin G, F(ab’)S, and Fab in tumors,” Cancer Res. 49, 5656-5663
(1989).
99
K. Fujimori, D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “A
modeling analysis of monoclonal antibody percolation through tumors:
A
binding-site barrier,” J. Nucl. Med. 31, 1191-1198 ( 1990).
100
K. Koizumi. G. L. DeNardo, S. J. DeNardo, M. T. Hays, H. H. Hines,
P. O. Scheibe, J. S. Peng, D. J. Macey, N. Tonami, and K. Hisada,
“Multicompartmental analysis of the kinetics of radioiodinated monoclonal antibody in patients with cancer,” J. Nucl. Med. 27, 1273-1254
(1986).
101
R. R. Eger, D. G. Covell, J. A. Carrasquillo, P. G. Abrams, K. A.
Foon, J. C. Reynolds, R. W. Schroff, A. C. Morgan, S. M. Larsson, and
J. N. Weinstein, “Kinetic model for the biodistribution of an 111Inlabelled monoclonal antibody in humans,” Cancer Res. 47, 3328-3336
(1987).
102
A. Rescigno, H. Bushe, A. B. Brill, M. Rusckowski, T. W. Griffin, and
D. J. Hnatowich. “Pharmacokinetics modeling of radiolabeled antibody distribution in man,” Am. J. Physiol. Imaging. 5, 141-150
(1990).
103
K. Norrgren, S. E. Strand, and C. Ingvar, “Contrast enhancement in
RII and modification of the therapeutic ratio in RIT. A theoretical
evaluation of simulated extracorporeal immunoadsorption,” Antibody,
Immunoconjugates and Radiopharmaceuticals 5, 61-73 (1992).
104
R. E. Bigler and P. B. Zanzonico. “Adjuvant radioimmunotherapy for
micrometastases: A strategy for cancer cure,” in Radiolabeled Monoclonal Antibodies for Imaging and Therapy, edited by S. C. Srivastava
(Plenum, New York, 1988), pp. 409-429.
105
S. E. Strand, K. Norrgren, C. Ingvar, K. Erlandsson, and E. C. Persson, “Plasmapheresis as a tool for enhancing contrast in radioimmunoimaging and modifying absorbed doses in radioimmunotherapy,”
Med. Phys. 16, 465 (Abstract) (1989).
106
B. Charlton and K. Schindhelm, “The effect of extracorporeal antibody
removal on antibody synthesis and catabolism in immunized rabbits,”
Clin. Exp. Immunol. 60, 457-464 (1985).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
107
527
B. Charlton. K. Schindhelm, L. C. Smeby, and P. C. Farrell, “Analysis
of immunoglobulin G kinetics in the non-steady state,” J. Lab. Clin.
Med. 3. 312-320 (1985).
108
A. M. Zimmer, T. Steven, S. T. Rosen, S. M. Spies, R. GoldmanLeikin. J. M. Kazikiewics, E. A. Silverstein, and E. H. Kaplan, “Radioimmunotherapy of patients with cutaneous T-cell lymphoma using
an iodine-131-labeled monoclonal antibody: Analysis of retreatment
following plasmapheresis,” J. Nucl. Med. 29, 174-180 (1988).
109
K. Norrgren, S. E. Strand, R. Nilsson, L. Lindgren, and P. Lillehom,
“Evaluation of extracorporeal immunoadsorption for reduction of the
blood background in diagnostic and therapeutic applications of radiolabelled MAb’s,” Antib. Immunoconj. Radiopharm.4, 907-914
(1991).
110
K. Norrgren, S. E. Strand, R. Nilsson, L. Lindgren, and H.-O. Sjogren,
“A general extracorporeal immunoadsorption method to increase
tumor-to-normal tissue ratio in radioimmunoimaging and radioimmunotherapy,” J. Nucl. Med. 34 (1993).
111
T. K. Johnson, S. Maddock, R. Kasliwal, D. Bloedow, C. Hartman, A.
Feyerabend, D. Dienhart, S. Glenn, R. Gonzales, J. Lear, and P. Bunn,
“Radioimmunoadsorption of KC-4G3 antibody in peripheral blood:
Implications for radioimmunotherapy,” Antib. Immunoconj. Radiopharm. 4, 24 (Abstract) (1990).
112
M. McAteer, H. Pastusiak, A. Hamstra, E. Maddock, D. Dienhart, R.
Kasliwal, S. Glenn, A. Heal, P. Bunn, and S. Maddock, “Performance
of an immunoadsorption column used to improve radioimmunodetection,” Antib., Immunoconj. Radiopharm. 4, 23 (Abstract) (1990).
113
S. Maddock, P. Bunn, D. Dienhart, A. Feyerabend, S. Glenn, T.
Johnson, R. Kasliwal, J. Lear, E. Maddock, and M. McAteer, “Strategy and use of immunoadsorption to improve RAIT,” Antib. Immunoconj. Radiopharm. 4, 34 (Abstract) (1990).
114
C. Hartman, D. C. Bloedow, D. Dienhart, R. Kasliwal, T. K. Johnson,
S. W. Maddock, S. D. Glenn, G. M. Butchko, A. Feyerabend, R.
Gonzales, J. L. Lear, and P. A. Bunn, “A pharmacokinetic model
describing the removal of circulating radiolabelled antibody by extracorporeal immunoadsorption,” J. Pharmacokinet. Biopharm. 19, 385
(1991).
115
G. Sgouros, R. E. Bigler, and P. B. Zanzonico, “Compartmental model
simulations of antibody kinetics: What parameters most influence antibody dosimetry?,” Supplement, J. Nucl. Med. 28, 617 (Abstract)
(1987).
116
R. E. Bigler, P. B. Zanzonico, M. Cosma, and G. Sgouros, “Adjuvant
radioimmunotherapy for micrometastases: A strategy for cancer cure,”
in Radiolabeled Monoclonal Antibodies for Imaging and Therapy, edited by S. Srivastava (Plenum, New York, 1988, pp. 409-429.
117
R. W. Howell, D. V. Rao, and K. S. R. Sastry, “Macroscopic dosimetry for radioimmunotherapy: Nonuniform activity distributions in
solid tumors,” Med. Phys. 12, 405-412 (1989).
118
J. L. Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
119
J. L. Humm and L. M. Cobb, “Nonuniformity of tumor dose in radioimmunotherapy,” J. Nucl. Med. 31, 75-83 (1990).
120
G. M. Makrigiorgos, S. J. Adelstein, and A. I. Kassis, “Limitations of
conventional internal dosimetry at the cellular level,” J. Nucl. Med. 30,
1856-1864 (1989).
121
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
122
J. A. Jungerman, K. P. Yu, and C. I. Zanelli, “Radiation absorbed dose
estimates at the cellular level for some electron-emitting radionuclides
for radioimmunotherapy,” Int. J. Appl. Radiat. Isot. 35, 883-888
(1984).
123
J. A. Jacquez, Compartmental Analysis in Biology and Medicine (University of Michigan, Ann Arbor, 1985), pp. 20-28.
Tumor dosimetry in radioimmunotherapy:
for beta particles
Methods of calculation
Peter K. Leichner
University of Nebraska Medical Center, Department of Radiology. Omaha, Nebraska 68198-1045
Cheuk S. Kwok
Hamilton Regional Cancer Centre, Ontario Cancer Treatment and Research Foundation and McMaster
University, Hamilton. Ontario, Canada
(Received 18 March 1992; accepted for publication 23 October 1992)
Calculational methods of beta-particle dosimetry in radioimmunotherapy (RIT) are reviewed
for clinical and experimental studies and computer modeling of tumors. In clinical studies,
absorbed-dose estimates are usually based on the in-vivo quantitation of the activity in tumors
from gamma camera images. Because of the limited spatial resolution of gamma cameras,
clinical dosimetry is necessarily limited to the macroscopic level (macrodosimetry ) and the
MIRD formalism for absorbed-dose calculations is appropriate. In experimental RIT, tumor
dimensions are often comparable to or smaller than the beta-particle range of commonly used
188
90
radionuclides (for example, 1 3 1I, 6 7Cu, 1 8 6R e , Re, Y) and deviations from the equilibrium
dose must be taken into account in absorbed-dose calculations. Additionally, if small tumors are
growing rapidly at the time of RIT, the effects of tumor growth will need to be included in
absorbed-dose estimates. In computer modeling of absorbed-dose distributions, analytical, numerical, and Monte Carlo methods have been used to investigate the consequences of uniform
and nonuniform activity distributions and the effects of inhomogeneous media. Measurements
and calculations of the local absorbed dose at the multicellular level have shown that variations
in this dose are large. Knowledge of the absorbed dose is essential for any form of radiotherapy.
Therefore, it is important that clinical, experimental, and theoretical investigations continue to
provide information on tumor dosimetry that is necessary for a better understanding of the
radiobiological effects of RIT.
human and experimental tumors and tumor modeling
studies.
I. INTRODUCTION
There is an increasing body of clinical evidence which
shows that antibodies labeled with beta-emitting radionuelides have resulted in tumor remissions in some patients
with certain cancers. In experimental RIT, several investigators have reported complete remissions of tumor xenografts following the administration of radiolabeled antibodies. In clinical and experimental RIT, absorbed-dose
calculations are essential to gain an understanding of the
dose-response relationship for different cancers and varieties of antibodies labeled with beta emitters, evaluation of
normal-tissue toxicity, and treatment planning.
Tumor dosimetry of radiolabeled antibodies poses difficult problems, and a number of sophisticated models has
been developed to address these problems. As discussed by
Loevinger, 1 absorbed-dose estimates for administered radionuclides by their very nature are made for mathematical
models rather than patients. This is true of the models
included in this review. However, they resemble the actual
biological situation as much as possible so that the results
provide meaningful information for clinical and experimental RIT.
The purpose of this article is to summarize some of the
recently published techniques for tumor dosimetry in RIT
with beta-particle emitting radionuclides. These include
image-based dosimetry (macrodosimetry) often used in
clinical trials, and numerical, analytical and Monte Carlo
methods which have been employed for the dosimetry of
529
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
II. CALCULATIONAL METHODS
A. Macrodosimetry
In clinical studies, absorbed-dose estimates are based
on the in-vivo quantitation of the activity of radiolabeled
antibodies in tumors from planar gamma camera images,
single-photon emission computed tomography (SPECT),
positron emission tomography (PET), or a combination of
planar imaging and SPECT. Because of the limited spatial
resolution of gamma cameras, clinical dosimetry is necessarily limited to the macroscopic level (macrodosimetry).
Macrodosimetry is nonstochastic and due to the lack of
sufficiently detailed information about source distributions,
the MIRD schema for absorbed-dose calculations are used.
A dosimetry model for clinical RIT was developed by
Leichner et al.2,3 based on the MIRD formalism. 4 In this
formulation of radiolabeled antibody dosimetry, tumor
volumes were obtained from patients’ CT examinations.’
Thus, although the MIRD schema for formulating doserate equations was adopted, different tumor volumes were
taken into account for each patient. The basic dose-rate
equations’ were subsequently confirmed by Wessels and
Rogus 6 in a radionuclide model calculation which demonstrated that methods of calculation for clinical dosimetry
and computer modeling were in agreement to within 4%.
In clinical or macrodosimetry, the beta radiations were
0094-2405/93/0205294%3s01.20
© 1993 Am. Assoc. Phys. Med.
529
530
P. K. Leichner and C. S. Kwok: Tumor dosimetry In radioimmunotherapy
treated as nonpenetrating radiations because the tumor and
normal organ volumes were large compared with the range
of 131I or 9 0Y beta particles.“’ Tumor and normal organ
activities were quantitated from planar gamma camera images so that, due to a lack of more detailed information, the
assumption of a uniform distribution of activity was invoked in absorbed-dose calculations. The justification for
this was that tumor volumes were large enough so that
only a small fraction of the beta-particle energy escaped
from the tumors.2 Under this circumstance, the dose from
a uniform distribution equals the mean dose from a nonuniform distribution.’ Consequently, dose calculations provided a mean absorbed dose but provided no information
about the range of absorbed doses. A further difficulty with
this approach to macrodosimetry was that tumor volumes
computed from CT scans were not necessarily the same as
the volumes in which radiolabeled antibodies localized (localization volumes) because the physiological uptake of
radiolabeled antibodies may not have corresponded exactly
to the anatomical configuration of an organ or tumor.
These difficulties can potentially be overcome with quantitative SPECT and PET which provide localization volumes and distributions of activity directly from radionuclide images.8 However, even with quantitative SPECT or
PET clinical dosimetry will remain macrodosimetry.
6. Numerical and analytical methods
These methods have been used to calculate absorbeddose distributions in tumors and normal tissues resulting
from uniform and nonuniform distributions of beta emitters. In general, point-source functions or tabulated pointsource data were used to make numerical or analytical
calculations of the absorbed dose. An empirical pointsource function developed by Loevinger et al. 9 was employed by Kwok et al. 1 0 to compute absorbed-dose distributions resulting from radially symmetric activity
concentrations of 1 3 1I and 3 2P beta particles in soft tissue.
The same function was also used by Griffith et al. 11 t o
calculate the absorbed dose for 131 I and 9 0Y beta particles
for activity distributions obtained from quantitative autoradiography. In the latter investigation, measurements
were obtained with miniaturized thermoluminescent devices (TLD’s) and compared with calculations. The variation in measured absorbed dose throughout an experimental tumor was approximately 400%. Both studies showed
that the absorbed-dose distributions depended strongly on
the activity distributions and that for the assumed” and
measured” distributions and volumes, the higher energy
beta particles resulted in larger absorbed doses. Additionally, the variation in absorbed dose was greater for 1 3 1 I
than for 9 0Y beta particles due to the higher energy of the
latter.
The measurements by Cross 12 and theoretical work by
Berger 13 and Cross et al.14 showed that Loevinger's point.
source was inaccurate at small and large distances from a
point source. Additionally, this function breaks down for
low-energy beta emitters.15 Several authors have therefore
utilized the tabulated data 13,14 to develop more general analytic representations for absorbed dose distributions
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
530
around point sources or used these data directly in numerical calculations. For example, using tabulated values of
monoenergetic electron point kernels in water calculated
by Berger,13 Kwok et al.1 6 have developed analytical and
numerical methods to derive dose point kernels in water
for radionuclides with allowed beta transitions. The advantage of analytical representations and solutions is that they
simplify calculations significantly. These authors also investigated the effects of tissue heterogeneity on absorbeddose distributions. A polystyrene (PST)-aluminum interface was used to simulate a soft tissue-bone interface and
dose measurements were made at distances ranging from 0
to 314 mg/cm2 , with a 3 2P point source placed at the interface. A maximum increase of 12% in the absorbed dose
was measured at approximately 30 mg/cm 2 from the interface. The implication of this study is that there may be an
increase in the absorbed dose at marrow-bone interfaces
resulting from backscattered radiation. In contrast, there
was a decrease in absorbed dose when a PST-air interface
was used to simulate a soft tissue-air interface. For lowenergy electrons, the exact positions of the point sources
and the dose scoring region have an important effect on the
dose enhancement.”
Langmuir and Sutherland18 have investigated the effect
of tumor size on absorbed-dose distributions from beta
emitters when radiolabeled antibodies are not uniformly
distributed in tumors. Two theoretical dosimetry models
were considered; one for vascularized tumors and one for
micrometastases without vasculature. In dose calculations,
it was assumed that there was no penetration of radiolabeled antibodies into the tumors. These were compared to
calculations based on uniform activity distributions within
tumors. Absorbed-dose rates for 131 I and 9 0Y beta particles
were calculated by numerical integration and the use of
Berger’s point source data. 13 The results showed that for
small lesions (1 mm or less in diameter) a given concentration of 1 3 1I resulted in a higher dose rate than that obtained from an equal concentration of 9 0Y beta particles,
due to the lower absorbed fraction of the latter. On the
other hand, for vascularized tumors, ?-labeled antibodies
yielded higher absorbed dose rates and more uniform dose
distributions within tumors because of overlapping contributions from multiple sources. Similar conclusions were
reached by Howell et al. 1 9 who made numerical calculations of absorbed-dose distributions for several beta emitters (3 2P , 6 7C u , 9 0Y , 1 1 1A g , 1 3 1I, 1 8 8Re) and for a lowenergy electron emitter, 1 9 3 mP t . I n t h e i r m o d e l
calculations, activity distributions were spherically symmetric and depended linearly and exponentially on the radial coordinate. The results demonstrated that for larger
tumors (1 cm or greater in diameter) high-energy beta
emitters, such as 3 2P or 9 0Y, would be most effective,
whereas for smaller tumors (~1 mm in diameter)
medium-energy beta particles (e.g., 131 I, 6 7Cu) were better
suited. To treat micrometastases, these authors suggested
the use of 1 9 3 m P t .
A generalized empirical point-source function for betaparticle dosimetry was developed by Leichner et al. 20 from
Berger’s tabulated absorbed-dose distributions for point
531
P. K. Leichner and C. S. Kwok: Tumor dosimetry in radioimmunotherapy
sources in water.1 3 Absorbed-dose distributions for eight
r a d i o n u c l i d e s (3 H, 1 4C, 3 5S, 1 3 1 I, 1 1 1 Ag, 3 2P, 9 0Y, 1 0 6 R h )
with average beta-particle energies ranging from 5.7 keV
( 3 H) to 1.43 MeV ( 106 Rh) were computed from this pointsource function. The results demonstrated agreement with
tabulated data over the entire energy range and for a wide
range of distances from point sources. Analytical solutions
in terms of absorbed fractions were derived for two source
geometries, a thin source of infinite extent and a plane
source of finite thickness and infinite extent. Beta-particle
dose calculations for a plane source of finite thickness were
carried out for 1 3 1 I- and v-labeled antiferritin deposited
in experimental tumor lines and determined to be in agreement with measurements.2 1’ 22 These calculations showed
that even for uniform distributions of activity, the absorbed
dose was nonuniform when tumor dimensions were comparable to or smaller than twice the distance r 9 0. The distance r9 0 is a useful parameter that indicates the distance
from a point source within which 90% of the energy is
absorbed. 13 Second, the absorbed dose in small tumors is
significantly less than the absorbed dose for complete absorption of energy. Consequently, in experimental RIT
where tumors tend to be small, absorbed-dose calculations
should take tumor dimensions into consideration to determine tumor dose-response relationships.
An investigation of the multicellular dosimetry of
131
I-labeled antibody in follicular lymphoma was carried
out by Hui et al. 23 In this work, photomicrographs of a
lymph node specimen were analyzed to determine the
mean value and statistical variation of the radii of follicles,
interfollicular distances, and number densities of follicles.
These measurements were used to construct two geometric
models, a cubic lattice model and a randomized distribution model. The cubic lattice model assumed no variation
in follicular radii and interfollicular distance. In the randomized distribution model, Monte Carlo methods were
used to simulate the distribution of follicular radii, interfollicular distances, and the number density of follicles.
The 1 3 1I-labeled antibodies were considered to be point
sources, and absorbed-dose calculations were performed
using Berger’s tabulated values for point sources of beta
particles in water.13 From the granular density in photomicrographs, it was determined that the activity ratio of
radiolabeled antibody for follicular-to-interfollicular areas
was approximately 10:1, and the spatial distribution of localized absorbed dose was calculated for an average tumor
dose of 40 Gy. It was assumed that the activity distribution
was fairly uniform within the follicles and uniform in the
interfollicular space. Based on these data and assumptions,
calculations of the local absorbed dose were made. These
calculations showed that the local dose varied from 20 to
90 Gy. Additionally, 70% to 80% of the tissue (by volume) had an absorbed dose that was lower than the average dose. In this study, no significant difference was found
for calculations based on the cubic lattice model and the
randomized distribution model, demonstrating that in
some cases a relatively simple geometric model can be a
valid starting point for a difficult dosimetric problem.
Simple, analytic representations for dose-rate distribuMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
531
tions due to regions containing beta-particle sources were
developed by Werner using the energy-averaged transport
m o d e l . 2 4 - 2 8 Solutions of the model were presented for planar and spherical symmetry, and for random and nonuniform source distributions.
The effects of tumor size on energy absorbed fractions
and antibody binding heterogeneity were further discussed
by Humm.29 Absorbed fractions for-beta sources were calculated using a computer code developed specifically for
that purpose. For solid tumors, a spherical model was
adopted to investigate the effects of tumor size on absorbed
dose. Two cases were considered, a spherical volume containing a uniform distribution of activity (“hot sphere”)
and a “cold sphere” containing no activity but surrounded
by a uniform distribution of activity. For “hot spheres” of
radii 100 and 500 µm, absorbed fractions were computed
for 2 1 1 At, 9 0Y, 7 7As, 1 3 1 Au, and 1 3 1 I. For such small tumor
spheres,
At and low-energy beta emitters ( 7 7As, 1 9 9Au)
had the largest absorbed fractions (highest energy deposition). For “cold spheres,” dose profiles were generated for
radii 0.5, 1, 2, and 4 mm. These showed that high-energy
beta emitters, such as 90Y, resulted in the highest absorbed
dose in “cold regions” resulting from the surrounding activity. The dosimetry of radiolabeled antibodies for nonsolid tumors; that is, isolated tumor cells as is the case for
circulating leukemia cells was also considered by Humm.
For assumed cellular and nuclear diameters of 20 and 10
µm, respectively, it was calculated that only one in 16
particles emitted on a cell surface membrane would
traverse the nucleus. It was, therefore, suggested that for
this type of RIT, radionuclides that emit large numbers of
low-energy electrons, e.g., 119 Sb might be optimal, as previously mentioned by Sastry et al. 3 0
These dosimetric considerations were developed further
by Humm and Cobb31 in calculations of the energy deposition at the cellular level. One tumor model consisted of a
random distribution of cells, and absorbed-dose calculations were made for two different source distributions: a
uniform distribution of sources and sources geometrically
placed on cell membranes. For a uniform distribution of
sources, the MIRD schema for absorbed dose calculations
was valid if the tumor was large enough so that boundary
effects could be ignored. For cell-surface bound antibodies
the energy deposited in cell nuclei was expressed as the
sum of two components: the energy deposition in the cell
nucleus from sources bound to the membrane of that cell
and the energy deposition to neighboring cell nuclei to
which the source was not bound. The energy deposited per
cell nucleus per decay was calculated for 211 At, 199 Au, 131 I,
and 90Y with internuclear distances ranging from 10 to 100
µm. The results showed that of the three beta emitters, 90Y
deposited the largest amount of energy per nucleus per
decay for both source distributions and all internuclear
distances considered. Additionally, 90Y required the smallest number of decays per cell membrane for 99% cell inactivation. We note, however, that in this model 211 At was
superior to the three beta emitters in energy deposition and
number of decays required for cell inactivation.
In all of the models discussed, calculations of the ab-
532
P. K. Leichner and C. S. Kwok: Tumor dosimetry in radioimmunotherapy
sorbed dose for tumors were made for constant tumor
mass. This assumption is justified in many experimental
and clinical trials in RIT because tumors are either no
longer growing or are growing at a slow rate. However,
small tumors and micrometastases may be growing rapidly
at the time of antibody administration so that tumor mass
and the absorbed fraction can change significantly during
treatment. This dosimetric problem was investigated by
Howell et al.33 who generalized the MIRD Schema to include the time dependence of tumor mass and absorbed
fractions in absorbed-dose calculations. The modified
MIRD equations were applied to an in-vitro model (multicellular V79 spheroids) and an in-vivo tumor (myeloma).
The results of this work show that tumor growth can be a
significant factor in tumor dosimetry and that in rapidly
growing tumors the absorbed dose will be overestimated if
such growth is not taken into account in calculations.
III. MONTE CARLO METHODS
The widely used tables of beta-particle dose kernels by
Berger 13 and Cross14 are based on Spencer’s 33,34 numerical
solution of the transport equation of primary electrons in a
uniform unbounded medium in the continuous slowingdown approximation (csda). Calculations based on Spencer’s theory agreed well with measurements 12 and this provided a sound basis for beta-particle dosimetry. An
important advance has been the development of Monte
Carlo methods for the simulation of electron transport. By
dividing the electron path into small segments, Berger 3 5
took into account multiple scattering and energy loss fluctuations. Departures from csda due to delta-ray and bremsstrahlung production were also incorporated and resulted
in improved point kernels for monoenergetic electrons in
w a t e r . 36 T h e s e r e s u l t s w e r e s p e c t r a l l y w e i g h t e d b y
Prestwich et al.37 to calculate beta dose point kernels for
32
P, 6 7C u , 9 0Y, 1 3 1 I, 1 8 6 Re, and 1 8 8 Re. Additionally, the
authors provided an analytic representation of the point
kernels.
A different approach was taken by Simpkin and
Mackie 38 who employed the EGS4 Monte Carlo computer
code to generate point kernels in water for 3 2P, 6 7Cu, 9 0Y ,
105
Rh, 1 3 1I, 1 5 3Sm, 1 8 6Re, and 1 8 8Re beta particles. Originally developed for high-energy physics, the EGS4 code
has become very useful in medical physics and can be obtained from Oak Ridge National Laboratory. 39 Simpkin
and Mackie compared their results with those published by
Berger 36 and Prestwich et al.33 and concluded that for radionuclides of interest in RIT, the agreement in point kernels obtained by different authors was remarkably good.
The EGS4 Monte Carlo code was also used by Johnson
et al.4 0 to calculate the radiation-absorbed dose at a boneto-marrow interface for 1 5 3Sm, 1 8 6Re, and 1 8 6Ho. These
radionuclides were chosen because they are of current interest as radiotherapeutic agents for metastatic bone cancers and for marrow ablation. In this calculation, activity
was taken to be distributed uniformly at midplane in the
endosteum which was modeled as a 10-µm-thick slab between marrow and cortical bone. The calculated absorbed
dose distributions included contributions from atomic elecMedical Physics, Vol. 20, No. 2, Pt. 2. Mar/Apr 1993
532
trons, beta particles, and photons. An important result of
this investigation was that the backscatter contribution to
the absorbed dose in the marrow increased from 3% to 4%
at the source to 6% to 8% at a marrow depth of 100 µm.
These results are consistent with those obtained by Kwok
et al.1 7
Humm41 has described a Monte Carlo computer model
to calculate energy deposition in tumor cell nuclei following the administration of “‘At-labeled antibodies. This approach to the dosimetry of radiolabeled antibodies was
subsequently extended by Humm and Cobb 31 to simulate
the tubular structure of differentiated colon carcinoma.
Cells of 10-µm radii containing 5-µm spherical nuclei were
assumed to be packed along cylinders which were separated by a variable distance. The sources ( 2 1 1 At or 1 3 1 I )
were placed on the outer surfaces of the cylinders. For 131I,
a constant LET (0.2 keV/µm) model was used with
straight line tracks of range 487 µm. The energy deposition
per cell nucleus per decay was calculated for a uniform
distribution of sources throughout the tumor volume and
for sources bound to the outer surface of the cylinders with
an outer radius of 50 µm and an inner radius of 30 µm. The
cell nuclei were centered at 40 µm from the cylinder axis.
A geometric enhancement factor was computed by dividing the energy deposition resulting from bound sources by
the energy deposition from uniformly distributed (unbound) sources. These calculations were made for distances between cylinders ranging from 0 to 200 µm. The
geometric enhancement factor was greater than one at all
intercylinder distances showing that the energy deposited
per cell nucleus per decay was greater for sources bound
uniformly to the outer surfaces than for sources distributed
uniformly throughout the tumor. This theoretical tumor
model demonstrated that the geometric enhancement factor, and hence the absorbed dose, depended strongly on the
spatial source-to-nuclei relationship at the micrometer
level.
IV. DISCUSSION
In this article, we have summarized some of the calculational methods for tumor dosimetry in RIT, with emphasis on beta particles. There are several reasons for this. As
stated in the Introduction, antibodies conjugated to betaparticle emitting radionuclides have resulted in tumor remissions. Second, currently used radiolabels in clinical
RIT, such as 1 3 1 I, 6 7Cu, 1 8 6 Re, 1 8 8 Re, and 9 0Y emit beta
particles that span a wide range of energies and it was,
therefore, important to review methods used and results
obtained by different authors in the computation of pointsource kernels. In general, Monte Carlo calculations have
resulted in improved beta and electron point-dose
kemels 35-38 as compared to those based on electron transport theory. 3 3 , 3 4 However, for beta emitters of interest in
RIT, differences in point-source kernels obtained by different methods were determined to be small. 38 For these beta
emitters it is, therefore, appropriate to use tabulated
values12,13 of absorbed-dose distributions in analytical or
numerical dose calculations. For completeness, we note
that in all references cited, bremsstrahlung has not been
533
P. K. Leichner and C. S. Kwok: Tumor dosimetry In radioimmunotherapy
included in tumor dose calculations because in soft tissue
less than 1% of the beta-particle energy is converted to
bremsstrahlung. 42,43
The type of information needed for tumor dosimetry in
RIT is under most circumstances no different than that
needed for other biologically distributed radionuclides:
physical data for the decay of the radionuclide, the distribution of absorbed energy of the emitted radiations, and
cumulated activities or residence times in the tumor. An
added difficulty, not usually encountered in normal-tissue
dosimetry, may occur if a tumor is rapidly growing. In this
case, the time dependence of tumor mass and absorbed
fractions will need to be included in dose calculations. 3 2
Activity distributions as a function of time and cumulated activities in tumors are difficult to obtain. This is
especially true in clinical studies and to a lesser extent in
experimental RIT where serial necropsies can provide the
necessary information. The shortcomings of image-based
macrodosimetry are well-understood: limited spatial resolution and difficulties associated with the extraction of
quantitative information from planar gamma camera or
emission-tomographic images. Although for most tumors
that can be imaged a mean value of activity and hence
absorbed dose can be determined, this information is not
sufficient to unravel the radiobiological effects of RIT.
Therefore, macrodosimetry will need to be augmented by
dosimetry on the cellular or multicellular level. For example, the dosimetry of 131 I-labeled antibodies in follicular
lymphoma 23 has shown that calculations of the local absorbed dose can be used to make improved estimates of the
cell killing efficiency of radiolabeled antibodies. Knowledge
of the absorbed dose is central to radiation oncology and
for gaining an understanding of dose-response relationships in RIT.
ACKNOWLEDGMENTS
One of the authors (PKL) gratefully acknowledges
port under DOE Grant No. DE-FG02-91ER61195.
other author (CSK) acknowledges support by Natural
ences and Engineering Research Council of Canada
U.S. NC1 Grant No. CA50872.
1
supThe
Sciand
R. Loevinger, “Distributed radionuclide sources,” in Radiation Dosimetry, edited by F. H. Attix and E. Tochilin (Academic, NY, 1969)
Volume III.
2
P. K. Leichner, J. L. Klein, J. B. Garrison, R. E. Jenkins, E. L. Nickoloff, D. S. Ettinger, and S. E. Order, “Dosimetry of 131I-labeled antiferritin in hepatoma: A model for radioimmunoglobulin dosimetry,”
Intl. J. Rad. Oncol. Biol. Phys. 7, 323-333 (1981).
3
P. K. Leichner, J. L. Klein, S. S. Siegelman, D. S. Ettinger, and S. E.
Order, “Dosimetry of “‘I-labeled antiferritin hepatoma,” Cancer
Treat. Rep. 67, 647-658 (1983).
4
R. J. Cloutier, E. E. Watson, R. H. Rohrer, and E. M. Smith, “Calculating the radion dose to an organ,” J. Nucl. Med. 14, 53-55 (1973).
5
N.-C. Yang, P. K. Leichner, E. K. Fishman, S. S. Siegelman, T. L.
Frankel, J. R. Wallace, D. M. Loudenslager, W. G. Hawkins, and S. E.
Order, “CT volumetrics of primary liver cancers,” J. Comput. Assist.
Tomogr. 10, 621-628 (1896).
6
B. W. Wessels and R. D. Rogus, “Radionuclide selection and model
absorbed dose calculations for radiolabeled tumor associated antibodies,” Med. Phys. 11, 638-645 (1984).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
7
533
P. K. Leichner, N.-C. Yang, T. L. Frankel, D. M. Loudenslager, W. G.
Hawkins, J. L. Klein, and S. E. Order, “Dosimetry and treatment
planning for y-labeled antiferritin in hepatoma,” Intl. J. Rad. Oncol.
Biol. Phys. 14, 1033-1042 (1988).
8
P. K. Leichner, W. G. Hawkins, and N.-C. Yang, “Quantitative
SPECT in radioimmunotherapy,” Antib. Immunoconjug. and Radiopharm. 4, 25 (1990).
9
R. Loevinger, E. M. Japha, and G. L. Brownell, “Discrete radioisotope
sources,” in Radiation Dosimetry, edited by G. J. Hine and G. L.
Brownell (Academic, NY, 1956).
10
C. S. Kwok, W. V. Prestwich, and B. C. Wilson, “Calculation of radiation doses for nonuniformly distributed β and γ radionuclides in soft
tissue,” Med. Phys. 12, 405-412 (1985).
11
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
12
W. G. Cross, “The distribution of absorbed energy from a beta point
source,” Can. J. Phys. 45, 2021-2040 (1967).
13
M. J. Berger, “Distribution of absorbed dose around point sources of
electrons and beta particles in water and other media,” Medical Internal Radiation Dose (MIRD) Committee, Pamphlet No. 7 (The Society of Nuclear Medicine, NY, 1971).
14
W. G. Cross, H. Ing, N. O. Freedman, and J. Mainville, “Tables of
beta-ray distributions in water, air, and other media,” Atomic Energy
of Canada Ltd., Report No. AECL-7617, Chalk River Nuclear Laboratories, Chalk River, Ontario, Canada (1982).
15
K. Tagden and W. Scheuerman, “Estimation of absorbed dose in the
cell nucleus after incorporation of 3H- or 14C-labeled thymidine,” Rad.
Res. 41, 202-216 (1970).
16
C. S. Kwok, M. Irfan, L. B. Chan, and W. V. Prestwich, “Beta dosimetry for radioimmunotherapy of cancer using labeled antibodies,” NC1
Monographs 3, 73-82 (1987).
17
C. S. Kwok, P. J. Bialobzyski, S. K. Yu, and W. V. Prestwich, “Effect
of tissue inhomogeneity on dose distribution of point sources of lowenergy electrons,” Med. Phys. 17, 786-793 (1990).
18
V. K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 (1988).
19
R. W. Howell, D. V. Rao, and K. S. R. Sastry, “Macroscopic dosimetry for radioimmunotherapy: nonuniform activity distributions in
solid tumors,” Med. Phys. 16, 66-74 ( 1989).
20
P. K. Leichner, W. G. Hawkins, and N.-C. Yang, “A generalized,
empirical point-source function for beta-particle dosimetry,” Antib.
Immunoconj. Radiopharm. 2, 125-144 (1989).
21
J. L. Klein, T. H. Nguyen, P. Laroque, K. A. Kopher, J. R. Williams,
B. W. Wessels, L. E. Dillehay, J. Frincke, S. E. Order, and P. K.
Leichner, “Yttrium-90 and iodine-131 radioimmunoglobulin therapy of
an experimental hepatoma,” Cancer Res. 49, 6383-6389 (1989).
22
P. K. Leichner, N.-C. Yang, B. W. Wessels, W. G. Hawkins, S. E.
Order, and J. L. Klein, "Dosimetry and treatment planning in radioimmunotherapy,” in Frontiers of Radiation Therapy and Oncologv, edited by J. M. Vaeth and J. L. Meyer (Karger Verlag, Basel, Switzerland, 1990), Vol. 24, pp. 109-122.
23
T. E. Hui D. R. Fisher, O. W. Press, J. F Eary, J. N. Weinstein, C. C.
Badger, and I. D. Bernstein, “Localized beta dosimetry of “‘I-labeled
antibodies in follicular lymphoma,” Med. Phys. 19, 97-104 (1992).
24
B. L. Werner and I. J. Das, “Dose distributions in regions containing
beta sources: Plane interfaces in a homogeneous medium,” Med. Phys.
14, 797-806 (1987).
25
B. L. Werner, “Dose distributions in regions containing beta source:
small-scale nonuniformities,” Med. Phys. 14, 807-808 (1987).
26
B. L. Werner, C. S. Kwok, and I. J. Das, “Dose distributions in regions
containing beta sources: Large spherical regions in a homogeneous
medium,” Med. Phys. 15, 358-363 (1988).
27
B. L. Werner, C. S. Kwok, and I. J. Das, “Dose distributions in regions
containing beta sources: uniform spherical source regions in homogeneous media,” Med. Phys. 18, 1181-1191 (1991).
28
B. L. Werner, “Dose distributions in regions containing beta sources:
Irregularly shaped source distributions in homogeneous media,” Med.
Phys. 18, 1192-1194 (1991).
29
J. L. Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
30
K. S. R. Sastry, C. Haydock, A. M. Basha, and D. V. Rao, “Electron
dosimetry for radioimmunotherapy: Optimal electron energy,” Radiat.
Prot. Dosim. 13, 249-252 (1985).
534
P. K. Leichner and C. S. Kwok: Tumor dosimetry In radioimmunotherapy
31
J. L. Humm and L. M. Cobb, “Nonuniformity of tumor dose in radioimmunotherapy,” J. Nucl. Med. 31, 75-83 (1990).
32
R. W. Howell, V. R. Narra, and D. V. Rao. “Absorbed dose calculations for rapidly growing tumors,” J. Nucl. Med. 33, 277-281 (1992).
33
L. V. Spencer, “Theory of electron penetration,” Phys. Rev. 98, 15971615 (1955).
34
L. V. Spencer, “Energy dissipation by fast electrons,” National Bureau
of Standards, Monograph 1 (U.S. Department of Commerce, Washington, D.C., 1959).
35
M. J. Berger, “Monte Carlo calculation of the penetration of diffusion
of fast charged particles,” in Methods in Compututional Physics edited
by B. Alder, S. Fembach, and M. Rotenerg (Academic, NY, 1963).
36
M. J. Berger, “Improved point kernels for electron and beta-ray dosimetry,” NBSIR 73-107 (Center for Radiation Research, U.S. Department of Commerce, Washington, D.C., 1973).
37
W. V. Prestwich, J. Nunes, and C. S. Kwok, “Beta dose point kernels
for radionuclides of potential use in radioimmunotherapy,” J. Nucl.
Med. 30, 1036-1046 (1989); ibid 30, 1739-1740 (1989).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
38
534
D. J. Simpkin and T. R. Mackic, “EGS4 Monte Carlo determination of
the beta dose kernel in water,” Med. Phys. 17, 179-186 (1990).
39
Radiation Shielding Information Center, Oak Ridge National Laboratory, P.O. Box 2008, Oak Ridge, TN 37831-6362.
40
J. C. Johnson, S. M. Langhorst, S. K. Loyalka, W. A. Volkert, and A.
R. Ketring, “Calculation of radiation dose at a bone-to-marrow interface using Monte Carlo modeling techniques (EGS4),” J. Nucl. Med.
33, 623-628 (1992).
41
J. L. Humm, “A microdosimetric model of astatine-211 labeled antibodies for radioimmunotherapy,” Intl. J. Radiat. Oncol. Biol. Phys. 13,
1767-1773 (1987).
42
M. J. Berger and S. M. Seltzer, “Tables of energy losses and ranges of
electrons and positrons,” (National Aeronautics and Space Administration, Washington, DC., 1964).
43
L. E. Williams, J. Y. C. Wang, D. O. Findley, and B. W. Forell,
“Measurement and estimation of organ bremsstrahlung radiation
dose,” J. Nucl. Med. 30, 1373-1377 (1989).
Microdosimetric concepts in radioimmunotherapy
J. L. Humm
Joint Center for Radiation Therapy, Harvard Medical School, 50 Binney Street, Boston,
Massachussetts 02115
J. C. Roeske
University of Chicago Medical Center. Radiation Therapy, 5841 S. Maryland Avenue. Box 440, Chicago,
Illinois 60637
D. R. Fisher
Battelle, Pacific Northwest Laboratories, P. O. Box 999, K3-53, Richland, Washington 99352
G. T. Y. Chen
University of Chicago Medical Center, Radiation Therapy, 5841 S. Maryland Avenue, Box 440, Chicago,
Illinois 60637
(Received 18 March 1992; accepted for publication 15 September 1992)
In microdosimetry particular emphasis is placed on the stochastic fluctuation of dose in small
target volumes such as individual cell nuclei or chromatin fiber, and their relevance to radiobiologic toxicity. Thus microdosimetry is intimately associated with models of radiation action.
There are three principal areas where microdosimetry has been applied: (1) radiation protection, (2) high LET radiotherapy, e.g., neutron therapy, and (3) incorporated radionuclides, and
in this latter category the importance of microdosimetry to the radiobiology of radiolabeled
antibodies is becoming increasingly recognized. The objective of microdosimetry is the complete characterization of energy deposition within all target volumes throughout the tissue of
interest, The importance and relevance of this pursuit will depend upon the properties of the
radionuclide emissions and the spatial distribution of the radionuclide relative to the target
volumes. If the distribution of internal emitters within both malignant and normal tissue is
uniform, the application of microdosimetry to radioimmunotherapy (RIT) is limited to
a-emitters and Auger emitters. Under such circumstances the traditional MIRD formalism for
the evaluation of tumor and tissue doses from the commonly used P-emitters is entirely adequate. This, however, is rarely the case. When the distribution of radiolabeled antibody is
nonuniform, techniques of dose averaging over volumes greater in size than the individual target
volumes can become inadequate predictors of the biological effect. The concepts, methods, and
realm of applicability of microdosimetry within the field of radioimmunotherapy are emphasized
in this paper.
Key words: microdosimetry, radiolabeled antibodies, energy deposition, alpha emitters, beta
emitters
I. CONCEPTS IN MICRODOSIMETRY
A. Introduction
Radiation dosimetry is the study of the physical properties
of radiation energy deposition in tissue. Radiation dose in
conventional dosimetry is a macroscopic concept.’ Target
volumes are many orders of magnitude greater than the
individual cellular entities which make up tissue. The dose
to a macroscopic multicellular volume is obtained by the
summation of the total energy deposited by multiple radiation tracks over the volume divided by the mass of that
volume. Microdosimetry is the study of radiation energy
deposition within microscopic volumes, where “microscopic” encompasses sensitive target volumes ranging from
the diameter of a cell (typically 20 µm) down to the diameter of the DNA molecule (2 nm). Although microdosimetry is concerned with the same concept of energy deposition per unit mass as dosimetry, the difference in size of
the target volume of interest introduces stochastic effects
which are negligible in conventional dosimetry. The mag535
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
nitude and importance of stochastic fluctuations in the target volumes depend greatly on the target diameter, on the
energy and linear energy transfer (LET) of the particles,
and on the relative number of particles, i.e., the magnitude
of the radition dose. For example, bulk tissue receiving an
absorbed dose of 1 cGy of γ− rays, results in an average
number of electron track traversals of approximately 50
per cell, with a standard deviation of 7 hits. The same 1
cGy absorbed dose of a-particles would result in a spectrum of individual cell doses ranging from 0-30 cGy, with
a mean number of α− particle hits per cell of only 0.1, and
with 90% of the cells experiencing zero hits. 2
B. The sensitive target
Several radiobiological studies point to the nucleus 3
and more specifically the DNA as the primary sensitive
target for cellular inactivation.- The evidence that DNA
is the principal target for radiation cell sterilization comes
from studies with radionuclides which result in a dense
0094-2405/93/020535-0-08$01.20
© 1993 Am. Assoc. Phys. Med.
535
536
Humm et al.: Microdosimetric concepts in radioimmunotherapy
cluster of ionizations within 2 nm of the decay site. These
radionuclides exhibit extreme positional effects, i.e., if directly incorporated into the DNA they may be many fold
more radiotoxic than when appended to other cellular
structures. Recent debates at the radiation research conference (March 1992) at Salt Lake City alluded to the
variation of DNA radiosensitivity with organizational
structure, i.e., the degree of supercoiling. This topic is,
however, beyond the scope of the current article.
If the genome is the relevant target for cell sterilization,
and the genome is assumed to be randomly distributed
throughout the cell nucleus, then the magnitude of energy
deposition within the cell nucleus appears to be an appropriate choice for the target dimensions with which to relate
cell toxicity. If some physical parameter of dose to the cell
nucleus can be related to the probability of cell death, and
this parameter obtained for all cells within the tissue of
interest, then a method should exist to calculate the fraction of cell survivors within a tumor following treatment
by a radiolabeled antibody. This is the goal of microdosimetry in RIT.
Although the use of energy deposition in the cell nucleus as the correlate for cell inactivation should be feasible
for a- and P-particle emitters, it may be inappropriate for
radionuclides which decay by electron capture or internal
conversion, e.g., iodine-125 These isotopes decay by the
induction of an inner shell vacancy in the atom. The process of electronic de-excitation of the atom results in the
emission of electrons, referred to as “Auger electrons” after their discoverer, Pierre Auger.’ Since filling one vacancy by an Auger process, results in two further vacancies, a cascade of Auger transitions ensues which persists
until all the vacancies have risen to the outermost atomic
orbitals. Therefore, an atom which decays by electron capture or internal conversion gives rise to several low energy
electrons (corresponding to the differences between the orbital electron binding energies). Such local clusters of low
energy Auger electrons at the decay site have been shown
to exhibit high LET-like toxicity, if the source decays
within 1 or 2 nm of the DNA molecule, but low LET
radiotoxicity at greater distances from the DNA target. 4,5
Under such circumstances radiation dose to the cell nucleus may be inadequate as a predictor of radiation toxicity, and determination of the energy deposition to the
DNA molecule may be necessary. Although studies have
been performed with 125I-radiolabeled antibody,’ this class
of radionuclide will not be discussed further in this paper.
The interested reader is referred to the literature.’
C. Criteria for the applicability of microdosimetry
The basic criterion for determining the necessity of
microdosimetry w a s e s t a b l i s h e d b y K e l l e r e r a n d
Chmelevsky. 1 0This principle states that the stochastic nature of energy deposition within the target should be taken
into account when the relative deviations of the local dose
from the mean in the target exceeds 20%. For a uniform
distribution of a long range β− source such as 90Y within the
tumor, even at doses as low as 1 cGy, the average number
of &particle traversals per cell nucleus is so great that the
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
536
concept of absorbed dose is entirely adequate. However, as
Kellerer noted, the requirement of microdosimetric techniques for α− particles is almost always necessary. For example, a spherical target of diameter 5 µm requires an
average dose of > 100 Gy for the use of the average dose to
be sanctioned. When the distribution of sources is nonuniform, as in radioimmunotherapy, microdosimetric analysis
may also be required for P-particle sources, if the fluctuation of target cell doses exceeds 20%.
D. Microdosimetric quantities
The most fundamental parameter in microdosimetry
is the energy deposition ε1 from a single event (track intersection) with a target volume. Given a specific irradiation geometry, target size and shape and particle type, the
entire probability distribution of energy deposits ƒ ( ε1)
within the target volume from single traversals is referred
to as a single event energy deposition spectrum. A more
commonly used quantity is the single event specific energy
z 1 . The quantity z 1 is the energy deposition ε1 divided by
the mass of the target volume m. The quantity z 1 has been
calculated and also measured, using a Rossi proportional
counter, for a number of radiations.” For high dose radiation fields, of concern for therapy, one is primarily interested in multiple event spectra, where the stochastics of
individual target hits is convoluted with the hit probability
distribution. The microdosimetric quantity, specific energy
z, used to denote the stochastic energy deposition per unit
mass from multiple track traversals is the microdosimetric
analog of absorbed dose. Indeed the frequency mean (z F )
of a multiple event specific energy spectrum f(z) is under
most circumstances equal to the absorbed dose. However,
identical zF’s resulting from differing specific energy spectra do not imply equitoxicity. This notion is of immense
importance for radioimmunotherapy, since microdosimetry can predict widely differing tissue toxicities resulting
from identical average tissue doses.
E. The scope of microdosimetry
Although traditional microdosimetry from its inception by Rossi and colleagues places emphasis on the stochastics of energy deposition primarily at low doses, in this
paper a broader usage of the term has been employed to
cover all studies which investigate the deposition of energy
within small target, in particular cell nuclear volumes.
II. METHODS
There are multiple factors which influence the distribution of energy deposition within the sensitive target of the
tumor cells: the energy and type of emission, the geometric
relation between the source and target distributions, the
kinetics of the radiolabeled antibody uptake, redistribution
and clearance from the tumor tissue. For example, radiolabeled antibody may be distributed within the interstitial
fluid surrounding the cell; on the surface of the cell; or
taken up and retained within the cytoplasm or nucleus
following antibody internalization. The full threedimensional distribution of activity as a function of time is
537
Humm et al.: Microdosimetric concepts In radioimmunotherapy
required for the exact evaluation of a microdosimetric
spectrum. Such spectra have been calculated from theoretical distributions.12-15
The theory of Rossi and colleagues1 has been used for
the analytical determination of microdosimetric spectra for
several external radiation fields. The technique involves obtaining the single event spectrum for the type of radiation
in the target volume. The advantage of this method is that
the single event spectrum needs only to be calculated once.
The two event spectrum is the convolution of two single
event spectra. The three event spectrum is given by the
convolution of a two event spectrum and a single event
spectrum, and so on. By summation of these multiple convolutions the multiple event energy deposition spectrum is
obtained. Roesch expanded this theory to internal emitters,
and obtained analytical solutions for a number of nonuniform distributions of 239Pu particles in tissue.16 Single event
spectra for 2 3 9Pu a-particles were determined by Monte
Carlo methods, and from proportional counter
measurements.” Using Fourier or Laplace transform
methods to combine single event spectra, specific energy
spectra can be evaluated for several geometries very rapidly. Fisher applied the work of Roesch to evaluate microdosimetric spectra for a-emitting radiolabeled antibodies
over a broad class of irradiation geometries. 1 2
An alternative approach is the point dose summation
methods by Monte Carlo or other methods. A distribution
of sources (which may be located extracellular, on the cell
surface, or intracellular) may be simulated, or obtained
from digitized images of autoradiographs. 18,19 Each source
decay is simulated, an energy and direction of the emission
chosen. For a-particles the tracks are assumed to be
straight. If the line intersects a biological target, the specific energy z deposited is determined by
where m is the target mass, dE/dx the energy deposited
per unit track length, t l and t2 are the entrance and exit
coordinates of the track through the target. If the track
ends in the target, t2 is the coordinate of the end of range
of the particle. If a track begins in the target, t 1 is zero.
The total distribution of specific energy f(z) for the
cellular targets represents a complete description of the
physical dose deposition throughout the target volume.
These physical data can be combined with a biological cell
inactivation model to estimate the fraction of cell survivors. Such inactivation models evaluate the fraction of cell
survivors within each energy deposition bin and then perform a weighted sum of these surviving fractions over the
cell populations. 13-15,20
The acquisition of such data from tissue specimens is
severely limited in practice. For the treatment of malignant
ascites, where the targeted disease may consist of individual free floating cells within the peritoneal cavity, such
data may be obtainable by in-vitro assay. Small biopsy samples may be retrievable, for example from colorectal malignancies by sigmoidoscopy. Autoradiographic analysis
from histological sections prepared from biopsies enables
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
537
the investigator to obtain a detailed picture of a piece of the
tumor microcosmos. The usefulness of such data will depend upon how representative the specimen proves to be of
the tumor bulk left remaining. A major limitation of the
autoradiographic technique is the loss of temporal information. An autoradiograph is a “freeze frame” of the activity distribution in a slice of tissue at the time of specimen
fixation. Techniques to adjust autoradiographic grain density data for the redistribution of radiolabeled antibody as
a function of time have been proposed by Griffith et al 21 In
this method micro-thermoluminescent dosimeters (200
×400×5000 µm3 ) are inserted into the tumor tissue to
obtain cumulative dose data within a small tumor volume
which enables the normalization of grain densities across
each section. This technique may be of considerable power
when considering doses averaged over voxels of several
hundred to thousand micrometer dimensions. It encounters problems when the requirements of source and target
resolution approach those of cellular dimensions, since the
TLD integrates indiscriminately the energy deposition
from all sources within range of the crystal (for P-sources,
possibly several millimeters). Thus the fluctuation of dose
to individual cells within each voxel over time cannot be
dealt with by this approach.
The existence of a time variant nonuniform source distribution gives rise to a formidable microdosimetric problem. Success of the therapy depends upon tumor eradication. Tumor eradication depends upon the sterilization of
most or possibly all clonogenic tumor cells, which necessitates the adequate deposition of dose to each and every
clonogenic tumor cell. Nonuniformity of radiolabeled antibody distribution can lead to two sets of opposing consequences.
Penetration of the antibody into tumor tissue may result
in antibody collecting in pools as a result of heterogeneity
of antigen expression and interstitial fluid flow gradients.
The patchy appearance of radiolabeled antibody distribution (apparent from autoradiographs) results in a continual undulation of dose through the tumor. The magnitudes
of the dose maxima and minima depend upon the spatial
separation of the sources and the range of the radionuclide
emissions. The mean dose can be quite different from the
actual dose deposited to the individual tumor cell nuclei,
and therefore not a good predictor of biological response.
For example, partial radiolabeled antibody localization in
the tumor results in split tumor doses, some regions receiving radiation doses greater than the average tumor dose,
and others less. Normalized to the same energy deposition
in the tumor, heterogeneity of radiolabel distribution commonly results in lower cellular toxicity than when the radiolabels are uniformly distributed.2 2
Certain conditions of nonuniformity of source distribution can result in a higher level of cell killing than a uniform distribution. If the sources carried by the antibody
selectively localize on cell surface antigens of some or all
tumor cells, then these cells can receive much higher doses
than the average tissue dose. The antigen expressing tumor
cells act to concentrate the radioactivity at the target sites.
The magnitude of the dose to cell nuclei from radiolabeled
Humm et al.: Microdosimetric concepts in radioimmunotherapy
FIG. 1. Schematic diagram of a two source distributions within tissue (a)
a uniform distribution of sources, and (b) a uniform distribution of
sources on the cell membrane. Although the average tissue doses resulting
from these two source distributions can be identical, the mean dose (specific energy) to the cell nuclei can b-e very different.
sources bound to cell surface antigen relative to the average
tissue dose depends on two factors: ( 1) the average range
of the prevalent dose contributing emission, and (2) the
intercellular spacing between the cells. The first factor is
determined by the choice of radionuclide. The second depends on the tumor histology.
If tumor cell inactivation is plotted against average tumor dose, then the effect of radiolabeled antibody binding
to cell surface antigen is to steepen the cell survival curve.
This phenomenon has been observed with in-vitro systems
for both α− emitters 2 3’ 24 and β− emitters. 25 This enhanced
cell kill will persist over the range of the survival curve
governed by the fraction of tumor cells expressing accessible antigen. For example, if a radiolabeled antibody binds
to the cell surface antigen of 75% of the tumor cell population, then enhanced tumor cell killing results with dose
levels necessary to reduce the fraction of tumor cell survivors to 0.25. At this level of survival, a sharp decrease in
the survival slope occurs, as if the cell population consisted
of two cell lines of differing radiation sensitivities. Another
example illustrating the effect of source distribution on biological response curves is given in Humm 13 where theoretical survival curves are compared for a uniform distribution of 2 1 1At in a tumor versus a distribution restricted
to the blood capillaries. A source distribution restricted to
the capillaries results in a concave survival curve when
surviving fraction is plotted against average tumor absorbed dose. This is due to the gradient of cell inactivation
rate as a function of distance from the capillary wall, which
with escalating radiation dose, produces an “overkill” to
the cells aligning the capillary wall and inadequate energy
deposition for the sterilization of cells distant from the
capillary.
The ratio of a mean cell nuclear specific energy resulting
from source decays on the target cell surface membrane,
z bound , relative to a uniform distribution of source decays,
z uniform (see Fig. 1) will determine the magnitude of the
enhanced cell killing. The ratio z b o u n d/ zu n i f o r m h a s b e e n
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
538
called a “geometric enhancement factor G. ,,26,27 Calculated
values for the geometric enhancement ratio are given for
four sources proposed for RIT: 2 1 1 At, 1 9 9 Au, 1 3 1 I, and
90
Y under random (lymphoma-like) and tubular (colon
carcinoma-like) cell arrangements.” For an a-emitter
such as 2 1 1At, under random cell packing conditions, the
value of G can be enormous, ranging from approx. 1 when
the cells are in contact to 70 for a mean inter-nuclear distance between adjacent cells of 100 µm. For the long range
β− source 9 0Y (mean range 3960 µm), the geometric enhancement values for mean inter-nuclear distances of: 10,
20, 50, and 100 µm, are 1.00, 1.034, 1.16, and 2.26. This
means, a sparsely populated tumor mass (100-µm mean
cell separation) to which an q-labeled antibody binds
100% to cell surface antigen of all cells deposits a dose to
the tumor cell nuclei which is 2.26 times greater than if the
same activity of q-labeled antibody is uniformly distributed. These theoretical estimates of G depend on ideal conditions of 100% uniform binding of the antibody across the
entire cell population. The magnitude of killing enhancement from antibody binding is unlikely to be so great with
in-vivo studies. Actual experimental data estimates of the
magnitude of G for given cell separations and antibody
binding fractions are not yet available, although enhancements of cell killing efficacy resulting from antibody binding for in-vitro studies have been reported. 23-25
Radiation dose calculations have been performed for a
number of several low energy electron emitting radionuclides appropriate for RIT by Jungermann et al. 28 at cellular dimensions, using the electron point kernels of
Berger. Similar calculations have been performed by Sastry
et al. 29 who concluded, in agreement with Jungermann,
that soft electron sources of energies 20-30 keV, with
ranges just sufficient to traverse the cell, e.g., 119Sb, deliver
the optimal tumor cell dose per decay relative to nontumor
cells. Howell30 has performed extensive calculations of the
dose rate for several electron energies and P-sources within
volumes from individual cells to multicellular clusters of
varying sizes for source distributions: on the cell surface, in
the cytoplasm, in the nucleus and uniform within the entire
cell. He concludes, that a detailed analysis of subcellular
distribution of dose is required for electron energies < 50
keV. For electron energies > 50 keV, the effect of subcellular source localization is diminished due to the diffusion
of energy over the multicellular matrix.
Whether the optimal sources for RIT (a- and low energy B-emitters) discussed above can be of clinical utility
will depend on the ability to design targeting molecules
which are sufficiently uniform to irradiate the entire tumor
cell population.
Microdosimetric models for the calculation of dose gradients around nonuniform source distributions have been
developed by several groups. These studies take some nonuniform distribution of sources, e.g., a diffusion gradient of
activity from an initial spherical radioactive seed of radius
r, and show absorbed dose as a function of position relative
to the activity distribution. 31 These are distributions of absorbed dose and not of the fluctuation of dose (specific
energy) at the cellular level. Therefore, although such
539
Humm et al.: Microdosimetric concepts in radioimmunotherapy
studies do not belong to the traditional realm of microdosimetry, which is concerned with stochastic fluctuations in
dose, they can be considered to belong to the broader classification of microdosimetry. Roeske et al. 32 have modeled
the dose to tumor from an intraperitoneal administration
of therapeutic levels of 9 0Y, 1 3 1 I, and 2 1 1 At labeled antibody. Isodose contours are calculated for assumed rectangular and hemispherical lesions in and on the peritoneal
wall and also to small biopsy specimens of ovarian metastases. Activity is assumed to localize on the tumor surface, to diffuse into the peritoneal wall setting up an exponential activity gradient or to be uniformly distributed
through the tumor. Further works which have concentrated on the evaluation of dose distribution through tumor
from non-uniform deposition of P-sources are: Kwok
et al.,31 Langmuir and Sutherland,33 and Howell et al.3 4
III. MICRODOSIMETRIC SPECTRA
Two methods are currently employed for the calculation
of microdosimetric spectra for internal radionuclides: the
Fourier convolution technique developed by Roesch 16 and
applied to problems with radiolabeled antibodies by
Fisher, 12 and the application of full Monte Carlo simulation by Humm13 and by Roeske.14 Examples of specific
energy spectra calculated by both methods are illustrated
in Figs. 2 and 3.
Figure 2 is a specific energy spectrum calculated by the
Fourier convolution method for a population of tightly
packed cells, diameter 8 µm, nuclear diameter 5 µm, uniformly labeled on the cell surface, after the complete decay
of 3.7×104 Bq/g of 2 1 1 At with 2 1 1 Po daughter. The mean
specific energy to the nucleus is 158 cGy, and the fraction
of cell nuclei receiving zero dose (delta) is 0.17.
Figure 3 is an a-particle hit and specific energy spectrum calculated by the Monte Carlo method for a uniform
7 . 4 × 1 04 Bq/g extra-cellular distribution of 2 1 1At labeled
antibody with 25 radiolabeled antibodies bound per cell
surface. The cell and cell nuclear diameters are 10 µm and
7.5 µm, respectively.
These are only two examples of many different types of
calculations that are possible, and are presented here to
show the level of information that can be obtained from
microdosimetric assessments. It is important to reemphasize that the shape of microdosimetric spectra depends on a number of parameters: the shape and size of the
target volume, the geometry of the source distribution relative to the targets, the energy emission spectrum of the
radionuclide, etc. For example, for a-particle sources appended to the cell membrane in which the cells are far
apart, the Bragg peak does not contribute to the specific
energy spectrum (the target nucleus is always traversed by
the initial portion of the a-track). If the cells are in close
proximity, large energy deposition events resulting from
the ends of a-particle track falling over adjacent cell nuclei
increase the breadth of the specific energy spectrum.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
539
540
Humm et al.: Microdosimetric concepts in radioimmunotherapy
IV. CONCLUSIONS
The application of microdosimetry to RIT is the pursuit
of the accurate determination of the distribution of dose to
individual tumor cell nuclei comprising the viable tumor
mass. These data form the basis for a more accurate evaluation of tumor toxicity. Radiation toxicity which is estimated on the basis of a single average dose is practical, but
perhaps only a first approximation to the true assessment
of tissue toxicity. How accurate tumor response relations
can be based on average tumor radiation doses is not
known. The usefulness of average radiation doses to predict the level of tumor cell inactivation will most certainly
depend on the antibody/tumor model investigated. However, one may ask whether microdosimetry offers true advantages over traditional dosimetric methods? If the question is “does microdosimetry assist our understanding of
the radiobiology of antibody targeted therapy, and will it
lead to improved dose-response relations,” the answer is
most definitely in the affirmative. If the question refers to
the clinical utility of microdosimetry, then the answer is a
reserved yes. Information on the spatial distribution of radionuclide in tumor biopsy samples will assist the clinician
to make judgements on how well and how uniform his
radiolabeled antibody is localizing in tumor tissue. The
disadvantage of microdosimetry, at the cellular level, is the
size of specimen and the amount of data which can be
measured and analyzed. In practice one is limited to the
evaluation of a few tissue sections from a biopsy specimen
which may be far less than 1% of the tumor mass. The
fulfillment of the objective of determining the energy deposition for all viable tumor cells in a patient belongs to the
very distant future.
One compromise between microdosimetry and macrodosimetry, is the evaluation of radiation doses within tissue
voxels one or more orders of magnitude greater than individual cellular dimensions.*’ This technique evaluates the
response to cell clusters. If only the activity levels vary
between voxels, and not the spatial relationship of the
sources to cells, then the evaluation of cell kill on a voxel
by voxel basis is an elegant method of data reduction. The
accuracy in predicting dose-response between this method
and a full microdosimetric method is not known. Certainly, if the greater accuracy of microdosimetry for
β− sources proves superfluous, then its necessity in the field
might be restricted to α− and Auger-emitting radionuclides
only. But until this is proven, study of the microdosimetry
of all radionuclides of possible application in RIT needs to
be rigorously investigated.
ACKNOWLEDGMENTS
One of the authors (J. L. Humm) was supported by
NCI Grant No. lR03 CA50886. Many thanks to Virginia
Langmuir from SRI International, Menlo Park, California,
and Ken Kase from the University of Massachusetts Medical Center for their useful remarks and critical appraisal of
the manuscript.
1
H. H. Rossi, “Microscopic energy distributions in irradiated matter,”
in Radiation Dosimetry, edited by F. H. Attix, W. C. Roesch, and E.
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
540
Tochlin (Academic, New York, 1968), Vol. I, pp. 43-92.
D.T. Goodhead, “Relationship of microdosimetric techniques to applications in biological systems, ” in The Dosimetry of Ionizing Radiation. edited by K. R. Kase, B. E. Bjarngard, and F. H. Attix (Academic, Orlando, 1987), Vol. II, pp. l-89.
3
T. R. Munro, “The relative radiosensitivity of the nucleus and cytoplasm of the chinese hamster fibroblasts,” Radiat. Res. 42, 451-470
(1970).
4
A. I. Kassis, R. W. Howell, K. S. R. Sastry, and S. J. Adelstein,
“Positional effects of Auger decays in mammalian cells in culture,” in
DNA Damage by Auger Emitters, edited by K. F. Baverstock and D. E.
Charlton (Taylor & Francis, London, 1988), pp. l-13.
5
K. G. Hofer. “Radiation biology and potential therapeutic applications
of radionuclides,” Bull Cancer (Paris) 67, 343-353 (1980).
6
R. B. Painter, “The role of DNA damage and repair in cell kill induced
by ionizing radiation,” in Radiation Biology of Cancer Research, edited
by R. E. Meyn and H. R. Withers (Raven, New York, 1980), pp.
59-68.
7
P. Auger. “Sur les rayons β secondaires produit dans un gaz par des
rayons X,” Comptes Rendus 180, 65-68 ( 1925).
8
D. V. Woo, D. Li. J. A. Mattis, and Z. Steplewski, "Selective chromosomal damage and cytotoxicity of I-125-labeled monoclonal antibody
17-l-A in human cancer cells," Cancer Res. 49, 2952-2958 (1989).
9
J. L. Humm and D. E. Charlton, “A new calculation method to assess
the therapeutic potential of Auger electron emission,” Int. J. Radiat.
Oncol. Biol. Phys. 17, 351-360 (1989).
10
A. M. Kellerer and D. Chmelevsky, “Criteria for the applicability of
LET,” Radiat. Res. 63, 226-234 (1975).
11
ICRU Report 36, “Microdosimetry,” International Commission on
Radiation Units and Measurements. Bethesda, Maryland, 1983.
12
D. R. Fisher, “The Microdosimetry of monoclonal antibodies labeled
with alpha particles,” 4th Int. Symp. Radiopharm. Dosim. Symp.,
CONF-851113: pp. 446-457, edited by A. T. Schlafke-Stelson and E.
E. Watson (Oak Ridge, Tennessee, 1986).
13
J. L. Humm “A microdosimetric model of astatine-211 labeled antibodies for radioimmunotherapy.” Int. J. Radiat. Oncol. Biol. Phys. 13,
1767-1773 (1987).
14
J. C. Roeske, G. T. Y. Chen, R. A. Atcher, J. Fang, M. Becket, and R.
R. Weiselbaum, “A microdosimetric analysis of cell survival curves
from irradiation of SQ-20B cells to bismuth labeled monoclonal antibody 425,” J. Nut. Med. 31, 788 (abstract) (1990).
15
D. E. Charlton and R. Sephton, “A relationship between microdosimetric spectra and cell survival for high-LET irradiation,” Int. J. Radiat.
Biol. 59, 447-457 (1991).
16
W. C. Roesch, “Microdosimetry of internal sources,” Radiat. Res. 70,
494-510 (1977).
17
W. A. Glass and L. A. Braby, “A wall-less detector for measuring
energy deposition spectra,” Radiat. Res. 39, 230-240 (1969).
18
T. E. Hui, D. R. Fisher, O. W. Press, J. F. Eary, J. N. Weinstein, C. C.
Badger, and I. D. Bernstein, “Localized beta dosimetry of I-131-labeled
antibodies in follicular lymphoma,” Med. Phys. 19, 97-104 (1992).
19
P. L. Roberson, R. K. Ten Haken, D. L. McShan, P. E. McKeever, and
W. D. Ensminger, “Three dimensional tumor dosimetry for hepatic
yttrium-90-microsphere therapy,” J. Nucl. Med. 33, 735-738 (1992).
20
V. P. Bond, M. N. Varma, C. A. Sondhaus, and L. E. Feinendegen,
“An alternative to absorbed dose, quality and RBE at low exposure,”
Radiat. Res. Suppl. 104, S52-257 (1985).
21
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Ncacy, “Direct dose conformation of quantitative autoradiography
with micro-TLD measurements for radioimmunotherapy,” J. Nucl.
Med. 29, 1795-1809 (1988).
22
E. D. Yorke, B. W. Wessels, and E. W. Bradley, “Dose averages and
dose heterogeneities in radioimmunotherapy,” Antib. Immunoconj.
Radiopharm. 4, 623-630 (1991).
23
R. W. Kozak, R. W. Atcher, O. A. Gansow, A. M. Friedman, J. J.
Hines, and T. A. Waldmann, “Bismuth-212-labeled anti-Tat monoclonal antibody: a-particle emitting radionuclides as modalities for radioimmunotherapy,” Proc. Natl. Acad. Sci. USA 83, 474-478 (1986).
24
R. M. Macklis, B. M. Kinsey, A. I. Kassis, J. L. M. Ferrara, R. W.
Atcher. J. J. Hines, C. N. Coleman, S. J. Adelstein, and S. J. Burakoff,
“Radioimmunotherapy with alpha-particle-emitting immunoconjugates.” Science 240, 1024-1026 (1988).
25
F. S. Gaedicke, J. L. Humm, C. C. Lau, R. M. Macklis, G. Bastert, and
R. C. Knapp, “Analysis of cytotoxicity of I-131-labeled OC125 F(ab’)s
2
541
Humm et al.: Microdosimetric concepts In radioimmunotherapy
on human epithelial ovarian cancer ceil lines,” Radiother. Oncol. 23,
150-159 (1992).
J. L. Humm and L. M. Cobb, “Nonuniformity of tumor dose in radioimmunotherapy,” J. Nucl. Med. 31, 75-83 (1990).
27
J. L. Humm, L. M. Chin, L. M. Cobb, and R. Begent, “Microdosimetry in radioimmunotherapy,” Radiat. Prot. Dosim. 31, 433-436
(1990).
28
J. A. Jungermann, K. H. P. Yu, and C. I. Zanelli, “Radiation absorbed
dose estimates at the cellular level for some electron-emitting radionuelides for radioimmunotherapy,” Int. J. Appl. Radiat. Isot. 35, 883-888
(1984).
29
K. S. R. Sastry, C. Haydock, A. M. Basha, and D. V. Rao, “Electron
dosimetry for radioimmunotherapy: Optimal electron energy,” Radiat.
Prot. Dosim. 13, 249-252 (1985).
30
R. W. Howell, D. V. Rao, and C. Haydock, “Dosimetry techniques for
therapeutic applications of incorporated radionuclides,” in Dosimetry
26
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
541
of Administered Radionuclides, edited by S. J. Adelstein, A. I. Kassis,
and R. W. Burt (The American College of Nuclear Physicians, U. S.
Department of Energy, 1990), pp. 215-252.
“C. S. Kwok. W. V. Prestwich. and B. C. Wilson, “Calculation of radiation doses for nonuniformly distributed β and γ radionuciides in soft
tissue,” Med. Phys. 12, 405-414 (1985).
32
J. C. Roeske, G. T. Y. Chen, R. A. Atcher. C. Pelizzari, J. Rotmensch,
D. Haraf, A. Montag, and R. Weichselbaum, “Modeling of dose to
tumor and normal tissue from intraperitoneal radioimmunotherapy
with alpha and beta emitters,” Int. J. Radiat. Oncol. Biol. Phys. 19,
1539-1548 (1990).
33
V. K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 (1988).
34
R. W. Howell, D. V. Rao, and K. S. R. Sastry, “Macroscopic dosimetry for radioimmunotherapy: Nonuniform activity distributions in
solid tumors,” Med. Phys. 16, 66-74 ( 1989).
Multicellular dosimetry for beta-emitting radionuclides: Autoradiography,
thermoluminescent dosimetry and three-dimensional dose calculations
E. D. Yorke
George Washington University Medical Center, Washington. DC 20037
L. E. Williams and A. J. Demidecki
City of Hope Medical Center, Duarte, California 91010
D. B. Heidorn and P. L. Roberson
University of Michigan Medical School, Ann Arbor, Michigan 48109
B. W. Wessels
George Washington University Medical Center, Washington, DC 20037
(Received 18 March 1992; accepted for publication 23 November 1992)
Inhomogeneities in activity distributions over distances from 10 to 10 4µm are observed in many
tumors treated with radiolabeled antibodies. Resulting nonuniformities in absorbed dose may
have consequences for the efficacy of radioimmunotherapy. Activity variations may be directly
studied with quantitative autoradiography (ARG). Converting these data to absorbed dose
distributions requires additional information about pharmacokinetics, the use of a point source
function and consideration of the complete three-dimensional activity distribution, as obtained
from sequential autoradiographic slices. Thermoluminescent dosimetry with specially prepared
C a S O 4 :Dy dosimeters implanted into tissue can directly measure absorbed dose in selected
regions. The conditions under which thermoluminescent dosimeters (TLD) are used differ
markedly from “normal” use conditions in external beam radiotherapy. Therefore special calibration and quality assurance precautions are needed to assure the precision of this technique.
Procedures and pitfalls in the use of both techniques in radioimmunotherapy are described.
I. INTRODUCTION
A major concern of external beam radiotherapy is the design of beam configurations which produce a uniform dose
distribution over the tumor volume. In radioimmunotherapy, (RIT) as with other radiopharmaceutical therapies,
the activity distribution is determined by biological factors
with large associated uncertainty. Nonuniform distributions of activity and of absorbed dose may result.
The technique of autoradiography (ARG) is well
known.’ For over a decade ARG has been used to demonstrate activity heterogeneity on the multicellular size scale
( 1 0 - 1 0 4 µm) for conventional radiopharmaceuticals?”
and more recently for radiolabeled antibodies 5-7 The film
density may be calibrated with standard activity samples,
leading to quantitative measurements of activity of distributions with submillimeter spatial resolution in the plane
of the tissue section.
Calculations of absorbed dose distributions for idealized
activity distributions of beta particle emitters demonstrate
that when the absorbed dose is delivered primarily by particulate radiation of short range, heterogeneous activity
distributions will lead to doses which are nonuniform on
approximately the same distance scale. 8-11 Autoradiography frequently reveals irregular activity distributions in
tumors. In such situations, calculations based upon geometrically simple shapes are of limited utility. Quantitative
ARG can provide the spatial activity distribution needed
to calculate instantaneous dose rate distributions. But this
543
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
technique cannot yield total absorbed dose distributions
without further assumptions. This is because absorbed dose
distributions are as much determined by pharmacokinetics
of antibody uptake and clearance as by the geometric distribution of activity. Autoradiography, however, shows
only a “freeze frame” of the activity distribution at the
time the tumor was resected and frozen.
Direct in vivo measurements of cumulative doses to tissues during RIT can be made using thermoluminescent
dosimeter(s) (TLD). This technique is well established in
medical and health physics.12,13 TLD materials used for
RIT beta dosimetry must meet some special criteria. The
physical size of the dosimeter should be small compared to
the average beta range (e.g., 0.4 mm for I-131) in order
that the dosimeter not perturb the dose distribution in its
vicinity. Small size is also necessary to assure good spatial
resolution and to avoid disruption of the tissues into which
they are implanted. The light output per unit absorbed
dose must be large enough to produce a useful signal despite the small volume of material. Additionally, since the
absorbed dose is delivered by a spectrum of beta particles,
it is necessary to choose a material whose thermoluminescent response is insensitive to beta energy for the radionuclide of interest. Using TLD that meet these criteria, large
variations in absorbed dose in association with autoradiographs which show strong activity heterogeneity have been
directly measured.’
ARG and thermoluminescent dosimetry are complementary techniques. ARG provides a wealth of “geo-
0094-2405/93/020543-08$01.20
© 1993 Am. Assoc. Phys. Med.
543
544
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
FIG. 1. Section autoradiographs from subcutaneous xenografts in athymic
nude mice taken one day post injection with I-131 labeled monoclonal
antibody. (a) LS174T human colon cancer with 300 µCi 17-1A monoclonal antibody; (b) Raji human Burkitt lymphoma xenograft with 100
µCi anti-B-1 pan-B-cell monoclonal antibody.
graphic” data relating to the activity distribution at a single instant of time. To proceed from a set of
autoradiographs to a dose distribution requires a pharmacokinetic model as well as an algorithm for adding the
contributions to the dose at a chosen point from all the
activity within range of that point. More than one tissue
slice must be considered even if the dose distribution in
only one slice is desired. The TLD crystal is an integrating
dosimeter. It performs the necessary spatial and temporal
integrations, but only within the very limited volume that
it occupies. Methods and questions relating to both these
techniques, as well as possible fruitful ways to combine
them are discussed in the following sections.
II. AUTORADIOGRAPHY
Autoradiography (ARG) is a unique method for the
graphical display of activity heterogeneity on the multicellular size scale of particular interest in RIT with medium
to high energy beta particles. Although detectors other
than film are being investigated, 14,15 the discussion below is
limited to film ARG.
Typically, the tissue sample of interest is frozen in liquid
nitrogen and divided into sections of known thickness with
a microtome. The frozen sections are mounted, air dried
and then either placed in contact with the emulsion side of
the film or separated from it by a thin cover or dipped into
emulsion so that the specimen is covered with a thin emulsion layer. Exposure times must be chosen to avoid either
underexposing or saturating the film and thus will depend
on the sample activity, the radionuclide and the film used.
Times from 1 h to approximately a week have been used.
Example autoradiographs are shown in Fig. 1.
Although homogenous activity distributions are seen in
many tissue samples, they are not universally observed.
Numerous workers have reported heterogeneous uptake of
radiolabeled antibody in tumors.5-7,16,17 Some patterns of
uptake commonly seen include concentration of activity
near the periphery of the tumor and near tumor vasculature.
Medical Physics. Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
544
T O use ARG to quantitate activity distributions, it is
necessary to choose film that will be sensitive to beta particles of medium to high energy. Intensifying screens will
degrade resolution and may cause reciprocity failure’ but
may be necessary with some films. They were not used in
Refs. 7 and 16 (LKB “Ultrofilm”) but were used in Ref.
17 (X-OMAT XTL-2). The exposure time for each autoradiograph should be recorded.
Conversion of optical density to activity requires calibration of the film using gel wafers of known thickness and
known uniform activity. The calibration curve depends on
radionuclide, section thickness, exposure conditions, film
development conditions, and (if reciprocity failure is
present) exposure rate. An independent calibration check
should be performed for each group of autoradiographs.
The calibration gels are left in contact with film for known
times under the same exposure conditions as used for the
tissue samples. Development conditions should be the
same for calibration and autoradiographic films. A calibration curve of optical density as a function of cumulated
specific activity of the gel is thus generated. The curve can
be used to find the average cumulated specific activity for a
small volume of interest of the autoradiographic tissue
sample. If the calibration gels and the tissue slices are of
different thickness, a correction factor should be applied.’
The correction factor may be measured using gel samples
of different thicknesses. Since the autoradiograph exposure
time is known and physical decay of the radionuclide is the
only process causing activity changes during autoradiography, the specific activity at the beginning of autoradiography can be determined.
With an optical density scan of the film, a map of the
specific activity distribution over a grid of voxels can be
generated. The densitometer readout resolution (spot size)
should be small to help minimize the change in optical
density over the aperture. Because the optical density varies with the logarithm of the light transmittance, the densitometer reading will not reflect the average optical density if there is a large gradient over the spot size diameter.”
Automated approaches to grain density determination
techniques with higher spatial resolution are being
explored. 1 9 The volume of a voxel is determined by the
readout grid spacing and the slice thickness. The twodimensional section images are stacked to yield a threedimensional activity density matrix and can also be used to
form a surface description.
Video digitization or laser densitometry techniques are
useful in dealing in a quantitative fashion with the abundant data provided by ARG. For example, with 100-µm
resolution of the densitometer and 50-µm-thick adjacent
tissue slices, a set of autoradiographs of a 5×5×5 mm
tumor provides information on the specific activity in
2.5×10 5 voxels.
The specific activity distribution can be used to calculate
a three dimensional absorbed dose rate distribution. An
example is shown in Fig. 2. Using the activity per voxel to
calculate dose rate distributions is computationally intensive. The dose rate at a point is the sum of contributions
from all the voxels lying within the maximum beta range.
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
FIG. 2. Three-dimensional dose rate distributions for tumor xenografts
from Fig. 1. The color scale is black, dark blue, light blue, pink, light
green, dark green, light peach, dark peach, dark red, red, orange in equal
ascending dose-rate intervals. Higher dose rate regions cycle back to
black, dark blue, etc. (a) LS174T human colon cancer with 17-1A monoclonal antibody, dose-rate interval 2.5 cGy/h, mean dose rate 7.6 cGy/h;
(b) Raji human Burkitt lymphoma xenograft with anti-B-1 pan-B-cell
monoclonal antibody, dose-rate interval 0.4 cGy/h, mean dose rate 2.4
cGy/h.
This includes voxels both in and out of the autoradiographic slice containing the point of interest. A suitable
point source function must be used to provide the distance
dependence appropriate to the radionuclide. 20-23 Roberson
et al.17 adapted brachytherapy software to perform this
task. A “voxel dose rate distribution” per unit activity was
generated using up to 500 equally spaced point sources
distributed over a voxel and the dose point kernel of Ref.
21. This voxel dose rate calculation was carried out beyond
the range of the beta particles. Each of 5000 to 8000 voxel
positions (0.5-mm voxel spacing for I-131) were assigned
the voxel dose rate distribution, weighted by the specific
activity in that voxel. The source distributions were then
summed in three dimensions. The calculation time investment (100-200 h on a VAX 8800) limited the number of
source positions which could be used. Based on the mean
beta range, the optimal voxel size for I-131 is approximately 100 µm, which increases the number of source
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
545
points by a factor of 125. To reduce the calculation time,
Fourier transforms could be used. 9
In general, activity distributions which vary over distances comparable to the beta particle range will produce
dose-rate distributions which vary strongly over the same
length scale. Smaller scale (less than beta range) activity
heterogeneities will produce less dramatic dose rate variations, since the dose at a point is delivered by beta particles
from both “hot” and “cold” portions of the tissue. 7-11,17,24
Thus computational effort to produce three-dimensional
dose or dose rate distributions depends on the range of the
beta particles and the tumor size.
Conversion of the activity distributions obtained by
ARG to the cumulative absorbed dose distribution produced during the administration of RIT-that is, during
the time that the tissue was in a living host-is not
straightforward. The dose distribution depends on the individualized pharmacokinetics of the radiolabeled antibody
in vivo. The autoradiograph provides only a “freeze frame”
view of the activity distribution at the time of tumor resection. At best ARG gives indirect information about the
time dependence of the biological processes of uptake and
clearance of the antibody during the RIT.
To provide the necessary missing kinetic information, it
might be possible to model the pharmacokinetics. Diffusion model equations have been applied to dosimetry calculations for multicellular spheroids 25 and simulated tumor nodules.26 It may be possible to extend such models to
tumors in vivo to provide kinetic input to cumulated dose
distribution calculations.
In an alternative approach many groups have measured
average specific activity as a function of time for tumors
and various organs by noninvasive imaging techniques in
humans and by serial sacrifice in small animal models for a
variety of antibody carrier/radionuclide combinations. 27-30
Assumptions must then be made as to how small scale
heterogeneities vary with time (e.g., do “hot” and “cold”
regions remain in the same ratio to the average throughout
RIT?). The resulting time dependence must be combined
with the radionuclide’s physical decay to obtain a model
cumulated activity distribution based on the autoradiographic information. While several groups have discussed
such a program, it has not yet been carried out. Griffith,
et al.7 used purely physical decay to generate dose distributions from autoradiographs. Recently Roberson,
et al. 17,24 generated three-dimensional dose rate distributions characteristic of discrete times of sacrifice and recommended sampling the dose rate distributions at a minimum of four to six time points. 24 For tumors which were
approximately matched in size, the variability in dose per
volume element was observed to be small compared to the
variability at different time points. Thus it might be possible to sum dose rate calculations from different tumors,
resected at different time points, by identifying areas of
similar composition (e.g., similar vascularization and/or
proximity to the periphery). Further work is needed to
develop and validate models of antibody carrier pharmacokinetics on the multicellular size scale in order to reliably translate the activity distributions visualized with
546
Yorks et al.: Multicellular dosimetry for beta-emitting radionuclides
quantitative autoradiography into absorbed dose distributions.
III. THERMOLUMINESCENT DOSIMETRY
Studies done with thermoluminescent dosimetry give information which is complementary to that provided by
ARG. TLD materials are crystalline solids in which ionizing radiation can excite electrons into metastable trapped
states. The number of such electrons is proportional to the
absorbed dose received. The electrons can be released from
these states by heating. Thereupon they recombine with
holes, giving off excess energy in the form of thermoluminescent photons, which can be counted with a photoelectric tube. The light output is proportional to the absorbed
dose received by the TLD but also depends on material
properties, irradiation conditions, heating conditions, and
the electronics of the TLD reader. Therefore, if thermoluminescent dosimeters are to be used for absorbed dose
measurements, they must be calibrated.
Appropriately calibrated TLD implanted directly into
tissue yields the total dose absorbed by the TLD material
during its time in situ. The TLD automatically integrates
over the spatial and temporal distribution of all the activity
within the beta particle range of its location (and, of
course, also accounts for the absorbed dose contributed by
penetrating radiation from distant sites). However, the
dose in only a small volume is recorded, as opposed to the
global activity distribution information provided by ARG.
The conditions under which TLD are used in RIT dosimetry differ markedly from those in health physics or
radiation therapy. This leads to special requirements in the
fabrication and calibration of the dosimeters. As noted in
the Introduction, the TLD must be of small cross section
compared to the beta particle range. Wessels and coworkers found that CaSO4 :Dy met the dual requirements
of high sensitivity (light output gm -1 c G y- 1) and weak
energy dependence for I-131 and higher energy beta
emitters. 31 They and others7,27,32-39 have fabricated TLDs
of dimensions 0.2×0.4×5 mm or less, implanted them
into animals or tumor model systems receiving RIT and
performed in vivo absorbed dose measurements. Techniques of fabrication, quality assurance, calibration and in
vivo use of these TLDs were developed by Wessels and
Griffith. 7,31 Similar procedures have been adopted at approximately 15 institutions including those involved in
Refs. 32-39. In the following discussion, CaSO 4:Dy dosimeters are emphasized because of their extensive application
in RIT dosimetry.
The starting materials are 400-µm-thick 1.2-cmdiameter CaS04 :Dy impregnated teflon disks (Teledyne,
Inc.). The disks are imbedded in a 2x2 cm paraffin block
and sliced with a well-sharpened tissue section microtome
to a thickness of 200 µm and a length of 500 µm, yielding
dosimeters of final dimensions 0.2x0.4x5 mm. These dosimeters conveniently fit inside a 20-gauge needle. Each
dosimeter is measured (by micrometer) to insure geometric batch uniformity (±3%). For initial studies 31 the dosimeters were also weighed using a microgram balance.
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
546
After being cut, the excess paraffin is removed and the
TLD are annealed. External beam calibration may be performed using a calibrated low megavoltage (4 MV or Co60) beam with full buildup. The dosimeters are then read
in a commercial TLD reader under dry nitrogen. Different
groups have used slightly different heat cycle settings (e.g.,
Ref. 7 uses a 5-s preheat at 115° followed by glow peak
integration over 50 s from 115°C to 275°C with temperature ramping at 3.6°C/s). Batches of “mini-TLD” with
response uniformity better than ±10% are readily obtained.
Linearity of light output (LO) versus dose should be
measured with external beam over the entire range of absorbed doses expected in RIT (5 to 5000 cGy). Deviation
of a log-log plot of LO versus absorbed dose from a 45° line
indicates supralinearity or saturation. Supralinearity has
been reported above 500 cGy by some workers 36,40 but not
seen up to 1000 cGy by others. 29 This effect may depend on
the batch of material or on preparation techniques. Supralinearity can be appreciable. Demidecki and co-workers
have seen an increase by a factor of 1.7 of the LO per cGy
or calibration factor as absorbed dose is increased from 50
to 3000 cGy. 40,41 Therefore it is essential to use a measured
dose-response curve and not to assume that the calibration
factor is independent of dose.
External beam exposures are of short (minutes) duration, after which the TLD material is stored in air at room
temperature and usually read out within 1-2 days. In RIT
applications, the TLD is imbedded in tissue at mammalian
body temperature and physiological pH. The tissue contains an activity distribution of beta-emitting radionuclide,
exposing the TLD to low dose rate (approximately 10
cGy/hr) beta and gamma radiation for times ranging from
a few days to two weeks. Upon removal, the TLD must be
cleaned of residual tissue before being read. The TLD is a
relative dosimeter; absorbed dose in an investigational situation is determined by the ratio of the LO to the output
from a similar (or the same) TLD given a known dose.
Additional calibration should therefore be performed under conditions which closely resemble the conditions of
actual use, as the calibration factor may well depend on
these conditions.
For this purpose the TLD are cross calibrated with uniform activity distributions of the radionuclide of interest.
The dosimeters are immersed for times ranging from minutes to 2 weeks in gels (e.g., Knox Gelatin) prepared with
known uniform activity. After removal from the gel, each
dosimeter must be thoroughly washed and then read on the
TLD reader. The calibration medium is large compared to
the beta range so the absorbed dose to the medium can be
calculated via the beta particle equilibrium dose constant
and an absorbed fraction of one. If the TLD are to be used
under conditions where the penetrating radiation dose is
expected to be important, calibration in a larger phantom
or with an added external x-ray irradiation might be advisable to obtain a combined calibration factor.
The radionuclide calibration factor may well be different from the standard external x-ray beam factor. Reference 31 reports the same (15%) factor for 4 MV as for
547
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
I-131, Y-90 and P-32 gels. However, in later work from the
same laboratory, I-131 calibration factors as low as 60% of
the 4-MV factor were measured and a calibration factor of
approximately 70% was measured for a smaller (0.1 X0.14
X2.5 mm) set of TLD.39 Heidorn observed a similar (approximately 40%) discrepancy between Co-60 and I-131. 42
Stewart et al.43 saw similar differences between 4-Mev electrons and I-131 solutions using 6×1×1 mm Lif rods while
Y-90 solution data coincided with 4-Mev electrons.
There are at least three reasons for expecting a difference in calibration factor between external megavoltage
x-rays and beta particle irradiation in solution or gel.
( 1) The LO of the TLD may have intrinsic energy dependence. This may be checked using external irradiation
at different nominal electron beam energies or with beta
sources. At least part of this effect is due to the thickness of
the TLD relative to the beta particle range in TLD
material. 4 4 Demidecki, et al. find that for Y-90, the energy
dependence is within 10% for mini-TLD. 4 1
(2) In radioactive gel or solution, the finite size of the
TLD excludes radioactive material from points within its
volume. Demidecki, et al. have called this the “void volume” effect.20,41 The absence of radioactivity reduces the
absorbed dose to the TLD. Demidecki et al. have performed calculations of this effect for Y-90 and I-131. The
dose reduction depends on the TLD density as well as its
size (i.e., on the beta particle range versus TLD size).
Calculations 41 indicate that especially for I-131, the predicted decrease in calibration factor relative to 4-MV
x-rays is substantial.
(3) The LO of the TLD also varies with time in the
medium. When the TLD are irradiated with external beam
and stored in air at room temperature, they show less than
5% fading per month. However, for irradiation in medium
over days to weeks, the fading properties depend upon the
medium (e.g., temperature and pH) as well as the time in
the medium and the total dose. The surface to volume ratio
of the TLD material probably plays a role; the effect may
also depend on the batch of material purchased from the
vendor.
Experiments performed by Wessels and co-workers
from 1984 to 1988 with one group of TLD material showed
no fading for TLD irradiated in aqueous media 31 at room
temperature. However, experiments with newer material
by Demidecki and collaborators,41 and Svenberg45 s h o w
fading by a factor of up to 50% in 20 days for mini-TLD
irradiated in Y-90 gel for 20 days. The effect is larger for
geometries with a larger surface to volume ratio. For a
6-mm diameter, 20-µm-thick CaSO 4 :Dy disk, Demidecki
et al40,41 report an approximately exponential decrease in
LO with time by a factor of five over 20 days in cell medium and by a factor of 10 for the same time in gel. This
fading appears to be irreversible. After the TLD has been
cleaned, read, and annealed it does not regain its initial
sensitivity.
Since it is not presently possible to theoretically account
for these effects, it is necessary to calibrate the dosimeters
for in vivo RIT dosimetry using conditions as close as possible to those under which they are used. This will miniMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
547
mize the impact of pH, temperature and the “void volume”
effect and will help account for possible interplay between
supralinearity and fading.
The mini-TLD can be implanted into animal models
undergoing RIT and left in place for days to several weeks.
They can also be implanted into animals receiving external
beam (e.g., 4 MV) irradiation to a known dose as a check
on the effect of biological conditions on the thermoluminescent response. A recent study reports fading under
these circumstances.4 6 Mini-TLD have also been extensively checked for signs of degradation due to biological
conditions.’ None were seen. Before reading a TLD which
has been implanted in tissue it is important that it be carefully cleaned and dried.
In RIT, the mini-TLD yield an average (over the length
of the dosimeter) dose to the nearby surrounding tissue.
Agreement with average doses calculated from organ or
tumor-average cumulated activities obtained by serial sacrifice of similarly treated animal models is generally
good. 27,33,34 These calculations have incorporated boundary corrections as necessary for organs or tumors which
are small compared to the beta particle range. Activity
heterogeneity within the tissue is not included. In this
work, possible fading due to time in aqueous medium, pH,
temperature and “void volume” effects have been corrected
for, at least in part, by appropriate calibration.
The mini-TLD have good spatial resolution for dose
gradients along their thin (0.2 and 0.4 mm) dimensions.
However the LO depends on the summed dose along the
long (5 mm) axis. Steep dose gradients were measured in
cylindrical phantoms containing I-131, Y-90, and P-32. 3 1
The spatial resolution along the 5-mm axis can be extracted by slicing the dosimeter. This is the technique
which was applied in conjunction with autoradiography.’
The tissue sample containing the TLD was quickly frozen
in liquid nitrogen. The frozen tissue was then microtomed
into sections (e.g., 20-50 µm) appropriate for autoradiography, with the slices being approximately perpendicular
to the long TLD axis. The resulting micro-TLD chips were
removed, cleaned, air dried, and read in the same reader
and with the same heat cycle as is used for the mini-TLD.
The uniformity of response of the micro-TLD was investigated by Wessels and Griffith 31 and by Heidorn et al..47
and by Langmuir et al..3 9 Mini-TLD were exposed to calibrated external beams under standard conditions. The dosimeters were then imbedded in suitable solid medium and
microtomed as described above. Micro-TLD were selected
at random from these samples and read. A standard deviation of 10% was observed in Ref. 31 while a standard
deviation ranging from 22% to 32% was reported in the
study Ref. 47, and a standard deviation of 29% (for 50-µm
sections) and 50% for 30-µm sections was reported in Ref.
39. The reason for the very different dispersions measured
by different investigators is not, at present, understood but
may be related to differences in TLD grain size. Heidom 4 7
using a dissection microscope at 50X magnification, observed differences in grain size distribution between microTLD batches. Some micro-TLD contained large CaS0 4:Dy
crystals, some had large voids due to crystals pulled from
540
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
the Teflon matrix by the microtome knife and some had a
uniform distribution of small crystals. In general, slice
thickness must be carefully regulated to improve light output uniformity.
There is no predictive index to determine the uniformity
of response of a group of micro-TLD. However precision
can be optimized by individually calibrating each microTLD as described by Heidorn, et al. 47 Through use of individual calibration factors, standard deviations of 12%
were achieved in measurement of a known external beam
dose gradient.
IV. COMBINATION OF TECHNIQUES
When absorbed doses measured with micro-TLD extracted from autoradiographs were considered in the context of the optical density in the region from which the
TLD had been removed, qualitative agreement was observed between high absorbed dose and high optical density for tumors7 ’ 34 and spheroids.39 Good agreement was
found between micro-TLD measurements and calculated
dose gradients in a spheroid model 39 where physical decay
of I-131 provided the only time dependence. While such
agreement is self evident in situations where physical decay
provides the only time dependence, it is not assured in
tumors with more complex pharmacokinetics. Additionally, the micro-TLD provide the magnitude of the absorbed dose. The combined use of ARG and thermoluminescent dosimetry demonstrated quantitatively that large
absorbed dose gradients can be found in tumors treated
with RIT. In one sample’ a 200% dose variation was measured within a single slice and a 400% variation was observed between slices which were only 500 µm apart.
Since the micro-TLD integrate absorbed dose over time,
no biokinetic model is needed to calculate the dose at the
site of the TLD. Wessels et al. 48 have suggested that the
micro-TLD be used to calibrate the optical density of the
autoradiographs. That is, rather than associate optical density with specific activity, one could make a direct relationship between OD and absorbed dose via the micro-TLD.
Ideally, there should be several micro-TLD at sites in a
slice with different OD’s allowing an individualized calibration curve (OD versus dose measured by the TLD) to
be generated for a particular tissue sample. Since the TLD
integrates over the spatial as well as the temporal activity
distribution, there is also no need to use a point source
function or to correlate the activity distribution in different
slices. Instead, the OD would be translated directly to absorbed dose through the calibration curve. The accuracy of
this technique (which estimates the absorbed dose via interpolation between micro-TLD readings at two or three
points per slice) versus the pharmacokinetic modeling approach discussed previously requires further investigation.
The use of electronic probes such as MOSFET detectors 49
may be helpful in providing in vivo measurements of dose
versus time at a few locations in tissue.
Theoretically, both approaches have potential drawbacks and possible advantages. Autoradiography, by defiMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
548
nition, is a destructive process in relation to unique tumor
architecture. Modeling approaches used to correct autoradiographic information for time varying concentrations are
constrained to use average bulk tumor biodistribution data
or repetitive activity distribution phenomena (e.g., timevarying but predictable tumor rim enhancement) to correct for antibody pharmacokinetics and gross tumor heterogeneity. The combination TLD/ARG methods do
include a directly measured time integration factor in the
absorbed dose along with a dose distribution which is
based on ARC. However, some uncertainty is entered into
this method by assuming that the “local” assignment of an
absorbed dose value to a particular optical density value
applies universally throughout the tumor. Perhaps a safe
starting point or working hypothesis for both methods is
that any correction for time dependence of antibody pharmacokinetics is superior to simply using physical decay to
derive a cumulated activity distribution from autoradiography patterns.
V. DISCUSSION
The goal of the dosimetric studies presented above is to
help relate the therapy technique of RIT to the outcome
(e.g., tumor regression). ARG demonstrates that tumors
often exhibit activity distributions which are inhomogeneous on a distance scale of 10 - 10 4 µm. Both calculations
and in vivo TLD measurements show that these spatial
activity variations are associated with large dosimetric
variations on the same distance scales. The validity of approximating the tumor dose distribution by a single average absorbed dose may therefore be questioned.
In addition to spatial dosimetric inhomogeneities, other
factors may alter the biological effectiveness of the absorbed dose. Among these are the variation of the dose rate
with time and the possible relationship of cell viability to
local activity deposition. An understanding of the interrelationships between tumor pharmacokinetics and spatial
and temporal variations of dose rate and total dose deposition may be required for reliable prediction of the outcome of tumor therapy. However, a necessary step toward
this goal is improved quantitation of absorbed dose at the
multicellular level in tumors.
ACKNOWLEDGMENTS
This work was supported in part by NCI Grants No.
CA33572, CA43904 and CA44173.
1
A. W. Rogers, Techniques of Autoradiography (Elsevier/NorthHolland Biomedical, New York, 1979).
2
W. K. Sinclair, J. D. Abbatt, H. E. A. Farran, E. B. Harriss, and L. F.
Lamerton, “A quantitative autoradiographic study of radioiodine distribution and dosage in human thyroid glands,” Br. J. Radiol. 29,
36-41 (1950).
549
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
3
T. K. Lewellen. M. M. Graham, and A. M. Spence, “Quantitative
autoradiography using a personal computer,” J. Nucl. Med 27, 549554 (1986).
4
Y. Yonekura, A. B. Brill, P. Som, G. W. Bennett, and I. Fand, “Quantitative autoradiography with radiopharmaceuticals, part 1: Digital film
analysis system by videodensitometry: Concise Communication.” J.
Nucl. Med. 24, 231-237 (1983).
5
P. L. Jones, B. M. Gallagher, and H. Sands, “Autoradiographic analysis of monoclonal antibody distribution in human colon and breast
tumor xenografts,” Cancer Immunol. Immunother. 22, 134-143
(1986).
6
J. M. Esteban, J. Schlom, F. Momex, and D. Colcher, “Radioimmunotherapy of athymic mice bearing human colon carcinomas with monoclonal antibody B72.3: Histologic and autoradiographic study of effects on tumors and normal organs,” Eur. J. Cancer Clin. Oncol. 23,
643-655 (1987).
7
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
8
J. L. Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
9
C. S. Kwok, W. V. Prestwich, and B. C. Wilson, “Calculation of radiation doses for non uniformly distributed beta and gamma radionuclides in soft tissues,” Med. Phys. 12, 405-412 (1985).
10
V. K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 (1988).
11
R. W. Howell, D. V. Rao, and K. Sastry, “Macrodosimetry for radioimmunotherapy:Nonuniform activity distributions in solid tumors,”
Med. Phys. 16, 66-74 (1989).
12
Applied Thermoluminescence Dosimetry, edited by M. Oberhofer and
A. Scharmann (Adam Hilger Ltd. Bristol, 1981).
“Thermoluminescence and Thermoluminescent Dosimetry, Vols. I, II,
and III, edited by Y. L. Horowitz (CRC, Inc., Boca Raton, FL, 1984).
14
J. L. Humm, L. M. Chin, R. C. Lanza, C. M. Schaefer, M. Speidel, and
R. L. Greene, “Digital imaging for autoradiography,” in Computed
Digital Radiography in Clinical Practice edited by R. E. Greene and J.
W. Oestmann (Thieme Medical Publishers, Inc., New York, 1992). pp.
167-172.
15
R. Mayer, L. E. Dillehay, Y. Zhang, Y. Shao, S. Song, W. C. Lam, and
J. R. Williams, “New method for microdosimetry in radioimmunotherapy using GAF TM chromic media,” Antib. Immunoconj. Radiopharm. 5, 336 (1992).
16
R. L. Vessella, P. H. Lange, D. F. Palme, R. K. Chiou, M. K. Elson,
and B. W. Wessels, “Radioiodinated monoclonal antibodies in the imaging and treatment of human renal cell carcinoma xenografts in nude
mice,” in Antibody Mediated Delivery Systems, edited by J. D. Rodwell
(Marcel Dekker, Inc., NY, 1988), pp. 245-282.
17
P. L. Roberson, D. J. Buchsbaum, D. B. Heidom, and R. K. Ten
Haken, “Three-dimensional tumor dosimetry for I-131 labeled MoAb
using serial autoradiography,” Int. J. Radiat. Oncol. Biol. Phys. 24
329-334 (1992).
18
L. J. Van Battron and H. Huizenga, “Film dosimetry of clinical electron beams,” Int. J. Radiat. Oncol. Biol. Phys. 18, 69-76 (1990).
19
K. E. Eklund and J. R. Williams, “A method for quantitative autoradiography over stained sections of tumors exposed in vivo to radiolabeled antibodies,” Int. J. Radiat. Oncol. Biol. Phys. 21, 1635-1642
(1992).
20
R Locvinger, E. M. Japha, and G. L. Brownell, “Discrete radioisotope
sources,” in Radiation Dosimetry, edited by G. J. Hine and G. L. M.
Brownell (Academic,, NY, 1956), pp. 693-799.
21
W. V. Prestwich, J. Nunes, and C. S. Kwok, “Beta dose point kernels
for radionuclides of potential use in radioimmunotherapy,” J. Nucl.
Med. 30, 1036-1046 (1989).
22
P. K. Leichner, W. G. Hawkins, and N. C. Yang, “A generalized
empirical point source function for beta particle dosimetry,” Antib.
Immunoconj. Radiopharm. 2, 125-144 (1989).
23
P. K Leichner and C. S. Kwok, “Tumor dosimetry in radioimmunotherapy:Methods of calculation for beta particles,” Med. Phys. 20, 529534 (1993).
24
P. L. Roberson, D. J. Buchsbaum, D. B. Heidom, and R. K. Ten
Haken, “Variations in 3-D distributions of tumor uptake and dose
deposition for I-131 labeled MoAb,” Antib., Immunoconj. Radiopharm. 4, 43 (1991).
25
R. McFadden and C. S. Kwok, “Mathematical model of simultan-
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
549
eous diffusion and binding of antitumor antibodies in multicellular
human tumor spheroids,” Cancer Res. 48, 4032-4037 ( 1988).
K. Fujimori. D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “A
modeling analysis of monoclonal antibody percolation through tumors:
A binding site barrier,” J. Nucl. Med. 31, 1191-1198 ( 1990).
27
P. K. Leichner, N. C. Yang, B. W. Wessels, W. G. Hawkins, S. E.
Order, and J. L. Klein, “Dosimetry and treatment planning in radioimmunotherapy,” in The Present and Future Role of Monoclonal Antibodies in the Management of Cancer, edited by J. M. Vaeth and J. L.
Meyer (Karger, Basel, Switzerland, 1990), pp. 109-120.
28
D. G. Covell, J. Barbet, O. D. Holton, C. D. Black, R. J. Parker, and
J. N. Weinstein, “Pharmacokinetics of monoclonal immunoglobulin
G1, F (ab’)2 and Fab’ in mice,” Cancer Res. 46, 3969-3978 (1986).
29
J. A. Carrasquillo, P. Sugarbaker, D. Colcher, J. C. Reynolds, J. Esteban, G. Bryant, A. M. Keenan, P. Perentesis, K. Yokoyama, D. E.
Simpson, P. Ferroni, R. Farkas, J. Schlom, and S. M. Larson, “Radioimmunoscintigraphy of colon cancer with I-131 labeled B72.3 monoclonal antibody,” J. Nucl. Med. 29, 1022-1030 (1988).
30
F. Buchegger, A. Vacca, S. Carrel, M. Schreyer, and J-P. Mach, “Radioimmunotherapy of human colon carcinoma by I-131 labeled monoclonal anti CEA antibodies in a nude mouse model,” Int. J. Cancer 41,
127-134 (1988).
31
B. W Wessels and M. H. Griffith, “Miniature thermoluminescent dosimeter absorbed dose measurements in tumor phantom models,” J.
Nucl. Med. 27, 1308-1314 (1986).
32
B. W. Wessels, R. L. Vessella, D. F. Palme, J. M. Berkopec, G. K.
Smith, and E. W. Bradley, “Radiobiological comparison of external
beam irradiation and radioimmunotherapy in renal cell carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 17, 1257-1263 (1989).
33
J. L. Klein, T. H. Nguyen, P. Laroque, K. A. Kopher, J. R. Williams,
B. W. Wessels, L. E. Dillehay, J. Frincke, S. E. Order, and P. K.
Leichner, “Yttrium-90 and I-131 radioimmunoglobulin therapy of an
experimental human hepatoma,” Cancer Res. 49, 6383-6389 (1989).
34
J. A. Williams, B. W. Wessels, J. A. Edwards, K. A. Kopher, P. M.
Wanek, M. D. Wharam, S. E. Order, and J. L. Klein, “Targeting and
therapy of human glioma xenografts in vivo utilizing radiolabeled antibodies,” Cancer Res. (Suppl.) 50, 974s-979s (1990).
35
D. F. Palme, J. M. Berkopec, B. W. Wessels, M. K. Elson, P. H. Lange,
and R. L. Vessella, “Dosimetry and pharmacokinetics of monoclonal
antibody A6H with human renal cell carcinoma xenografts: Single dose
study,” Int. J. Nucl. Med. Biol. 18, 527-537 (1991).
36
R. Wessely. H. Bihl, E. Friedrich, and S. Matzku, “Assessment of
radiation dose distribution in xenografts,” in Monoclonal Antibodies:
Application in Clinical Oncology, edited by A. Epenetos (Chapman and
Hall Medical, NY, 1991), pp. 315-322.
37
R. K. Chiou, B. W. Wessels, M. Woodson, and C. Limas, “Study of
clinical thermoluminescent dosimeters (CL.TLD) in direct measurement of absorbed radiation dose for radioimmunotherapy,” Radiat.
Appl. Isot. 42, 181-186 (1991).
38
J. Y. C. Wong, L. E. Williams, A. J. Demidecki, B. W. Wessels, and X.
W. Yan, “Radiobiologic studies comparing yttrium-90 irradiation and
external beam irradiation in vitro,” Int. J. Radiat. Oncol. Biol. Phys.
20, 715-722 (1991).
39
V K. Langmuir, B. W. Wessels, H. L. Mendonca, E. D. Yorke, and L.
Montilla, “Comparisons of sectioned micro-tld dose measurements
with predicted dose from I-131 labeled antibody,” Med. Phys. 19,
1213-1218 (1992).
40
A. J. Demidecki, L. E. Williams, and J. Y. C. Wong, “Calibration of
thermoluminescent dosimeters for beta radiation,” Antib. Immunoconj. Radiopharm. 4, 52 (1991).
41
A. J. Demidecki, L. E. Williams, J. Y. C. Wong, B. W. Wessels, E. D.
Yorke, M. Strandh, and S. Strand, “Considerations on the calibration
of small thermoluminescent dosimeters (TLDs) used for measurement
of beta particle absorbed doses in liquid environments,” in press, Med.
Phys. (1993).
42
D. B. Heidom, personal communication.
43
J. S. W. Stewart, V. Hird, D. Snook, M. Sullivan, G. Hooker, N.
Courtenay-Luck, G. Sivdapenko, M. Griffiths, M. J. Meyers, H. E.
Lambert, A. J. Munro, and A. A. Epenetos, “Intraperitoneal radioimmunotherapy for ovarian cancer: Pharmacokinetics, toxicity and efficacy of I-131 labeled monoclonal antibodies,” Int. J. Radiat. Oncol.
Biol. Phys. 16, 405-413 (1989).
44
A. S. Pradhar and R. C. Bhatt, “Graphite mixed CaSo 4:Dy teflon TLD
discs for beta dosimetry,” Phys. Med. Biol. 22, 873-879 (1977).
45
A. Svenberg, personal communication.
26
550
Yorke et al.: Multicellular dosimetry for beta-emitting radionuclides
46
S-E Strand, A. Svenberg, M. Strandh, and K. Norrgren. “Parameters
affecting the accuracy of in vivo dosimetry with mini-TLD,” Med.
Phys. 19. 781 (1992).
47
B Heidorn, D. J. Buchsbaum. P. L. Roberson, and R. K. Ten
Haken, “A sensitivity study of micro-TLD’s for in vivo dosimetry of
radiolabeled antibodies,” Med. Phys. 18, 1195-1199 (1991).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
48
550
B. W. Wessels and E. D. Yorke. Biology of Radionuclide Therapy,
edited by G. L. DeNardo, J. P. Lewis, A. Raventos, and R, W. Burt
(ACNP Publication No. 308, Washington, DC, 1989). pp. 216-222.
49
D. J. Gladstone and L. M. Chin, “Automated data collection and
analysis system for MOSFET radiation detectors,” Med. Phys. 18,
542-548 (1991).
Experimental radioimmunotherapy
Donald J. Buchsbauma )
Department of Radiation Oncology, University of Alabama at Birmingham, Birmingham, Alabama 35233
Virginia K. Langmuir
Life Sciences Division, SRI International, Menlo Park, California 94025
Barry W. Wessels
Department of Radiology, George Washington University Medical Center, Washington, DC 20037
(Received 18 March 1992; accepted for publication 20 October 1992)
Radiolabeled monoclonal antibodies have been used for radioimmunotherapy studies with human tumor spheroids and murine and human tumor xenografts in experimental animals. This
paper reviews the work that has been performed in these models with different types of cancer,
and highlights those papers that have presented dosimetry estimates and attempts to correlate
the findings. Radioimmunotherapy studies in multicell spheroids, as a model for micrometastases, have been performed in human neuroblastoma, colon cancer, and melanoma cell lines
using 1 3 1 I-, 1 2 5 I-, 1 8 6 Re-, and 212Bi-labeled antibodies. The uniform geometry of the spheroid has
allowed radiation dose estimates to be made. Up to three logs of cell kill have been achieved with
131
1- and 186 Re-specific antibody with minimal toxicity from labeled nonspecific antibody, but
212
Bi-antibody had little effect because of its short half-life as shown by Langmuir. It appears
that the two most important factors for therapeutic efficacy in this model are good penetration
of the radiolabeled antibody and an adequate radionuclide half-life to allow penetration of the
immunoconjugate prior to significant radionuclide decay. Radioimmunotherapy studies in animals bearing transplants of colon cancer, leukemia, lymphoma, hepatoma, renal cell carcinoma,
neuroblastoma, glioma, mammary carcinoma, small cell lung carcinoma, cervical carcinoma,
ovarian carcinoma, and bladder cancer have been performed with 1 3 1I, 9 0Y, 1 8 6Re, 1 5 3Sm, and
177
Lu beta emitting, and 212Bi alpha emitting radionuclides conjugated to monoclonal antibodies.
A few studies compared different radionuclides in the same model system. The approaches that
have been used in these studies to estimate tumor dosimetry include the MIRD approach,
thermoluminescent dosimetry, autoradiography, and comparison to external irradiation. The
majority of investigators have estimated the dose to tumor and normal organs using MIRDbased calculations (time-activity curve and equilibrium dose constant method). The range of
tumor doses has been between 17 and 11 171 mGy/MBq of administered radioactivity. The
effectiveness of radiolabeled monoclonal antibody therapy depends on a number of factors
relating to the antibody such as specificity, affinity, and immunoreactivity. The density, location,
and heterogeneity of expression of tumor-associated antigen within tumors will affect the localization and therapeutic efficacy of radiolabeled antibodies, as will physiological factors such as
the tumor vascularity, blood flow, and permeability. These factors are discussed and examples
are presented. In the future, it is recommended that investigators make comparisons of different
radionuclides in the same system, which should include an analysis of the relative toxicity. It is
also recommended that comparisons to external beam radiation be made for both tumor and
normal tissue damage. It is also recommended that investigators look at radiation dose heterogeneity using thermoluminescent dosimeters and autoradiography, so that the range of tumor
radiation dose and dose-rate is reported. It is hoped that an answer to how heterogeneity in
radiolabeled antibody deposition in experimental tumors and spheroids affects absorbed dose
distribution and the radiobiological consequences will be understood. It is also hoped that a
definitive answer will be obtained for what radionuclides and forms of antibody are optimum for
radioimmunotherapy of leukemias, micrometastases, and solid tumors, and most importantly
how best to apply these techniques and information to the treatment of cancer clinically.
I. INTRODUCTION
Radiolabeled monoclonal antibodies (MoAbs) have been
used for radioimmunotherapy (RIT) of spheroids in vitro
and in a variety of murine syngeneic tumors and human
tumor xenografts in vivo A recent review of the animal
RIT literature by Wessels 1 will be updated and expanded
upon in this review. Those papers that have presented dosimetry estimates in experimental RIT studies are dis551
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
cussed, and the presentation is organized by tumor type.
The majority of the work has been with 131I- or 90Y-labeled
MoAbs and human tumor xenografts. There are a few
manuscripts available describing 1 8 6 Re-, 1 7 7 Lu-, and
153
Sm-labeled MoAb therapy in experimental animals. In
addition to these studies with beta emitting radionuclides,
alpha emitters ( 2 1 2Bi or 2 1 1 At) and the Auger emitter 1 2 5 I
have been investigated in experimental RIT studies. A dis-
0094-2405/93/020551-18$01.20
© 1993 Am. Assoc. Phys. Med.
551
552
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
cussion of the physical and chemical properties of these
radionuclides is presented in another manuscript in this
special issue.2
The approaches that have been taken to estimate tumor
dosimetry include the MIRD approach, thermoluminescent dosimetry, autoradiography, and comparison to external irradiation. Most authors have used MIRD infinite
media/equilibrium dose constant calculations, 3 but calculations for long range beta emitters (e.g., 9 0Y) in small
tumors (less than l-cm diameter) should use point source
calculations. 4 The comparison to the external irradiation
approach is reviewed in another section of this report by
Langmuir et al.5 It is hoped that these studies in experimental animal models and with spheroids will provide information useful to clinical RIT trials, such that better
therapeutic results with less toxicity will ultimately be obtained.
II. RESULTS OF PUBLISHED STUDIES
A. The multicell spheroid as a three-dimensional
model for RIT dosimetry research
Multicell spheroids have been used by several investigators to assess the efficacy of radiolabeled antibody
therapy. 6 - 1 5 Multicell spheroids are clusters of tumor cells
grown in vitro in spinner flasks which can grow to diameters of 1 mm or more. The cells become differentiated and
produce extracellular matrix. Gradients of oxygen and nutrient concentrations develop, thus mimicking what occurs
in vivo. The spheroid is therefore a useful in vitro threedimensional (3D) tumor model. Autoradiography of
spheroid sections can be used to evaluate the distribution
of radiolabeled compounds. Clonogenic assay of dissociated spheroid cells can be used to evaluate the toxicity of
various treatments. Because of the simple spherical geometry, more accurate dose estimates can be made than are
possible with in vivo tumors. 16-19 Because of the importance of delayed antibody penetration and radionuclide
cross-fire in RIT, an in vitro 3D tumor model can be very
useful, particularly as a model for tumor microregions and
for studies of radiobiological and dosimetric aspects of
RIT. Comparisons between different radionuclides can be
made as well as between different extents of radiolabeled
antibody penetration. 14,15 This model does not allow evaluation of the roles of normal host cells, the vasculature, or
pharmacokinetics.
The main problem in determining the dose-response relationship in RIT is the heterogeneity of radiolabeled antibody deposition. Because of this, tumor doses are generally reported as average doses over the whole tumor
volume, without differentiating between necrotic and viable regions. The response of the spheroid can be measured
using either clonogenic assay of cells from dissociated
spheroids or regrowth assays of intact spheroids. The average dose to the region of viable cells can be calculated
separately from the dose to the necrotic center resulting in
more meaningful dose estimates to the potentially viable
cell population. 10
In general, it is possible to reach higher radiation doseMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
552
rates and doses than are presently achievable with RIT in
vivo and a complete dose-response curve can be constructed using a uniform population of spheroids. End
points used have included regrowth delay, 7,9 proportion of
spheroids sterilized,’ and clonogenic assay of dissociated
spheroid cells.9-11 Using 131I-labeled anticarcinoembryonic
antigen (CEA) or 131I-labeled NR-LU-10, it has been possible to achieve up to 99.9% to 99.99% (3 to 4 log) cell kill
in 0.8 to 1.0 mm diameter LS174T human colon cancer
spheroids. 10,14,15 Calculated absorbed doses to the outer 0.2
mm of the spheroids, which contains the viable cells in
untreated spheroids, were 30 to 40 Gy at this level of cell
kill. Approximately 10% of the dose was from 1 3 1I in the
incubating medium. When 1 3 1I was compared with 1 8 6R e ,
similar doses produced similar toxicity. 14 For 1 3 1I, it was
shown that a more even distribution of radionuclide produced a higher absorbed dose and more cell kill. 15 Studies
using 212Bi-labeled NR-LU-10, which has a half-life of only
1 h, produced little cell kill in spheroids despite substantial
cell kill in monolayer cells.” This occurred because the
212
Bi decayed before there was significant penetration of
the immunoconjugate into the spheroids. Pretargeting with
a bifunctional antibody followed by administration of chelated 212 Bi may get around this problem, as well as the use
of longer half-life alpha emitters such as 2 1 2 Pb or 2 1 1 At.
Both of these solutions would allow higher tumor/normal
tissue (T/NT) ratios to be reached prior to full decay of
the radionuclide. Alpha emitters have the advantage of
high linear energy transfer (LET) which results in more
killing for a given radiation dose. However, normal tissues
would also receive this high LET radiation which once
again emphasizes the importance of high T/NT ratios
when alpha emitters are used. Bardies et al. 18 have predicted doses of up to 417 Gy with 153 Sm and 135 Gy with
9 in 0.2-mm-diam ovarian cancer spheroids based on
uptake data using “‘In-labeled OC125 F(ab’) 2 fragments.
B. Radioimmunotherapy of human colon cancer in
animal models
Goldenberg et al.2 0 evaluated RIT of GW-39 human
colonic carcinoma xenografts in the hamster cheek pouch
following administration of 131 I-labeled goat anticarcinoembryonic antigen (CEA) polyclonal antibody. With a
single injection of 37 MBq 131 I-labeled antibody, there was
marked tumor growth inhibition and an increase in animal
survival time compared to an equivalent radionuclide dose
of normal goat IgG. Radiation dose estimates to the tumor
using biodistribution data and the MIRD technique were
13 250 mGy to the tumor over a 20-day period from the
specific antibody, and 4111 mGy for the normal IgG, following the administration of 37 MBq of 131 I-labeled antibody. A summary of these and other results presented below are shown in Fig. 1 and Table I. Sharkey et al. 2 1
investigated the therapeutic efficacy of a single injection of
131
I-labeled NP-4 MoAb against CEA in hamsters bearing
the GW-39 tumor in the cheek pouch. A dose of 18.5 MBq
of 131 I-labeled NP-4 was able to reduce the growth rate of
4-day-old GW-39 tumors by 84% on day 14 after treatment compared to untreated controls. Thirty-seven MBq
553
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
of 1 3 1 I-labeled NP-4 had about the same percentage of
growth inhibition on day 14. At day 21, the percentage
growth inhibition of 4-day-old tumors compared to untreated controls produced by 18.5 MBq and 37 MBq of
131
I-labeled NP-4 was 92% and 79%, respectively. The
reason that the higher quantity of 131 I did not improve the
effect was that the control tumors grew to twice the size in
the higher dose experiment than in the lower dose experiment. The radiation dose to the tumor calculated using the
MIRD formalism was 11 960 mGy for 18.5 MBq
131
I-labeled NP-4 over a 14-day period.
Esteban et al.22 administered 11.1 MBq 1 3 1 I-labeled
B72.3 to nude mice bearing LS174T tumor xenografts.
They found no visible toxic effect in the mice with 11.1
M B q o f 1311-labeled B72.3, although 18.5 MBq of
131
I-labeled B72.3 showed greater inhibition of tumor
growth and produced toxic effects in the mice, including
early death. Zalcberg et al. 23 found that 37 MBq of
131
I-labeled 250-30.6 MoAb directed against an antigen
present on human colonic secretory epithelium inhibited
the growth of COLO 205 colon carcinoma xenografts in
nude mice, whereas a similar quantity of 131 I-labeled control MoAb or unlabeled specific antibody did not. They
calculated using the MIRD technique a radiation dose of
7000 mGy to the tumor following administration of 37
MBq of 131I-labeled 250-30.6 MoAb.
In the above described studies, some of the preparations
may have dehalogenated faster than others, especially if
they formed immune complexes with circulating antigen in
the vascular compartment, so that one must be careful
about the dose estimates reported.
One approach to dealing with the potential complexities
of decaying low dose rate irradiation in RIT, which was
suggested by Wessels and co-workers, 1,24,25 is to attempt to
express the effect on tumor growth of radiolabeled antibody treatment compared to external beam irradiation.
Buchsbaum et al. performed such a study comparing 6 0C o
irradiation to 131 I-labeled 17-1A treatment of LS174T human colon cancer xenografts in nude mice. 26 There was a
prolonged inhibition of growth produced by one or three
injections with 11.1 MBq 131 I-labeled 17-1A as compared
to untreated control animals and animals that received unlabeled 17-1A. The response that was achieved by the administration of 11.1 MBq of the 1 3 1I-labeled 17-1A antibody was similar to that produced by 6000 mGy 6 0C o
irradiation. A calibration curve was constructed which
plotted doubling time as a function of 60Co dose. Based on
this curve, three injections of 11.1 MBq of 1 3 1 I-labeled
17-1A was equal to 9200 mGy of 60Co irradiation and one
injection of 11.1 MBq of 131 I-labeled 17-1A was equal to
5000 mGy of 60Co irradiation. Finally, MIRD calculations
suggest that the dose to tumor following a single injection
of 131I-labeled 17-1A would be 19 060 mGy and all normal
tissue doses were less than 6500 mGy. This difference of
19 060 mGy and 9200 mGy 60Co irradiation results at least
partially from the low-dose rate effect, as described in the
manuscript on “Radiobiology of radiolabeled antibody
therapy as applied to tumor dosimetry” contained in this
report. 5 In another study, Buchsbaum et al. found that
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
131
553
I-labeled chimeric IgG1 17-1A MoAb, following a single
i.p. injection of 11.1 MBq, produced tumor growth inhibition comparable to that of multiple doses of 1 3 1I-labeled
murine 17-1A.27 Neacy et al. compared the LS174T tumor
volume doubling time in athymic nude mice treated with
131
I-labeled B72.3 MoAb and single fraction 4-MV external
x-ray radiation and found the therapeutic efficacy of both
types of irradiation to be similar with a relative efficacy
factor of 0.8-1.0.28 Griffith et al29 compared theoretical
absorbed dose calculations to measured micro-TLD values
in LS 174T tumors growing in athymic nude mice injected
with 7.4 MBq 131 I-labeled B72.3. There was good agreement between the two methods, 8100 mGy measured to
8240 mGy calculated per 7.4 MBq injected.
Three-dimensional dose distributions have been developed for LS174T human colon cancer xenografts in athymic nude mice injected with 131 I-labeled 17-1A MoAb.30,31
The activity distributions were determined using autoradiographs of serial sections. Tumors removed one and four
days postinjection were analyzed. The dosimetry calculations used a point dose kernel for 1 3 1 I, modified for the
finite extent of the activity-distribution voxels. The 3D
dose distributions were obtained by summing the contribu-
554
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
554
555
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
tions from each voxel. Dose rates at one day postinjection
of 11.1 MBq of 1 3 1I-labeled 17-1A MoAb were 50-150
mGy/h at the surface of the tumor, decreasing to nearly
zero in the interior. At four days postinjection, the surface
dose ranged between 40-100 mGy/h and was approximately half of this dose in the interior. Additional information is reported elsewhere. 30,31
An important issue in maximizing the effectiveness of
131
I-labeled MoAb therapy concerns the relative benefit of
intact antibodies versus F(ab’)2 fragments. This issue has
been addressed by Buchegger et al. 32 using a cocktail of
four 131 I-labeled antibodies reactive with distinct epitopes
of CEA. Although both forms of MoAbs had efficacy, fragments were more effective at producing growth delay of
T380 human colon carcinoma xenografts than intact MoAbs. In addition, only fragments appeared to produce long
term tumor remission. Compared to fragments, intact
MoAb caused more toxicity, such as weight loss and depression of peripheral white blood cells. This was true despite the fact that a much higher dose of radioactivity was
given with fragments (92.5 MBq administered in 3 injections) than with intact MoAb (18.5 MBq administered in
2 injections). These findings were consistent with the
MIRD calculations which showed that, for the same dose
delivered to the tumor, fragments delivered less dose to
most normal tissues, with the exception of kidneys, stomach, and intestine. The radiation dose to kidney was 26%
higher with fragments as compared to intact antibodies.
Most importantly the whole-body dose with F(ab’) 2 fragments was 4400 mGy, compared to 6600 mGy with the use
of intact MoAb. Based on these results, and others that
were previously published, 33,34 these investigators feel that
fragments will have a lower uptake in marrow and liver,
and will lead to a higher T/NT ratio, and therefore a better
therapeutic index.
Other investigators have reported that the use of antibody fragments has resulted in higher T/NT ratios and
greater therapeutic efficacy than intact MoAbs. 33,35 T h e
rationale for the use of antibody fragments [F(ab’) 2 , Fab,
or Fv3 6] is that the smaller antibody molecule has more
rapid penetration through the tumor vasculature into the
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
555
extravascular space where ‘it can bind to tumor cells with a
more homogeneous distribution, and more rapid catabolism from both blood and normal tissues than intact antibody. These differences would produce a higher T/NT ratio than intact MoAbs. However, most preparations of
antibody fragments have a lower affinity than the corresponding intact MoAbs, and in both preclinical and clinical studies, MoAb fragments have had a shorter biological
half-life in tumor than intact MoAbs and a higher relative
uptake in kidneys, which could result in renal toxicity.
In studies of dose fractionation with 131 I-labeled intact
MoAbs, multiple administrations have been found to produce prolonged tumor growth inhibition and less toxicity
than single administrations.26,27 ’ 3 7
Although 1 3 1I-labeled MoAbs have produced regressions and potential cures in colon cancer xenograft models,
several findings suggest that there may be advantages to
employing a radionuclide with more energetic emissions.
First, not all cells synthesize antigen. In addition, all tumor
sites do not have adequate vascularization. The experimental findings clearly demonstrate nonuniform binding. The
best studied example of a radionuclide that has been utilized for this purpose is 9 0Y. It is a pure beta emitter with
a 64-h half-life and an intermediate beta energy (2.3-MeV
maximum). The results using v-labeled MoAbs for treatment are presented below. In these studies, 90Y labeling has
been accomplished with different chelates, resulting in different stabilities of the radiolabeled antibodies. These differences are important, because they affect the uptake and
retention of 9 0Y in the tumor and the bone, since this radionuclide is a bone-seeker. Thus, with the use of less stable chelates there would be a greater loss of 9 0Y from the
antibody resulting in a lower radiation dose to the tumor
with increased toxicity to the host. In addition, the molar
substitution ratio of chelate to antibody has been shown to
be an important parameter affecting both immunoreactivity of the antibody and uptake in tumor and normal organs. Thus the results presented need to be interpreted
with caution, and one must be very careful in drawing
conclusions.
Washburn and others have used 90Y-labeled 17-1A pre-
556
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
pared with cyclic DTPA as the chelate or the more stable
p - N H2 -Bz-DTPA chelate to treat nude mice bearing
SW948 human colon cancer xenografts. 38 After injection
with unlabeled 17-IA, the tumors continually increased in
size. In animals receiving 7.4 MBq 90Y-labeled 17-1A prepared with cyclic DTPA, tumor volume was unchanged
from base line. As the quantity of v-labeled 17-1A increased from 3.7 to 7.4 MBq, the rate of tumor growth
decreased, but all experimental animals died between 14
and 21 days after treatment. In contrast, 7.4 MBq
90
Y-labeled 17-1A prepared with p-NH2 -Bz-DTPA produced a maximum tumor volume reduction of 87% by day
15, and no deaths were noted for 71 days after treatment.
Dose-response curves again showed increased tumoricidal
effects with increased quantities of 90Y-labeled 17-IA. Using the MIRD approach, a radiation dose to tumor of
33 400 or 41 600 mGy was calculated for 7.4 MBq
90
Y-labeled 17-1A administered with each of these chelates, respectively. 39 In another study, 40 groups of athymic
nude mice bearing SW 948 xenografts were injected with
5.55 or 7.4 MBq 9 0Y-labeled 17-1A MoAb prepared with
the stable p-NH2 -Bz-Mx-DTPA chelate. At 49 and 125
days after the first injection, the treatment group receiving
7.4 MBq was reinjected with 5.55 MBq of 90Y-labeled 171A. There were no deaths from treatment in this group.
The reduction in the initial tumor size reached nadirs of
96% at 39 days, 88% at 74 days, and 44% at 147 days.
The treatment group receiving 5.55 MBq was reinjected
with 7.4 MBq 9 0Y-labeled 17-1A at 49 days after the first
injection. There was a maximum reduction in the initial
tumor size of 85% at 21 days, but all the animals in this
group died within 17 to 21 days after reinjection at 49 days,
probably due to hematopoietic death.
Sharkey et al.4 1 reported that 1.85 MBq of 9 0Y-labeled
NP-2 anti-CEA MoAb conjugated with cyclic DTPA inhibited growth of the GW-39 tumor in athymic mice by
77% as compared to control animals given 1.85 MBq
v-labeled irrelevant MoAb at 21 days after injection. The
estimated radiation dose to the tumor using the MIRD
formulation was 16 030 mGy after 1.85 MBq 9 0Y-labeled
NP-2 administration over a 14-day period. Doses to lungs,
kidneys, and liver were 5730, 5960, and 7420 mGy, respectively. Buras and colleagues have performed a similar
study with s.c. LS174T solid tumor xenografts of colon
cancer. 42 As was the case with 17-1A and NP-2, while
unlabeled antibody had no affect on tumor growth,
y-labeled ZCE025 (anti-CEA antibody conjugated with
a proprietary bifunctional chelating agent) arrested tumors
for 2 to 3 weeks. They performed a series of MIRD calculations to estimate the dose to the tumor and normal tissues produced by specific and nonspecific MoAbs. There
was no correction for the small tumor volume and the
deposition of a fraction of the beta particle energy outside
the tumor. The tumor was calculated to receive 34 000
mGy with the administration of 4.44 MBq 9 0Y-labeled
anti-CEA antibody as compared to 14 000 mGy with the
nonspecific antibody. However, some normal tissues received potentially significant doses as well. For instance,
the liver dose was calculated to be 37 000 mGy compared
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
556
to 18000 mGy with a control antibody against melanoma.
With regard to spleen, they calculated similar degrees of
dose of 29 000 mGy with the specific antibody, 27000
mGy with the nonspecific antibody, and the dose to kidney
was similar with 17000 mGy with the specific antibody
and 16000 mGy with the nonspecific antibody. In a more
recent study, Buras et al. corrected for the loss of beta
particle energy outside the tumor and normal organs and
estimated that the tumor dose from a single 4.44 MBq
administration of 9 0Y-labeled ZCE025 was 17500 mGy. 4 3
In another study by the same group of investigators it was
shown that interferon increased the amount of CEA expression in tumors by a factor of 6.9. In animals treated
with interferon, there was enhanced localization of
90
Y-labeled ZCE025 (using a stable benzyl DTPA chelate)
in WiDr human colon cancer xenografts by a factor of
2.4. 4 4 T h e d o s e t o t u m o r p r o d u c e d b y 4 . 4 4 M B q
90
Y-labeled ZCE025 increased from 12 170 mGy in animals treated without interferon to 24 770 mGy in animals
treated with interferon.4 4
Another therapeutic approach that has been studied in a
nude mouse xenograft system has been to give multiple
administrations of low quantities (between 1.48 and 5.55
MBq) of 9 0Y-labeled antibody prepared using the GYKDTPA chelate. However, tumors regrow as soon as the
injections are stopped. 4 5
In a preliminary experiment on 9 0Y-labeled 17-1A tumor growth inhibition, groups of 8 mice each were injected
i.p. with 0, 5.55, 9.25, 12.95, and 16.65 MBq of 90Y-labeled
17-1A prepared using the p-NH2 - M x - D T P A s t a b l e
chelate. 4 6 There was tumor growth inhibition produced
which was proportional to the quantity of 9 0Y - l a b e l e d
17-1A administered. The toxicity (decrease in peripheral
white blood cells and death of animals) of the q-labeled
antibody treatments was proportional to dose. The results
of a comparison of the tumor growth inhibition produced
by 131 I- and 9 0Y-labeled 17-1A indicate that similar tumor
growth inhibition was produced by 9.25 MBq 9 0Y- and
5.55 MBq 1 3 1 I-labeled 17-1A. In this study, 9.25 MBq
90
Y-labeled 17-1A MoAb was estimated to deliver 17 900
mGy to the tumor based on MIRD calculations. However,
9.25 MBq 90Y-labeled 17-1A showed considerably greater
toxicity in terms of decreased peripheral white blood cells
and animal deaths than 5.55 MBq 1 3 1I-labeled 17-1A
MoAb, which was estimated to deliver 9530 mGy to the
tumor by MIRD calculations. Higher doses of 131 I-labeled
17-1A (14.8 and 18.5 MBq) produced greater tumor
growth inhibition without toxicity. The differences in tumor growth inhibition were in part due to a lower degree of
tumor localization of the 9 0Y-labeled antibody, and because about 25% of the 90Y dose was deposited outside the
tumor as determined by 3D dose distributions calculated
using autoradiography data.
Sharkey et a1.47 conducted biodistribution studies with
131
I- and 9 0Y-labeled (using the ITC-Bz-Mx-DTPA stable
chelate) intact NP-4 anti-CEA MoAb and fragments in
nude mice bearing human colonic tumor xenografts. Radiation dose estimates derived from these studies suggest that
the maximum tolerated dose of 1 3 1I-labeled intact MoAb
557
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
would deliver a greater dose to a small tumor than
v-labeled intact antibody, principally due to the increased toxicity of ?-labeled antibody brought on by the
higher and prolonged retention of 9 0Y in the normal organs, especially bone. It was concluded that 9 0Y-labeled
MoAb fragments would not be useful due to the higher
doses to the kidneys than to the tumor, but that
“‘I-labeled fragments administered in a fractionated regimen might have an advantage over multiple treatments
with 131 I-labeled intact antibody due to less bone marrow
toxicity.
One of the chief stumbling blocks in achieving cures
using radiolabeled MoAb therapy is that hematologic toxicity limits the dose that can be delivered. Two potential
methods of increasing the dose of labeled antibody that can
be delivered are through the use of autologous bone marrow transplantation (ABMT) and colony stimulating
factors. 48-51 The potential role of ABMT in colon cancer
was assessed by Morton and colleagues. 48 In their studies
using nude mouse xenografts, they found that 4.44 MBq of
90
Y-labeled anti-CEA antibody (prepared with a proprietary bifunctional chelating agent) alone produced a median survival of 45 days. This represented an increase from
31 or 35 days, which was observed in the control group and
in those receiving nonspecific antibody, respectively.
Higher doses of antibody could be tolerated only if ABMT
was performed. This allowed administration of up to 8.325
MBq of anti-CEA antibody, which increased median survival to 63 days.
An alternative to bone marrow transplantation which
may allow dose escalation of RIT includes the use of radioprotective agents. Interleukin-1 (IL-1) is the most studied hematopoietic growth factor with regard to radioprotection. It, as well as other hematopoietic stimulatory
factors, has a radioprotective effect on bone marrow progenitor cells in vitro when given before, during, or shortly
after acute external radiation exposure. 51,52 In mice, the
protective effect has been greater when given 24 h prior to
as opposed to after sublethal or lethal doses of
radiation. 53-57 IL-1 stimulates growth of pluripotent hematopoietic cells.58 In mice, survival was increased most by
administering 100-1000 ng 20 h before lethal radiation
compared to 4 or 45 h prior to radiation. 53,54 Some radioprotective effect resulted from l-5 µg doses given up to 3 h
after radiation but not at longer time intervals 54-57 Initial
testing of IL-l in conjunction with RIT has been carried
o u t b y B l u m e n t h a l e t a l5 0 T h e y s h o w e d t h a t t h e
131
I-labeled antibody induced decline in circulating white
blood cells in hamsters could be prevented by a single injection of IL-l 20 h prior to radiolabeled antibody injection, or reversed by IL-l injection 7 days after “‘I-labeled
antibody administration. Thrombocytopenia has been the
dose limiting toxicity in most clinical RIT trials. IL-l has
not been shown to be effective in stimulating the growth of
megakaryocytes. The adjunctive use of IL-l and other
growth factors that stimulate megakaryocyte proliferation
may allow the use of higher doses of radiolabeled MoAbs
due to their protective effect on bone marrow stem cells or
the accelerated proliferation of cells surviving RIT.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
557
Another approach to enhancing the efficacy of RIT is to
target cells not well targeted by the antibody. Hypoxic cells
are in this category as they are generally at a distance from
blood vessels. Hypoxic cells are also relatively radioresistant decreasing even further the effectiveness of RIT. Misonidazole, an hypoxic cell radiosensitizer, has been evaluated in combination with 1 3 1 I - l a b e l e d a n t i - C E A i n
LS174T human colon cancer xenografts. 59 They found that
the addition of misonidazole resulted in significant prolongation of tumor growth inhibition as compared to the radiolabeled antibody alone. SR 4233, a benzotriazine hypoxic cytotoxin, has been used in the same tumor model in
combination with 1311-labeled NR-LU-10 and tumor
growth delay was significantly prolonged. 60 It was estimated that the combined treatment produced 10 times
more cell kill than radiolabeled antibody alone. The application of hypoxic cell sensitizers in clinical studies with
external beam radiation has been disappointing, which has
been attributed largely to the fact that doses were limited
to inadequate levels because of toxicity. New sensitizers
have been synthesized that are less toxic, and these are
being evaluated in clinical trials.
C. Radioimmunotherapy of leukemias and
lymphomas in animal models
MoAbs labeled with 1 3 1 I have been used for RIT of
leukemia and lymphoma in experimental animal models. A
feature of many lymphomas and leukemias is that they are
more radiosensitive than carcinomas.6 1
RIT of Rauscher murine erythroleukemia was studied
with 1 3 1I-labeled 103A MoAb reactive with the envelope
glycoprotein expressed on Rauscher murine erythroleukemia cells 62 Dose-response studies showed that about 90%
reduction in spleen size occurred at 2.96 MBq injected per
animal. Similar results were obtained with an irrelevant
MoAb, indicating that RIT with 1 3 1 I was not antibody
specific in this system. Using the MIRD formulation, the
calculated mean absorbed doses to the spleen and whole
body of a mouse treated with 5.92 MBq of 131 I-polyclonal
bovine IgG were 18000 and 1650 mGy, respectively. RIT
using 90Y-labeled 103A MoAb prepared with cyclic DTPA
was also studied.63 Doses of 0.999 to 1.85 MBq 90Y-labeled
103A antibody resulted in complete remission with no microscopic evidence of tumor foci in either spleen or liver,
whereas a dose of 1.85 MBq of control bovine IgG had
areas of abnormal erythropoiesis suggestive of tumor foci
in lymphoid tissue. The specific radiation dose delivered to
the tumor or whole body was not calculated. However,
analysis of the MBq/g present in tumor and normal tissues
over 9 days, indicated that over 20-fold greater radiation
doses were delivered to the tumor than to any other organ
examined.
Gansow et al.64 labeled the 103A MoAb with 2 1 2Bi and
treated mice bearing Rauscher erythroleukemia cells. With
whole body doses of 1270 mGy, tumor foci in spleens of
leukemic mice were mostly eliminated without substantive
toxicity.
M a c k l i s e t a l .6 5 , 6 6 p e r f o r m e d R I T s t u d i e s w i t h
212
Bi-labeled anti-Thy 1.2 IgM MoAb for the treatment of
558
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
EL4 (Thy1.2+) leukemic T-cells injected i.p. in mice.
Mice inoculated i.p. with 5.55 or 8.51 MBq of 212Bi-labeled
antibody in 2 to 4 injections 24 h after EL4 injection were
often cured (80% survival) of their ascites. Animals
treated with 1.48 to 3.7 MBq of 2 1 2Bi-labeled antibody
given i.p. over 4 to 8 h showed significant prolongation in
survival. Nonspecific IgM labeled with 212 Bi did not prolong survival at the same doses. No attempts were made to
estimate the absorbed radiation dose to the tumor cells.
The high LET (about 100 keV/µ) and S-7 cell-diameter
path length of the alpha particle ejected from the 2 1 2 B i
nucleus make it a potentially useful radionuclide for the
RIT of ascites, leukemia, and micrometastases. The short
half-life (60.55 min) may be advantageous in limiting normal tissue doses if there is good tumor localization at early
time points after injection; however, the short half-life creates logistical problems with regard to shipping the radionuclide or even if a cyclotron is nearby.
Badger et al.67 evaluated the use of 131 I-labeled anti-Thy
1.1 differentiation antigen MoAb (31E6.4) to deliver radiotherapy to established AKR/J SL2 (Thy 1.1+) murine
T-cell lymphoma nodules of 0.5 to 1.0 cm in diameter
growing s.c. in congenic AKR/Cum (Thy 1.2+) mice.
Based on kinetic biodistribution data and the MIRD formulation, the mean calculated dose to tumor was 16000
mGy following injection of 18.5 MBq of 131 I-labeled antiThy 1.1 antibody which led to regression of the tumor in
44% of animals. Mice treated with more than 18.5 MBq
131
I-labeled anti-Thy 1.1 antibody died of bone marrow
aplasia. In comparison, 18.5 MBq 131 I-labeled irrelevant
antibody was calculated to deliver a mean dose of 3800
mGy to tumor and had an effect on tumor growth in 6% of
animals. Nourigat et al. 6 8 using the same model demonstrated that 55.5-62.9 MBq 1 3 1I-labeled anti-Thy 1.1
MoAb produced 92% complete regression of SL2 lymphoma nodules containing 0.3% to 1% variant lymphoma
cells that do not express the Thy 1.1 antigen. This study
demonstrated that emitted radiation from radiolabeled antibody bound to antigen-positive tumor cells killed adjacent tumor cells that do not express the target antigen. All
animals treated with radiolabeled antibody died by day 12
from anticipated bone marrow aplasia. Badger et a1. 69 also
examined RIT with 131 I-labeled MoAb against Thy 1.1 for
treating solid SL2 tumor masses in syngeneic AKR/J (Thy
1.1+) mice, where the antibody also reacts with normal
T-cells. The results demonstrated that it was possible to
cause regressions of lymphoma in spite of reactivity with
normal cells. RIT of AKR/J mice bearing established s.c.
lymphoma nodules with 55.5 MBq of 131I-labeled anti-Thy
1.1 MoAb 24 h after infusion of 1mg of unlabeled anti-Thy
1.1 resulted in complete regression of the tumors in 71% of
animals and had a greater cure rate than 27.75 MBq of
131
I-labeled irrelevant antibody (23% complete regression,
p<0.00l), which delivered equivalent radiation doses to
normal organs except for bone marrow. All animals
treated with 55.5 MBq 131 I-labeled anti-Thy 1.1 antibody
died of bone marrow aplasia. Radiation doses to tumor and
various tissues were calculated from the biodistribution
data using the MIRD formulation assuming uniform disMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
558
tribution of the radiolabeled antibody within individual organs. The dose to tumor following treatment with 55.5
MBq 131 I-labeled anti-Thy 1.1 after 1 mg unlabeled antibody was estimated to be 16000 mGy.
Adams et al.7 0 successfully treated Raji Burkitt lymphoma xenografts in athymic nude mice with a single injection of 11.47-14.54 MBq of 1 3 1 I-labeled Lym-1 pan
B-cell MoAb reactive with this tumor. In 3 mice treated
with 1 3 1 I-labeled Lym-1, 4 of 6 tumors regressed completely and did not recur. Griffith et a1.29 performed quantitative autoradiography on Raji tumors with implanted
mini-TLDs from animals injected with 131I-labeled Lym-1.
A maximum radiation dose to tumor of 17400 mGy was
measured (range of 3920-17 400 over all TLD sections)
per 24.27 MBq 131I-labeled Lym-1 injected.
Schmidberger et al.7 1 radiolabeled the Ly1 anti-T-cell
MoAb, the murine homologue of human CD5, with 9 0Y .
When tested in an aggressive model of T-cell lymphoma, a
single 5.18 MBq i.p. dose of 90Y-anti-Ly1, given 1 day after
i.v. injection of a lethal dose of 10 4 E L 4 m o u s e
T-lymphoma cells, resulted in significant, but transient improvement in survival. Protection was selective since a
90
Y-labeled irrelevant control antibody did not prolong
survival. Comparison with external whole-body irradiation
studies indicated that the partially protective effect of 5.18
MBq 9 0Y-anti-Lyl was equivalent to external radiation of
1000-2000 mGy.
D. Radioimmunotherapy of hepatoma in animal
models
Tumor doses of 4500 mGy were calculated by Rostock
et al.72 using the MIRD formulation following injection of
18.5 MBq of 131 I-labeled anti-ferritin polyclonal antibody
in the H-4-11-E syngeneic rat hepatoma model. The dose
deposited in tumor was calculated to be 1550 mGy following injection of 18.5 MBq of 131I-labeled normal IgG. Klein
et al.73 performed RIT studies with 1 3 1 I- and 9 0Y-labeled
(prepared using a proprietary bifunctional chelating
agent) anti-ferritin MoAbs in athymic nude mice bearing
HepG2 human hepatoma s.c. xenografts of 2 to 3 mm in
diameter. Animals injected with a single dose of 14.8 MBq
of 131 I-labeled anti-ferritin MoAb QCI054 showed inhibition of tumor growth and significantly prolonged survival
compared to untreated controls, but there were no longterm survivors, whereas 7.4 or 11.1 MBq of 1 3 1I-labeled
antibody did not inhibit tumor growth nor produce increased survival compared to controls. Animals treated
with 3.7, 7.4, or 11.1 MBq of 9 0Y-labeled anti-ferritin
MoAb had inhibition of tumor growth and significantly
prolonged survival compared to untreated control animals.
Miniature TLDs were implanted into some of the tumors
for radiation dose measurements. Tumor absorbed dose
calculations were performed using biodistribution data and
the MIRD formulation. Tumor doses of 10000 to 15000
mGy produced an inhibition of tumor growth and an extension in survival, but no regressions. Tumor doses of
20000 to 50000 mGy produced greater tumor growth inhibition and a more pronounced increase in survival. At
the highest tumor doses, 75000 to 124000 mGy, obtained
559
Buchsbaum, Langmuir, and Wessls: Experimental radioimmunotherapy
with 7.4 and 11.1 MBq of 9 0Y-labeled MoAb, there was
considerable tumor regression and increased survival.
Those animals showing a significant increase in survival
received up to 124000 mGy to the center of the tumor.
The radiation doses to tumors measured with implanted
TLDs were in good agreement with the calculated tumor
doses. It was estimated that v-labeled anti-ferritin MoAb
deposited approximately 7 times the dose deposited to tumor as equivalent levels of 131I-labeled anti-ferritin MoAb,
which is higher than that expected based on the relative
energy deposited by each radionuclide under equilibrium
conditions, and may be a result of higher nonspecific tumor
uptake or retention of 9 0Y-labeled MoAbs.
E. Radioimmunotherapy of renal cell carcinoma in
animal models
Renal cell carcinoma is relatively resistant to external
beam radiation. Tumor localization studies have demonstrated a high uptake (greater than 50% ID/g) of
131
I-labeled A6H MoAb reactive with human renal cell
carcinoma in tumor xenografts weighing 100 mg. Vessella
et al.74 treated athymic nude mice bearing established s.c.
TK-82 human renal cell carcinomas weighing about 50 mg
with 3.7 MBq of 1 3 1I-labeled A6H MoAb reactive with
human renal carcinoma cells at day 0 and day 20. There
was tumor regression to about 20% of initial size, and
tumor growth was inhibited for at least 90 days. Control
mice treated with 1 3 1 I-labeled irrelevant MoAb showed
progressive increase in tumor size. Dosimetry calculations
using the MIRD formulation and external imaging indicated that the tumors received up to 50000 mGy from
each of the 3.7 MBq 1 3 1 I-labeled MoAb doses, whereas
normal tissues and organs received less than 2500 mGy.
Chiou et al.75 carried out dosimetry studies with 1.37 to
6.55 MBq 131 I-labeled A6H MoAb in athymic nude mice
bearing TK-82 or TK-177G renal cell carcinoma xenografts. Using quantitative imaging and the MIRD formulation, the median radiation dose delivered to TK-177G
tumors was 10 260 mGy/MBq 1311-labeled A6H administered in a single dose, and the median dose to TK-82 tumors was 15 930 mGy/MBq. Normal mouse tissues received a mean dose of 243 mGy/MBq administered. Two
doses of 1311-labeled A6H MoAb (4.07 to 4.81 MBq/dose)
arrested the tumor growth or caused regression of both
renal cell carcinoma xenografts. Similar doses of
131
I-labeled irrelevant MoAb did not inhibit tumor growth.
Using TLDs and autoradiography, Vessella et al. 76 reported a measured tumor dose of 7000 to 24 000 mGy for
a 5.55 MBq injected dose of 131I-labeled A6H MoAb in the
TK-82 renal cell carcinoma xenograft. In another study,
Wessels et al.25 reported TLD average doses to TK-82 xenografts of 3410, 3830, 8860, and 10 340 mGy following a
single administration of 3.7, 7.4, 14.8, and 22.2 MBq of
131
I-labeled A6H antibody, respectively. The range of absorbed doses was estimated to be 300% based on autoradiography density data. Wessels et al. 25 found that MIRD
calculations for tumors were usually higher than TLD
measurements by up to 50%, which is thought to be a
result of the peripheral deposition of radiolabeled antibody
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
559
in contrast to the centrally located TLD. Comparisons to
external beam radiation were reported in this study, 25 a s
were discussed above for colon cancer models, and they are
discussed in more detail in the radiobiology section of this
report.5
F. Radioimmunotherapy of human neuroblastoma in
animal models
131
I-labeled UJ13A MoAb reactive with neuroblastoma
cells was administered to athymic nude mice with TR14
human neuroblastoma xenografts.77 Tumors of approximately 1 cm3 regressed to 10% of their original volume
over a 21-day period following administration of 5.55 MBq
131
I-labeled UJ13A antibody. Repeated injection caused tumors to disappear, but regrowth at the original site always
123
occurred. 1 2 5 1- and -I-labeled UJ13A antibody at the
same radionuclide level had no effect on tumor growth.
Cheung et al. 7a treated athymic nude mice bearing neuroblastoma xenografts with 4.63 to 37 MBq of 131I-labeled
3F8 anti-GD2 MoAb present on neuroblastoma cells.
There was a dose dependent inhibition of tumor growth.
Complete tumor ablation was achieved with 18.5 to 37
MBq of 1 3 1I-labeled 3F8. The dose to tumor was greater
than 42 000 mGy using the MIRD technique. It should be
emphasized that neuroblastoma is a highly radiosensitive
tumor.
G. Radioimmunotherapy of human glioma and
leptomeningeal tumors in animal models
Lee et al.7 9 evaluated the therapeutic efficacy of
I-labeled MoAb 81C6 of the IgG2b subclass, reactive
with an epitope of the glioma-associated extracellular matrix protein tenascin, in athymic nude mice bearing s.c.
human D-54 MG glioma xenografts of 100-500 mm 3. Specific tumor growth inhibition was noted with 9.25 and 18.5
131
MBq i.v. administered I-labeled 81C6 antibody. The
percentage of animals with tumor regression progressively
increased with increasing doses of radiolabeled MoAb. Statistically significant tumor regression was seen at doses of
18.5 and 37 MBq 131I-labeled 81C6. The estimated dose to
tumor over an 11-day period using biodistribution data and
the MIRD formalism was 97 190 mGy following administration of 37 MBq 131I-labeled 81C6, whereas the dose with
an equivalent quantity of irrelevant MoAb of the same
isotype was 23 460 mGy. Doses to other organs ranged
from 1350 mGy for brain to 24 150 mGy for lung. An
important finding in this study was that tumor radiation
dosimetry based on prior 1251-labeled 81C6 localization
data underestimated the dose to tumor by 35%-52% due
to differences in tumor growth in the localization and therapy studies. This has important implications for comparing
the results obtained by various investigators with different
tumor systems.
Lee et al.8 0 evaluated the therapeutic efficacy of
131
I-labeled 81C6 in athymic rats bearing intracranial D-54
MG xenografts. For animals with an average intracranial
tumor volume of 16 to 20 mm 3 , a statistically significant
increase in animal survival was found for animals treated
131
560
Etuchsbaum, Langmuir, and Wessels: Experlmental radioimmunotherapy
with 46.25 or 92.5 MBq 131I-labeled 81C6. The estimated
radiation dose to intracranial tumors of about 3.4 mm in
diameter using the MIRD technique following the i.v. ad131
ministration of 46.25 MBq I-labeled MoAb was 15 850
mGy over a 12-day period for 81C6 and 1680 mGy for the
control antibody. Doses to the other organs ranged from
310 mGy to the brain to 7340 mGy to the bone marrow.
These data were similar to the radiation doses predicted
from localization studies.
Schuster et al.81 compared the growth delay of s.c. D-54
MG tumors produced by 1 3 1I-labeled 81C6 MoAb prepared using Iodogen (IOD) to that prepared using
N-succinimidyl-3-(tri-n-butylstannyl)
benzoate
(ATE).
Growth delay with 81C6 ATE was significantly longer
than with 81C6 IOD. Biodistribution data gave estimated
radiation doses to tumors of 150 mm 3 initial tumor volume
of 77 230 and 52 000 mGy for 18.5 MBq of 1 3 1I-labeled
81C6 ATE or 81C6 IOD, respectively. It was previously
shown that labeling of 81C6 using ATE increased tumor
uptake and T/NT ratios and decreased deiodination compared with labeling using IOD,a2 which explains the difference in tumor growth delay produced by the two radioiodinated MoAbs.
Colapinto et al.8 3 evaluated the efficacy of 131 I-labeled
F(ab’) 2 fragments of MoAb Mel-14, an Ig2a reactive with
a chondroitin sulfate proteoglycan antigen expressed on
gliomas, in prolonging survival of athymic nude mice bearing intracerebral D-54 MG human glioma xenografts. Intravenous injection of 55.5 or 74 MBq of 1 3 1 I-labeled
Mel-14 F(ab’)2 6-7 days after tumor implantation resulted
in a significant increase in animal survival over control
untreated animals or animals treated with 131I-labeled nonspecific antibody. The injection of 111 MBq of 131I-labeled
Mel-14 F(ab’)2 in two doses of 55.5 MBq, 48 h apart,
significantly increased animal survival over untreated control animals. A single injection of 111 MBq of 131I-labeled
Mel-14 did not improve survival over controls which was
probably due to hematologic toxicity. The estimated radiation dose to tumor was 9150 mGy after the two 55.5 MBq
administrations using the MIRD formulation, which was a
higher dose than that delivered to normal organs. The only
normal tissue to receive a substantial dose was kidney
(7490 mGy), which is expected with F(ab’) 2 fragments. A
single dose of 55.5 MBq 1 3 1 I-labeled Mel-14 F(ab’) 2 w a s
estimated to deliver 3900 mGy to tumor and 3790 mGy to
kidney. No cures were reported in any of the above RIT
studies with glioma, which is known to be relatively radioresistant.
Williams et al.84 evaluated the tumor dosimetry of
90
Y-labeled P96.5 MoAb of the IgG2a subclass, reactive
with P97, a cell surface glycoprotein expressed on glioma,
administered to athymic nude mice bearing s.c. U-251 human glioma xenografts 0.3-0.4 g in weight. Miniature
TLDs were implanted into tumors and normal tissues.
Seven days after administration of 3.7 MBq of 90Y-labeled
96.5, average absorbed doses of 37 700, 9800, and 3530
mGy were measured in tumor, liver, and contralateral s.c.
tissue.
Zalutsky et al.85 demonstrated that 2 1 1At-labeled 81C6
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
560
MoAb injected intrathecally into athymic nude rats 8 days
after intrathecal injection of 5×10 5 TE-671 human rhabdomyosarcoma cells improved survival. 211At-labeled 81C6
at a dose of 0.44 MBq increased survival by 113% compared to saline treated animals (median survival of 22.5
days) and produced 3 apparent cures at 6 months, while 6
out of 10 rats receiving 0.67 MBq of 211 At-labeled 81C6
were alive with no evidence of disease at 6 months.
Bender et al.86 reported that 5.55 MBq 125 I-labeled 425
F(ab’) 2 fragments reactive with the epidermal growth factor receptor administered at 4 and 11 days after tumor cell
inoculation exhibited greater anti-tumor effects than 5.55
MBq 131 I-labeled F(ab’), fragments in athymic nude mice
bearing U-87MG human glioma xenografts. These differences may be due to enhanced nuclear damage caused by
the high LET Auger electrons emitted by 1 2 5I following
125
internalization of the I-labeled antibody fragments into
the glioma cells. The radiation dose to tumor using the
standard MIRD procedure was 190 mGy/11.1 MBq of
125
I-labeled F(ab’)2 fragments and 1590 mGy/11.1 MBq
of 1 3 1I-labeled F(ab’), fragments. The radiation dose delivered to normal organs for 125I-labeled fragments was 3 to
60 mGy/11.1 MBq as compared to 26 to 400 mGy/11.1
MBq with 31I-labeled fragments. No effort was made to use
microdosimetry to calculate the dose to tumor and normal
tissues. 8 7
H. Radioimmunotherapy of human mammary
carcinoma in animal models
Ceriani et al.88 conducted experimental RIT studies
with 4 MoAbs, raised against human milk fat globule
membrane glycoproteins also present on normal breast epithelial cells, in athymic nude mice bearing MX-1 human
breast cancer xenografts. 1311-labeled MoAbs injected as a
mixture (“cocktail”) inhibited growth of the tumor in a
dose dependent fashion. A single injection of 18.5 MBq of
“‘I-labeled cocktail inhibited growth for 30 days while a
similar dose of 1 3 1I-labeled control IgG had no effect. A
second administration of 18.5 MBq of 131I-labeled cocktail
injected at an appropriate interval inhibited tumor growth
for another 20 days. No estimate of radiation dose to tumors was made in this study. Ceriani et al. 89 gave single
i.p. injections of 1 3 1I- or 9 0Y-labeled Mc5 or BrE-1 antibreast MoAbs to athymic nude mice bearing MX-1 s.c.
xenografts. The maximum tolerated dose for McS was 55.5
M B q f o r t h e 1 3 1 I-conjugate and 9.25 MBq for the
q-conjugate. For the BrE-1 MoAb, the maximum tolerated doses for these radionuclides were 40.7 and 5.55 MBq,
respectively. Dose dependent growth inhibition of MX-1
tumors was observed with each of the radiolabeled
MoAbs. The highest tumoricidal effectiveness was ob131
tained with I-labeled Mc5. A second injection of 55.5
131
MBq of I-labeled Mc5 at 20 days after the first injection
produced prolonged inhibition of tumor growth.
Senekowitsch and colleague?’ investigated the therapeutic efficacy of 1 3 1I-labeled BW 495/36 MoAb against
human mammary carcinoma xenografts. Two injections of
7.4 MBq 131 I-labeled BW 495/36 1 week apart resulted in
a mean reduction of tumor volume of 88% within 42 days
561
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
post injection. 1 3 1I-labeled nonspecific antibody caused
slight inhibition of tumor growth. The estimated radiation
dose to tumor using scintigraphic imaging and the MIRD
formulation was 77 000 mGy within 38 days.
I. Radioimmunotherapy of human small cell lung
carcinoma in animal models
Small cell lung cancer cells are relatively radiosensitive.
Yoneda et a1.91 evaluated RIT of human small cell lung
cancer xenografts of 0.5-1 cm in diameter in athymic nude
mice using 131 I-labeled TFS-4 MoAb reactive with human
small cell lung cancer cells. Administration of 7.4 MBq of
131
I-labeled TFS-4 inhibited tumor growth when compared
with 131 I-labeled control MoAb. The tumor growth inhibition was dose dependent. A radiation dose to tumor of
10 380 mGy was estimated by scintigraphy and the MIRD
formulation following the administration of 11.1-18.5
MBq 1 3 1I-labeled TFS-4. Two injections of 18.5 MBq of
131
I-labeled TFS-4 at a 5 week interval inhibited tumor
growth for about 60 days.
B e a u m i e r a n d c o l l e a g u e s9 2 e v a l u a t e d t h e u s e o f
186
Re-labeled MoAb NR-LU-10 reactive with small cell
lung carcinoma cells in athymic nude mice bearing s.c.
SHT-1 small cell lung carcinoma xenografts. A multiple
dose regimen of 18.13 MBq 186 Re-labeled NR-LU-10 divided into 4 doses over 10 days was less toxic than a single
dose of 15.91 MBq 186Re-labeled NR-LU-10. Several dose
regimens were evaluated. Radiation doses to tumor were
estimated by biodistribution data and the MIRD formulation with an infinite volume boundary correction factor of
0.75 to account for the size of tumors used in this study.
Two doses of 7.88 MBq on day 0 and 10.32 MBq on day 7
(18.2 MBq total) were estimated to deliver 20 120 mGy to
tumor. Four doses of 8.07 MBq on day 0,2.22 MBq on day
3, 10.36 MBq on day 7, and 1.67 MBq on day 10 (22.31
MBq total) were estimated to deliver 26 710 mGy to tumor. This dose produced a 53 day mean growth delay that
was statistically greater than equal doses of 186 Re-labeled
irrelevant antibody, with a few complete remissions, but
most tumors recurred.
J. Radioimmunotherapy of human cervical and
ovarian carcinoma in animal models
Human cervical carcinoma has a moderate radiosensitivity. Chen and collaborators93 performed RIT studies
with 131 I-labeled TNT-1 IgG2a MoAb, with specificity for
nuclear histones, against ME-180 human cervical carcinoma s.c. xenografts of approximately 0.5 cm 3 in athymic
nude mice. The 131I-labeled antibody was administered i.v.
on days 1, 8, and 15. Tumor radiation dosimetry was estimated using tissue counting and imaging data and the
MIRD formalism. The administration of 11.1 MBq
131
I-labeled TNT-l antibody for three successive weekly
doses, produced significant inhibition of tumor growth
compared to 131 I-labeled irrelevant antibody, with regressions in 88% of treated animals and complete regressions
in 25% of the mice. After the first week of treatment with
11.1 MBq 131I-labeled TNT-1 antibody, the mean radiation
Medical Physical, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
567
dose delivered to tumor was 10 660 mGy. In the second
and third weeks of therapy with 11.1 MBq 1 3 1 I-labeled
antibody, the mean tumor doses were 20 460 and 24 760
mGy, respectively.
Molthoff et al. tested the therapeutic efficacy of
131
I-labeled 139H2 anti-episialin IgG1 MoAb in the
NIH:OVCAR-3 human ovarian cancer s.c. xenograft
model. 94 The radiation dose to the tumor after a single i.v.
131
injection of 18.5 MBq I-labeled 139H2 MoAb was estimated to be 13 000 mGy over a 7-day period calculated
from the biodistribution of the radiolabeled MoAb, and
assuming uniform distribution within the tumor and organs, using the MIRD formalism. Well vascularized organs such as the liver, spleen, heart, lungs, and kidneys
received between 4000 and 8000 mGy.
K. Radioimmunotherapy of human bladder cancer in
an animal model
Lightfoot et al.9 5 evaluated the RIT of UCRU-BL17CL human bladder cancer s.c. xenografts in athymic
nude mice following a single i.p. injection of 153Sm-labeled
BLCA-38 murine MoAb reactive with human bladder cancers. Tumors in mice that received 9.25 MBq 153Sm-labeled
BLCA-38 had a tumor doubling time of 8.4 days, whereas
tumors in mice injected with 9.25 MBq 153Sm-labeled control antibody had a tumor doubling time of 5.7 days. This
difference became significant from day 21 onward. The radiation dose to tumor and normal organs from
153
Sm-labeled BLCA-38 was estimated using biodistribution studies and the MIRD technique. For an injection of
153
37 MBq of Sm-labeled BLCA-38, the dose to tumor was
estimated to be 19 000 mGy, whereas the kidneys and liver
would receive a dose of 21 900 and 52 300 mGy, respectively. All other normal tissues would receive a lower dose
than tumor, but the whole-body dose was estimated to be
8500 mGy. This radiolabeling was performed using the
cyclic anhydride of DTPA, and the use of a more stable
chelate might result in a lower dose to normal organs.
III. DISCUSSION
The use of the spheroid model has demonstrated the
importance of adequate antibody penetration prior to radionuclide decay in micrometastases. Theoretical dosimetry modeling using the spheroid model has shown that,
although high energy beta emitters are likely best for the
treatment of solid tumors, this may not be the case in
micrometastases, and in fact, lower energy emitters may be
more efficacious because a smaller proportion of the radiation dose is lost outside of the target volume, particularly
when there is poor penetration. 1 6
The results presented above indicate that RIT with 131 I,
153
212
90
Y, 1 8 6Re, and Sm beta emitting, and Bi alpha emitting radionuclides attached to MoAbs has been effective
against a variety of tumor types transplanted in animals
including leukemia and lymphoma, colon cancer, hepatoma, renal cell carcinoma, neuroblastoma, glioma,
breast cancer, lung cancer, cervical carcinoma, ovarian
carcinoma, and bladder cancer. The majority of investiga-
562
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
tors have estimated the dose to tumor and normal organs
using MIRD-based calculations (time-activity curve and
equilibrium dose constant method).3* 4 A few investigators
have estimated the dose to tumor and normal organs using
TLDs and autoradiography. A summary of the results reported is shown in Table I. Recently, RIT studies have
been conducted with the beta emitting radionuclide
177
L u ,96 although no dosimetry estimates were made. A
single injection of 7.4 or 12.95 MBq of 177Lu-labeled CC49
reactive with human colon cancer was shown to produce
complete regression of established LS174T tumor xenografts.
The effectiveness of radiolabeled MoAb therapy depends on such factors as antibody specificity, immunoreactivity and affinity; antigen density, availability, shedding,
and heterogeneity; stability of the radiolabeled antibody;
tumor vascularity, blood flow, and permeability. 8 0’ 9 7 , 9 8
Each of these factors will be discussed in some detail.
Monoclonal antibodies have great specificity for recognizing and selectively binding to antigens on tumor cells,
and cell surface antigenic targets such as B-cell immunoglobulin idiotypes, growth factor receptors, and other
tumor-associated, accessible, high density antigens have
been defined for effective MoAb action.99 In principle, the
more specific the antibody for a particular tumor type, the
greater the opportunity for the MoAb to show selective
uptake in the tumor. A quantitative increase of an antigenic substance on tumor cells or in the milieu of a tumor
can suffice for targeting MoAbs to this site. 100 Radiolabeled
MoAbs offer potential advantages over conventional therapeutic procedures by providing greater specificity as a result of preferential binding of the antibodies to tumor cells.
The immunoreactivity of radiolabeled MoAb preparations has been shown to affect the localization in tumor and
n o r m a l t i s s u e s .101-104 Yokoyama et al.101 p r e p a r e d t w o
high performance liquid chromatography fractions of
125
I-labeled Fab 96.5 MoAb reactive with human melanoma. One fraction had relatively low immunoreactivity
(25%-38%) and the second fraction had high immunoreactivity (70%-81%). The two fractions had similar affinity constants. In biodistribution studies in athymic nude
mice bearing FEMX-11 human melanoma xenografts, the
high immunoreactivity preparation rapidly cleared from
the blood and normal organs while retention of radioactivity in the tumor was prolonged. The low immunoreactivity
preparation had slower blood and normal organ clearance
but faster tumor clearance than the high immunoreactivity
fraction. Thus highly immunoreactive antibody gave
higher tumor to normal tissue ratios. Koizumi et al.102
compared the uptake in human osteogenic sarcoma xenografts of three 7 5Se-, 1 1 1In-, and 1 2 5I-labeled MoAbs reactive with human osteogenic sarcoma, and correlated the
results to their immunoreactivity. For “‘In-labeled
MoAbs, increasing immunoreactivity resulted in higher tumor uptake, whereas with 7 5Se- and 1 2 5I-labeled MoAbs,
there was not a direct correlation between increasing immunoreactivity and increased tumor uptake. Sakahara
et al.103 found that as the molar ratio of cyclic DTPA conjugated to a MoAb reactive with human α− fetoprotein inMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
562
creased from 1.0 to 5.5, the immunoreactivity of the antibody decreased and the uptake in an α− fetoproteinproducing human testicular tumor was lower by 35% but
the liver uptake was 71% higher. Similarly, Matzku
et al.104 reported that as the level of 1 2 5 I substitution was
increased in the M.2.9.4 MoAb reactive with human melanoma, the immunoreactivity decreased and the specificity
index of tumor localization decreased.
A potential method to increase the uptake and retention
of radiolabeled MoAbs in tumor and increase their therapeutic efficacy is the use of MoAbs with greater affinity.
However, if circulating tumor-associated antigen is
present, then the higher affinity may result in greater nontumor binding and less tumor localization than if a lower
affinity MoAb was used. Muraro et al. 105 produced a series
of MoAbs with different affinities for the TAG-72 antigen
expressed in human carcinomas. A direct correlation was
found between the affinity of these six 125 I-labeled MoAbs
(range of 3.6 to 27.7×10 9 M - 1) and the uptake in LS174T human colon cancer xenografts. 106 The effect of
MoAb affinity on LS174T anti-tumor efficacy was studied
with three of the 1 3 1I-labeled MoAbs (range of 2.5 to
27.7×10 9 M - 1) reactive with the TAG-72 antigen.“’ The
results of these studies demonstrated a substantial therapeutic advantage of the two higher affinity antibodies versus the lower affinity antibody at five radionuclide dose
levels. Greater anti-tumor effects were seen using 2.5- to
3-fold less of the higher affinity antibodies. Andrew et al. 108
correlated the in vitro binding characteristics of four
MoAbs reactive with the murine Ly-2.1 or Ly-3.1 antigen
with their in vivo tumor localization characteristics. The
ranking of the antibodies by affinity (range of 2.1 to
2 8 . 4 × 1 0 5 M - 1) agreed with the ranking in terms of their
localization in tumors, but the immunoreactivity of the
antibodies did not correlate with their tumor localization.
In contrast, McCready et al. 109 did not find that the in vitro
binding characteristics of two MoAbs reactive with human
melanoma correlated with their localization in three human melanoma xenografts. There is no good experimental
data yet in humans to support the hypothesis that increased MoAb affinity results in better tumor localization.
Langmuir et al. have shown that a lower affinity antibody
produced a more even radionuclide distribution in multicell spheroids. When equivalent amounts of activity bound
were compared, the lower affinity antibody (3-fold lower)
labeled with 125 I produced significantly more cell killing,
presumably because the range of 125 I is so small.1 3
In regard to antigen density, Philben et al. 110 found that
human colon cancer xenografts that had a higher CEA
content (ng/g of tumor) had a higher tumor uptake of
111
In-labeled anti-CEA MoAb. Several other investigators
have demonstrated a relationship between tumor antigen
content in human tumor xenografts and uptake of radiolalabeled antibody. 100,111-113 It has also been shown in a number of tumor systems that interferon enhances the expression of tumor-associated antigens on tumor cells both in
vitro and in vivo, which results in increased localization of
radiolabeled MoAbs in tumors in animal models 44,114-116
and patients,1 1 7 and has produced greater therapeutic
563
Buchsbaum, Langmuir, ad Wessels: Experimental radioimmunotherapy
results. 4 4 This approach may also result in higher levels of
circulating tumor-associated antigen, which may interfere
with the localization of radiolabeled antibody in tumor.
In regard to tumor antigen availability, it is not possible
to generalize regarding the best location of antigen.
Whether the tumor-associated antigen needs to be on the
tumor cell membrane, in the extracellular milieu, or accessible intracellularly may vary for each tumor type, site of
growth, and radionuclide.100 Blumenthal et al.118 evaluated
the localization of 131I-labeled NP-4 anti-CEA antibody in
four size-matched human colon cancer xenografts (L174T,
GW-39, GS-2, and Moser) grown s.c. in athymic nude
mice. Intratumoral distribution of antigen, and intracellular accessibility of antigen affected localization. Tumorassociated antigens shed into the serum have been found to
complex with injected radiolabeled MoAbs, 100,118 and these
complexes may accumulate in reticulonedothelial tissues,
resulting in radiation toxicity to these tissues.
A concern in the use of radiolabeled MoAbs has been
the degree of heterogeneity of binding to target cells within
a tumor, due to the inability of antibody to penetrate uniformly in a solid tumor mass and bind to all cells, 119-122 a s
well as whether or not all cells within the tumor express
antigen. 123,124 It has been postulated that low affinity antibodies or antibody fragments would penetrate tumors
better. 112,114 Andrew et al. 123 found that a cocktail of two
or three MoAbs reactive with different antigens expressed
by human colon cancer showed a 2- to 3-fold higher %
ID/g in the L1M1899 human colon cancer xenograft than
did single antibodies. Blumenthal et al. 124 reported that
hamsters bearing GW-39 human colon cancer xenografts
given a mixture of 1 3 1I-labeled NP4 anti-CEA antibody
and Mu-9 anti-colon-specific antigen-p showed better tumor growth inhibition of tumor masses less than 0.5 cm 3 in
size than was produced by either antibody alone at an
equal radionuclide dose. Interestingly, the radiation dose
delivered to tumor by the antibody mixture was estimated
by the MIRD procedure to be 35 980 mGy/37 MBq,
whereas the dose for the individual antibodies was estimated to be 11 500 mGy/37 MBq for NP-4 alone and
41 370 mGy/37 MBq for Mu-9 alone. Thus, the enhanced
therapeutic efficacy of the antibody cocktail cannot be explained by the radiation dose delivered, but it may be a
result of targeting a greater number of tumor cells or a
change in the microdistribution of the antibodies with the
antibody mixture.
Tumor vascularity, blood flow, and permeability are
factors that affect the localization and distribution of radiolabeled MoAbs in tumors and influence their therapeutic
effectiveness. 100,121,122,125 As discussed above, the permeability of antibody fragments is greater than intact antibody, and this may explain their greater therapeutic
e f f e c t i v e n e s s .3 2 - 3 5 , 1 0 0 , 1 1 1 , 1 2 1 , 1 2 2 B l u m e n t h a l e t a l .1 1 2 i m planted the GW-39 human colon tumor in the cheek
pouch, muscle, subcutaneously, or in the liver of hamsters
or nude mice. They found that the tumors with a higher
blood flow rate, vascular volume, and/or vascular permeability had a higher tumor uptake of 1 3 1 I-labeled NP-4
anti-CEA antibody. Blumenthal et al. 126 reported that 5.55
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
563
MBq 1 3 1I-labeled Mu-9 antibody reduced the number of
blood vessels in GW-39 xenografts in athymic nude mice
by 60% to 70%, reduced the vascular volume by 75%, the
blood flow rate by 65%, and the vascular permeability to
an IgG by 60% at 7 to 14 days after injection. These functional changes in tumor blood vessels reduced the tumor
uptake of a second dose of radiolabeled antibody by 90%.
Cope et al.1 2 7 found an enhanced localization of both specific and control F(ab’)2 fragments in human glioma xenografts over a limited time period following local hyperthermia which is known to increase tumor blood flow.
It must be kept in mind, however, that there are limitations of spheroid and animal models in mimicking what
occurs in the clinical situation. 1,97 The limitations of the
spheroid model are that it does not allow for an evaluation
of the role of normal host cells, the vasculature, blood flow,
vascular permeability, or pharmacokinetics on the dose to
tumor. The limitations of the animal models in predicting
what will occur in humans are their smaller size and therefore smaller volume of radiolabeled antibody distribution,
differences in tumor cell cycle and volume doubling times
which influence radioresponsiveness, the difference in
plasma half-life of radiolabeled MoAbs in animals as compared to humans, lack of cross-reactive antigens in animals, and the differences in bone marrow radiosensitivity
and repopulation kinetics following RIT. These differences
make it difficult to design studies in animals that will predict what will occur in the clinical situation. The greater
use of disseminated tumor models in animals would come
closer to the clinical situation than a simple subcutaneous
tumor model, and more effort should be paid experimentally to regional therapy models such as intracerebral or
intraperitoneal that should allow for a greater tumor dose.
A few studies attempted to compare different radionuclides in the same model system. 46,47,73 It is recommended
that in the future more investigators make such comparisons which should include an analysis of the relative toxicity including comparisons for both tumor and normal
tissue damage to external beam therapy (see radiobiology
section 5). Alpha emitters and Auger electron emitters have
the potential advantage of high LET and radiobiological
effectiveness (RBE) which produces greater tumor cell
killing per quantity of radioactivity administered than low
and medium LET gamma ray and beta emitters. 5 T h e r e
would be an advantage for alpha emitters if the radiolabeled MoAbs were uniformly distributed in tumors. However, for bone marrow or other tissues more radiosensitive
than tumor, alpha emitters conjugated to MoAbs would
have less toxicity than beta emitters for an equivalent tumor cell kill. For normal tissues less radiosensitive than
tumor, beta emitters would produce less toxicity. 5
It is also recommended that more investigators look at
radiation dose heterogeneity using TLDs and autoradiography, so that the range of tumor radiation dose and dose
rate is reported. It is hoped that in the future, an answer to
how heterogeneity in antibody deposition affects absorbed
dose distribution and the radiobiological consequences will
be understood for the various radionuclides and tumor
types studied in experimental RIT. It is hoped that a de-
564
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
finitive answer will be obtained for
forms of antibody are optimum for
crometastases, and solid tumors,
how best to apply these techniques
treatment of tumors clinically.
what radionuclides and
RIT of leukemias, miand most importantly
and information to the
ACKNOWLEDGMENTS
We thank Dr. Michael Zalutsky for his helpful comments and Renee Kite and Done11 Berry for typing the
manuscript. Supported by NIH Grant CA44173.
a)
Correspondence should be sent to: Donald J. Buchsbaum, Ph.D., Department of Radiation Oncology, University of Alabama at Birmingham, 619 South 19th Street, Birmingham, AL 35233.
1
B. W. Wessels, “Current status of animal radioimmunotherapy,” Cancer Res. (Suppl.) 50, 970s-973s (1990).
2
L. F. Mausner and S. C. Srivastava. “Selection of radionuclides for
radioimmunotherapy,” Med. Phys. 20, 503-509 (1993).
3
L. T. Dillman and F. C. Von der Lage, “Radionuclide decay schemes
and nuclear parameters for use in radiation-dose estimation,” in, Medical Internal Radiation Dose (MIRD), (Society of Nuclear Medicine,
New York, NY, 1975) Pamphlet No. 10, pp. 5-119.
4
M. J. Berger, “Biodistribution of absorbed dose around point sources of
electrons and beta particles in water and other media,” MIRD Pamphlet No. 7, J. Nucl. Med. (Supp.) 12(5), 1-23 (1971).
5
V. K. Langmuir, J. F. Fowler, S. J. Knox, B. W. Wessels, R. M.
Sutherland, and J. Y. C. Wong, “Radiobiology and radiolabeled antibody therapy as applied to tumor dosimetry,” Med. Phys. 20, 601-610
(1993).
4
R. Sutherland, F. Buchegger, M. Schreyer, A. Vacca, and J. -P. Mach,
“Penetration and binding of radiolabeled anti-carcinoembryonic antigen monoclonal antibodies and their antigen binding fragments in human colon multicellular tumor spheroids,” Cancer Res. 47, 1627-1633
(1987).
5
K. A. Walker, T. Murray, T. E. Hilditch, T. E. Wheldon, A. Gregor,
and I. M. Harm, “A tumour spheroid model for antibody-targeted
therapy of micrometastases,” Br. J. Cancer 58, 13-16 (1988).
8
C. S. Kwok, S. E. Cole, and S. -K. Liao, “Uptake kinetics of monoclonal antibodies by human malignant melanoma multicell spheroids,”
Cancer Res. 48, 1856-1863 (1988).
9
C. S. Kwok, A. Crivici, W. D. MacGregor, and M. W. Unger, “Optimization of radioimmunotherapy using human malignant melanoma
multicell spheroids as a model,” Cancer Res. 49, 3276-3281 (1989).
10
V. K. Langmuir, J. K. McGann, F. Buchegger, and R. M. Sutherland,
“ 131I-anticarcinoembryonic antigen therapy of LS174T human colon
adenocarcinoma spheroids,” Cancer Res. 49, 3401-3406 (1989).
11
V. K. Langmuir, R. W. Atcher, J. J. Hines, and M. W. Brechbiel,
“Iodine-125-NRLU-10 kinetic studies and bismuth-212-NRLU-10 toxicity in LS174T multicell spheroids,” J. Nucl. Med. 31, 1527-1533
(1990).
12
V, K. Langmuir, J. K. McGann, F. Buchegger, and R. M. Sutherland,
“The effect of antigen concentration, antibody valency and size, and
tumor architecture on antibody binding in multicell spheroids,” Nucl.
Med. Biol. 18, 753-764 (1991).
13
V. K. Langmuir, H. L. Mendonca, and D. V. Woo. “Comparisons
between two monoclonal antibodies that bind to the same antigen but
have differing affinities: Uptake kinetics and 125I-antibody efficacy in
multicell spheroids,” Cancer Res. 52, 4728-4734 (1992).
14
V. K Langmuir, H. L. Mendonca, J. -L. Vanderheyden, and F. -M. Su,
“Comparisons of the efficacy of 1 8 6Re- and 1 3 1I-labeled antibody in
multicell spheroids,” Int. J. Radiat. Oncol. Biol. Phys. 24, 127-132
(1992).
15
V. K. Langmuir and H. L. Mendonca, “The role of radionuclide distribution in the efficacy of 131I-labeled antibody as modeled in multicell
spheroids,” Antib. Immunoconj. Radiopharm. 5, 273-283 (1992).
16
V. K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 (1988).
17
M. Bardies, I. Lame, M. J. Myers, and J. P. Simoen, “A simplified
approach to beta dosimetry for small spheres labelled on the surface,”
Phys. Med. Biol. 35, 1038-1050 (1990).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
18
564
M. Bardies, P. Thedrez. J. F. Gestin, and M. B. Marcille, “Use of
multicell spheroids of ovarian carcinoma as an intraperitoneal radioimmunotherapy model: Uptake, retention kinetics and dosimetric evaluation,” Int. J. Cancer 50, 984-991 (1992).
19
V. K. Langmuir. B. W. Wessels. H. L. Mendonca, E. D. Yorke, and L.
Montilla. “Comparisons of sectioned micro-TLD dose measurements
with predicted dose from “‘I-labeled antibody,” Med. Phys. 19, 12131218 (1992).
20
D. M. Goldenberg. S. A. Gaffar, S. J. Bennett, and J. L. Beach. “Experimental radioimmunotherapy of a xenografted human colonic tumor (GW-39) producing carcinoembryonic antigen,” Cancer Res. 41,
4354-4360 (1981).
21
R. M. Sharkey, M. J. Pykett, J. A. Siegel, E. A. Alger. F. J. Primus,
and D. M. Goldenberg, “Radioimmunotherapy of the GW-39 human
131
colonic tumor xenograft with I-labeled murine monoclonal antibody
to carcinoembryonic antigen,” Cancer Res. 47, 5672-5677 (1987).
22
J. M. Esteban, J. Schlom, F. Momex, and D. Colcher, “Radioimmunotherapy of athymic mice bearing human colon carcinomas with
monoclonal antibody B72.3: Histological and autoradiographic study
of effects on tumors and normal organs,” Eur. J. Cancer Clin. Oncol.
23, 643-655 (1987).
23
J. R. Zalcberg, C. H. Thompson, M. Lichtenstein. and I. F. C.
McKenzie, “Tumor immunotherapy in the mouse with the use of
“‘I-labeled monoclonal antibodies,” J. Natl. Cancer Inst. 72, 697-704
(1984).
24
B. W. Wessels, M. H. Griffith, E. W. Bradley, and B. Sibinski, “Dosimetric measurements and radiobiological consequences of radioimmunotherapy in tumor bearing mice, ” in Fourth International Radiopharmaceutical Dosimetry Symposium, edited by A. T. Schlafke-Stelson and
E. E. Watson (Oak Ridge Associated Universities, Oak Ridge, TN
1968), pp. 446-457.
25
B. W. Wessels, R. L. Vessella, D. F. Palme II, J. M. Berkopec, G. K.
Smith, and E. W. Bradley, “Radiobiological comparison of external
beam irradiation and radioimmunotherapy in renal cell carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 17, 1257-1263 (1989).
26
D. J. Buchsbaum, R. K. Ten Haken, D. B. Heidom. T. S. Lawrence, A.
A. Glatfelter, V. H. Terry, D. M. Guilbault, Z. Steplewski, and A. S.
Lichter, “A comparison of “‘I-labeled monoclonal antibody 17-1A
treatment to external beam irradiation on the growth of LS174T human colon carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 18,
1033-1041 (1990).
27
D. J. Buchsbaum, P. G. Brubaker, D. E. Hanna, A. A. Glatfelter, V. H.
Terry, D. IM. Guilbault, and Z. Steplewski, “Comparative binding and
preclinical localization and therapy studies with radiolabeled human
chimeric and murine 17-1A monoclonal antibodies,” Cancer Res.
(Suppl.) 50, 993s-999s (1990).
28
W. P. Neacy, B. W. Wessels, E. W. Bradley, S. Kovandi, T. Justice, S.
Danskin, and H. Sands, “Comparison of radioimmunotherapy (RIT)
and 4 MV external beam radiotherapy of human tumor xenografts in
athymic mice,” J. Nucl. Med. 27, 902-903 (1986).
29
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
30
P. L. Roberson, D. J. Buchsbaum, D. B. Heidom, and R. K. Ten
Haken, “Three-dimensional tumor dosimetry for radioimmunotherapy
using serial autoradiography,” Int. J. Radiat. Oncol. Biol. Phys. 24,
329-334 (1992).
31
P. L. Roberson, D. J. Buchsbaum, D. B. Heidom, and R. K. Ten
Haken, “Variations in 3-D dose distributions for “‘Iodine-labeled
monoclonal antibody,” Antib. Immunoconj. Radiopharm. 5, 397-402
(1992).
32
F. Buchegger, A. Pelegrin, B. Delaloye, A. Bischof-Delaloye, and J. -P.
Mach, “Iodine-131-labeled MAb F(ab’)2 fragments are more efficient
and less toxic than intact anti-CEA antibodies in radioimmunotherapy
of large human colon carcinoma grafted in nude mice,” J. Nucl. Med.
31, 1035-1044 (1990).
33
F. Buchegger, C. Pfister, K. Foumier, F. Prevel, M. Schreyer, S. Carrel, and J. -P. Mach, “Ablation of human colon carcinoma in nude
mice by 131I-labeled monoclonal anti-carcinoembryonic antigen antibody F(ab’)2 fragments,” J. Clin. Invest. 83, 1449-1456 (1989).
34
F. Buchegger, A. Vacca, S. Carrel, M. Schreyer, and J. -P. Mach,
“Radioimmunotherapy of human colon carcinoma by 131I-labelled
monoclonal anti-CEA antibodies in a nude mouse model,” Int. J. Cancer 41, 127-134 (1988).
565
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
35
R. M. Sharkey, K. S. Weadock, A. Natale, L. Haywood, R. Aninipot,
R. D. Blumenthal, and D. M. Goldenberg, “Successful radioimmunotherapy for lung metastasis of human colonic cancer in nude mice,” J.
Natl. Cancer Inst. 83, 627-632 (1991).
36
T. Yokota, D. E. Milencic, M. Whitlow. and J. Schlom, “Rapid tumor
penetration of a single-chain Fv and comparison with other immunoglobulin forms,” Cancer Res. 52, 3402-3408 (1992).
37
J. Schlom, A. Molinolo, I. F. Simpson, K. Siler, M. Roselli, G. Hinkle,
D. P. Houchens, and D. Colcher, “Advantage of dose fractionation in
monoclonal antibody-targeted radioimmunotherapy,” J. Natl. Cancer
Inst. 82, 763-771 (1990).
38
Y. C. Lee, L. C. Washburn, T. T. H. Sun, B. L. Byrd, J. E. Crook, and
Z. Steplewski, “Radioimmunotherapy of human colorectal carcinoma
xenografts using 90Y-labeled monoclonal antibody CO17-IA prepared
by two bifunctional chelate techniques,” Cancer Res. SO, 4546-4551
(1990).
39
L. C. Washburn, T. T. H. Sun, Y. -C. C. Lee, B. L. Byrd, E. C.
Holloway, J. E. Crook, J. B. Stubbs, M. G. Stabin, M. W. Brechbiel, O.
A. Gansow, and Z. Steplewski, “Comparison of five bifunctional chelate techniques for v-labeled monoclonal antibody CO17-1A,” Nucl.
Med. Biol. 18, 313-321 (1991).
40
L. C. Washburn, Y. -C. C. Lee, T. T. H. Sun, B. L. Byrd, E. C.
Holloway, J. E. Crook, and Z. Steplewski, “Radioimmunotherapy of
SW 948 human colorectal carcinoma xenografts with repeated injections of 90Y-labeled monoclonal antibody CO17-1A.” Antib. Immunoconjug. and Radiopharm. 4, 729-734 ( 1991).
41
R. M. Sharkey, F. A. Kaltovich, L. B. Shih, I. Fand, G. Govelitz, and
D. M. Goldenberg, “Radioimmunotherapy of human colonic cancer
xenografts with 90Y-labeled monoclonal antibodies to carcinoembryonic antigen,” Cancer Res. 48, 3270-3275 (1988).
42
R. R. Buras. B. G. Beatty, L. E. Williams, P. M. Wanek, J. B. Harris,
R. Hill, and J. D. Beatty, “Radioimmunotherapy of human colon cancer in nude mice,” Arch. Surg. 125, 660-664 (1990).
43
R. R. Buras, J. Y. C. Wong, J. A. Kuhn, B. G. Beatty, L. E. Williams,
P. M. Wanek, and J. D. Beatty, “Comparison of radioimmunotherapy
and external beam radiotherapy in colon cancer xenografts,” Int. J.
Radiat. Oncol. Biol. Phys. 25, 473-479 ( 1993).
“J. A. Kuhn, B. G. Beatty, J. Y. C. Wong, J. M. Esteban, P. M. Wanek,
F. Wall, R. R. Bums, L. E. Williams, and J. D. Beatty, "Interferon
enhancement of radioimmunotherapy for colon carcinoma,” Cancer
Res. 51, 2335-2339 (1991).
45
C. S. Heacock, A. M. Blake, C. J. D’Aleo, and V. L. Alvarez, “Use of
an yttrium-90 labeled antibody for the treatment of human colon cancer xenografts in nude mice,” Synthesis and Applications of Isotopitally Labelled Compounds, 783-786 (1989).
46
D. J. Buchsbaum, T. S. Lawrence, P. L. Roberson, D. B. Heidorn, R.
K. Ten Haken, and Z. Steplewski, “Comparison of “‘I- and
90
Y-labeled monoclonal antibody 17-1A for treatment of human colon
cancer xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 25, 629-638
(1993).
47
R. M. Sharkey, C. Motta-Hennessy, D. Pawlyk, J. A. Siegel, and D. M.
Goldenberg, “Biodistribution and radiation dose estimates for yttriumand iodine-labeled monoclonal antibody IgG and fragments in nude
mice bearing human colonic tumor xenografts,” Cancer Res. 50, 23302336 (1990).
48
B. A. Morton, B. G. Beatty, A. Mison, P. M. Wanek, and J. D. Beatty,
“Role of bone marrow transplantation in yttrium-90 antibody therapy
of colon cancer xenografts in nude mice,” Cancer Res. (Suppl.) 50,
1008s-1010s (1990).
49
F. M. Uckun, L. Souza, K. G. Waddick, M. Wick, and C. W. Song, “In
vivo radioprotective effects of recombinant human granulocyte colonystimulating factor in lethally irradiated mice,” Blood 75, 638-645
(1990).
50
R. D. Blumenthal, R. M. Sharkey, D. J. Snyder, H. J. Hansen, and D.
M. Goldenberg, “Reduction of radioantibody-induced myelotoxicity in
hamsters by recombinant interleukin-1,” Cancer Res. 48, 5403-5406
(1988).
51
F. M. Uckun, S. Gillis, L. Souza. and C. W. Song, “Effects of recombinant growth factors on radiation survival of human bone marrow
progenitor cells,” Int. J. Radiat. Oncol. Biol. Phys. 16, 415-435
(1989).
52
V. S. Gallicchio, B. C. Hulette, M. J. Messino, C. Gass. M. W. Bieschke, and M. A. Doukas, “Effect of various interleukins (IL-l, IL-2,
and IL-3) on the in vitro radioprotection of bone marrow progenitors
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
565
(CFU-GM and CFU-MEG),” J. Biol. Response Mod. 8, 479-487
(1989).
R. Neta, S. Douches, and J. J. Oppenheim, “Interleukin 1 is a radioprotector,” J. Immunol. 136, 2483-2485 (1986).
54
R. Neta, J. J. Oppenheim, and S. D. Douches, “Interdependence of the
radioprotective effects of human recombinant interleukin-1, tumor necrosis factor, granulocyte colony-stimulating factor and murine recombinant granulocyte-macrophage colony stimulating factor,” J. Immunol. 140, 108-111 (1988).
55
R. Neta S. D. Douches, and J. J. Oppenheim, “Radioprotection by
interleukin-1,” in UCLA Symposia on Molecular and Cellular Biologv,
edited by G. Goldstein, J. F. Bach, and H. Wigzal (Liss, New York,
NY, 1986), p. 429.
56
R. Neta, J. J. Oppenheim, S. D. Douches, P. C. Giclas, R. J. Imbra,
and M. Karin, “Radioprotection with interleukin-1: Comparison with
other cytokines,” in Progress in Immunology, edited by B. Cinader and
R. G. Miller (Academic, San Diego, CA, 1986), Vol. 6, pp. 900-908.
57
R. Neta and J. J. Oppenheim, “Cytokines in therapy of radiation injury,” Blood 72, 1093-1095 (1988).
58
R. Neta M. B. Sztein, J. J. Oppenheim, S. Gills, and S. D. Douches,
“The in vivo effects of interleukin 1. I. Bone marrow cells are induced
to cycle after administration of interleukin 1,” J. Immunol. 139, 18611866 (1987).
59
R. B. Pedley, R. H. J. Begent, J. A. Boden, R. Boden, T. Adam, and K.
D. Bagshawe, “The effect of radiosensitizers on radioimmunotherapy,
using 131I-labelled anti-CEA antibodies in a human colonic xenograft
model,” Int. J. Cancer 47, 597-602 (1991).
60
V. K. Langmuir and H. L. Mendonca, “The combined use of
131
I-labeled antibody and the hypoxic cytotoxin SR 4233 in vitro and in
viva,” Radiat. Res. 132, 351-358 (1992).
61
E. P. Malaise, B. Fertil, N. Chavaudra, and M. Guichard, “Distribution of radiation sensitivities for human tumor cells of specific histological types: Comparison of in vitro to in vivo data,” Int. J. Radiat.
Oncol. Biol. Phys. 12, 617-624 (1986).
62
W. R. Redwood, T. D. Tom, and M. Strand, “Specificity, efficacy, and
toxicity of radioimmunotherapy in erythroleukemic mice,” Cancer
Res. 44, 5681-5687 (1984).
63
W. T. Anderson-Berg, R. A. Squire, and M. Strand, “Specific radioimmunotherapy using v-labeled monoclonal antibody in erythroleukemic mice,” Cancer Res. 47, 1905-1912 (1987).
64
O. A. Gansow, M. W. Brechbiel, G. Pippin, R. Huneke, P. Squire, and
M. Strand, “Synthesis of 2-(p-SCN-benzyl)-trans-cyclohexyl-DTPA
(CHX-DTPA); Use for a-particle radioimmunotherapy with Bi-212mAb-103A in mice infected with the Rauscher leukemia virus,” J.
Nucl. Med. (Suppl.) 32, 1056 (1991).
65
R. M. Macklis, B. M. Kinsey, A. I. Kassis, J. L. M. Ferrara, R. W.
Atcher, J. J. Hines, C. N. Coleman, S. J. Adelstein, and S. J. Burakoff,
“Radioimmunotherapy with alpha-particle-emitting immunoconjugates,” Science 240, 1024-1026 (1988).
66
R. M. Macklis, W. D. Kaplan, J. L. M. Ferrara, R. W. Atcher, J. J.
Hines, S. J. Burakoff, and C. N. Coleman, “Residents essay award:
Alpha particle radio-immunotherapy: Animal models and clinical prospects,” Int. J. Radiat. Oncol. Biol. Phys. 16, 1377-1387 (1989).
67
C. C. Badger, K. A. Krohn, A. V. Peterson, H. Shulman, and I. D.
Bernstein, “Experimental radiotherapy of murine lymphoma with
“‘I-labeled anti-Thy 1.1 monoclonal antibody,” Cancer Res. 45, 15361544 (1985).
68
C. Nourigat, C. C. Badger, and I. D. Bernstein, “Treatment of lymphoma with radiolabeled antibody: Elimination of tumor cells lacking
target antigen,” J. Natl. Cancer Inst. 82, 47-50 (1990).
69
C. C. Badger, K. A. Krohn, H. Shulman, N. Flournoy, and I. D.
Bernstein, “Experimental radioimmunotherapy of murine lymphoma
with 131I-labeled anti-T-cell antibodies,” Cancer Res. 46, 6223-6228
(1986).
70
D. A. Adams, G. L. DeNardo, S. J. DeNardo, G. B. Matson, A. L.
Epstein, and E. M. Bradbury, “Radioimmunotherapy of human lymphoma in thymic, nude mice as monitored by 3 1P nuclear magnetic
resonance,” Biochem. Biophys. Res. Commun. 131, 1020-1027 (1985).
71
H. Schmidberger, D. J. Buchsbaum, B. R. Blazar, P. Everson. and D.
A. Vallera, “Radiotherapy in mice with yttrium-90-labeled anti-Ly1
monoclonal antibody: Therapy of the T cell lymphoma EL4,” Cancer
Res. 51. 1883-1890 (1991).
72
R. A. Restock, J. L. Klein, P. Leichner, K. A. Kopher, and S. E.
Order, “Selective tumor localization in experimental hepatoma by ra53
566
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
diolabeled antiferritin antibody,” Int. J. Radiat. Oncol. Biol. Phys. 9.
1345-1350 (1983).
73
J. L. Klein, T. H. Nguyen, P. Laroque, K. A. Kopher, J. R. Williams,
B. W. Wessels, L. E. Dillehay, J. Frincke, S. E. Order, and P. K.
Leichner, “Yttrium-90 and iodine-13 I radioimmunoglobulin therapy of
an experimental human hepatoma,” Cancer Res. 49, 6383-6389
(1989).
74
R. L. Vessella, V. Alvarez, R. -K. Chiou, J. Rodwell, M. Elson, D.
Palme, R. Shafer, and P. Lange, “Radioimmunoscintigraphy and radioimmunotherapy of renal cell carcinoma xenografts,” Natl. Cancer
Inst. Monogr. 3, 159-167 (1987).
75
R. K. Chiou, R. L. Vessella, C. Limas, R. B. Shafer, M. K. Elson, E.
W. Arfman, and P. H. Lange, “Monoclonal antibody-targeted radiotherapy of renal cell carcinoma using a nude mouse model,” Cancer 61,
1766-1775 (1988).
76
R. L. Vessella, P. H. Lange, D. F. Palme II, R. K. Chiou, M. K. Elson,
and B. W. Wessels, “Radioiodinated monoclonal antibodies in the imaging and treatment of human renal cell carcinoma xenografts in nude
mice,” in Targeted Diagnosis and Thempy, edited by J. D. Rodwell
(Marcel Dekker, New York, NY, 1988), Vol. I, pp. 245-282.
77
J. T. Kemshead, D. H. Jones, L. Lashford, J. Prichard, I. Gordon, F.
Breatnach, and H. B. Coakham, “131-I coupled to monoclonal antibodies as therapeutic agents for neuroectodermally derived tumors:
Fact or fiction?,” Cancer Drug Delivery 3, 25-43 ( 1986).
78
N.-K. Cheung, B. Landmeier, J. Neely, A. D. Nelson, C. Abramowsky,
S. Ellery, R. B. Adams, and F. Miraldi, “Complete tumor ablation with
iodine-131-radiolabeled disialoganglioside GDZ-specific monoclonal
antibody against human neuroblastoma xenografted in nude mice,” J.
Natl. Cancer Inst. 77, 739-745 (1986).
79
Y. -S Lee, D. E. Bullard, M. R. Zalutsky, R. E. Coleman, C. J. Wikstrand, H. S. Friedman, E. V. Colapinto, and D. D. Bigner, “Therapeutic efficacy of antiglioma mesenchymal extracellular matrix
131
I-radiolabeled murine monoclonal antibody in a human glioma xenograft model,” Cancer Res. 48, 559-566 (1988).
80
Y. Lee, D. E. Bullard, P. A. Humphrey, E. V. Colapinto, H. S. Friedman, M. R. Zalutsky, R. E. Coleman, and D. D. Bigner, “Treatment of
intracranial human glioma xenografts with 131I-labeled anti-tenascin
monoclonal antibody 81C6,” Cancer Res. 48, 2904-2910 (1988).
81
J. M. Schuster, P. K. Garg, D. D. Bigner, and M. R. Zalutsky, “Improved therapeutic efficacy of a monoclonal antibody radioiodinated
using N-succinimidyl-3-(tri-n-butylstannyl) benzoate,” Cancer Res.
51, 4164-4169 (1991).
82
M. R. Zalutsky, M. A. Noska, E. V. Colapinto, P. K. Garg, and D. D.
Bigner, “Enhanced tumor localization and in vivo stability of a monoclonal antibody radioiodinated using N-succinimidyl 3-(tri-nbutylstannyl) benzoate,” Cancer Res. 49, 5543-5549 ( 1989).
83
E. V. Colapinto, M. R. Zalutsky, G. E. Archer, M. A. Noska, H. S.
Friedman, S. Carrel, and D. D. Bigner, “Radioimmunotherapy of intracerebral human glioma xenografts with 131I-labeled F(ab’)2 fragments of monoclonal antibody Mel-14,” Cancer Res. SO, 1822-1827
(1990).
84
J. A. Williams, B. W. Wessels, M. D. Wharam, S. E. Order, P. M.
Wanek, J. K. Poggenburg, and J. L. Klein, “Targeting of human
glioma xenografts in vivo utilizing radiolabeled antibodies,” Int. J. Radiat. Oncol. Biol. Phys. 18, 1367-1375 (1990).
85
M. R Zalutsky, P. K. Garg, J. M. Schuster, S. Garg, G. E. Archer, H.
E. Fuchs, and D. D. Bigner, “Effective treatment of experimental human neoplastic meningitis (NM) with intrathecal astatine-211 monoclonal antibody (MAb),” J. Nucl. Med. (Suppl.) 32, 922 (1991).
86
H. Bender, H. Takahashi, K. Adachi, P. Belser. S. Liang, M. Prewett,
M. Schrappe, A. Sutter, U. Rodeck, and D. Herlyn, “Immunotherapy
of human glioma xenografts with unlabeled, 131I-, or 125I-labeled monoclonal antibody 425 to epidermal growth factor receptor,” Cancer
Res. 52, 121-126 (1992).
87
J. L. Humm, J. C. Roeske, D. R. Fisher, and G. T. Y. Chen, “Microdosimetric concepts in radioimmunotherapy,” Med. Phys. 20, 535-544
(1993).
88
R. L. Ceriani and E. W. Blank, “Experimental therapy of human breast
tumors with 131I-labeled monoclonal antibodies prepared against the
human milk fat globule,” Cancer Res. 48, 4664-4672 ( 1988).
89
R. L. Ceriani, E. W. Blank, J. A. Peterson, H. Battifora, and H. Singh,
“Immunotherapeutic preclinical evaluation of anti-human milk fat
globule MoAbs Mc5 and BrE-1,” Antib. Immunoconj. Radiopharm. 3, 181-198 (1990).
90
R. Senekowitsch, G. Reidel, S. Mollenstadt, H. Kriegel, and H. -W.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
566
Pabst, “Curative radioimmunotherapy of human mammary carcinoma
xenografts with iodine- 131-labeled monoclonal antibodies,” J. Nucl.
Med. 30, 531-537 (1989).
91
S. Yoneda. M. Fujisawa, J. Watanabe, T. Okabe, F. Takaku, T.
Homma, and K. Yoshida, “Radioimmunotherapy of transplanted
131
small cell lung cancer with I-labelled monoclonal antibody,” Br. J.
Cancer 58, 292-295 (1988).
92
P. L. Beaumier, P. Venkatesan, J. -L. Vanderheyden, W. D. Burgua, L.
L. Kunz, A. R. Fritzberg, P. G. Abrams and A. C. Morgan, Jr., “ 186R e
radioimmunotherapy of small cell lung carcinoma xenografts in nude
mice,” Cancer Res. 51, 676-681 (1991).
93
F. -M. Chen, D. K. Taylor, and A. L. Epstein, “Tumor necrosis treatment of ME-180 human cervical carcinoma model with 131I-labeled
TNT-l monoclonal antibody,” Cancer Res. 49, 4578-4585 (1989).
94
C. F M. Molthoff, H. M. Pinedo, H. M. M. Schluper, and E. Boven,
“Influence of dose and schedule on the therapeutic efficacy of
131
I-labelled monoclonal antibody 139H2 in a human ovarian cancer
xenograft model,” Int. J. Cancer 50, 471-480 (1992).
95
D. V. Lightfoot, K. K. Walker, G. R. Boniface, E. L. Hetherington, M.
E. Izard, and P. J. Russell, “Dosimetric and therapeutic studies in nude
153
mice xenograft models with samarium-labelled monoclonal antiAntib.
Immunoconj.
Radiopharm. 4, 319-330
body, BLCA-38,”
(1991).
96
J. Schlom, K. Siler, D. E. Milenic, D. Eggensperger, D. Colcher, L. S.
Miller, D. Houchens, R. Cheng, D. Kaplan, and W. Goeckeler, “Monoclonal antibody-based therapy of a human tumor xenograft with a
“‘Lutetium-labeled immunoconjugate,” Cancer Res. 51, 2889-2896
(1991).
97
D. J. Buchsbaum, “Experimental radioimmunotherapy: Methods to
increase therapeutic efficacy relevant to the study of human cancer,”
Antib. Immunoconj. Radiopharm. 4, 693-701 (1991).
98
D. J. Buchsbaum and T. S. Lawrence, “Tumor therapy with radiolab e l e d m o n o c l o n a l a n t i b o d i e s , ” A n t i b . I m m u n o c o n j . Radiopharm. 4, 245-272 (1991).
99
T. A. Waldmann, “Monoclonal antibodies in diagnosis and therapy,”
Science 252, 1657-1662 (1991).
100
D. M. Goldenberg, R. D. Blumenthal, and R. M. Sharkey, “Biological
and clinical perspectives of cancer imaging and therapy with radiolabeled antibodies,” Sem. Cancer Biol. 1, 217-225 (1990).
101
K. Yokoyama, J. C. Reynolds, C. H. Paik, V. K. Sood, P. J. Maloney,
S. M. Larson, and R. C. Reba, “Immunoreactivity affects the biodistribution and tumor targeting of radiolabeled anti-P97 Fab fragment,”
J. Nucl. Med. 31, 202-210 (1990).
102
M. Koizumi, K. Endo, Y. Watanabe, T. Saga, H. Sakahara, J. Konishi,
T. Yamamuro, and S. Toyama, “Pharmocokinetics of internally labeled
monoclonal antibodies as a gold standard: Comparison of biodistribution of 7 5Se-, 1 1 1In- and 1 2 5I-labeled monoclonal antibodies in osteogenie sarcoma xenografts in nude mice,” Cancer Res. 49, 1752-1757
(1989).
103
H. Sakahara, K. Endo, T. Nakashima, M. Koizumi, H. Ohta, K. Torizuka, T. Furukawa, Y. Ohmomo, A. Yokoyama, K. Okada, O.
Yoshida, and S. Nishi, “Effect of DTPA conjugation on the antigen
binding activity and biodistribution of monoclonal antibodies against
α− fetoprotein.” J. Nucl. Med. 26, 750-755 (1985).
104
S. Matzku, H. Kirchgessner, W. G. Dippold, and J. Bruggen, “Immunoreactivity of monoclonal anti-melanoma antibodies in relation to the
amount of radioactive iodine substituted to the antibody molecule,”
Eur. J. Nucl. Med. 11, 260-264 (1985).
105
R. Muraro, M. Kuroki, D. Wunderlich, D. J. Poole, D. Colcher, A.
Thor, J. W. Greiner, J. F. Simpson, A. Molinolo, P. Noguchi, and J.
Schlom, “Generation and characterization of B72.3 second generation
monoclonal antibodies reactive with the tumor-associated glycoprotein
72 antigen,” Cancer Res. 48, 4588-4596 (1988).
106
D. Colcher, M. F. Minelli, M. Roselli, R. Muraro, D. Simpson-Milenic,
and J. Schlom. “Radioimmunolocalization of human carcinoma xenografts with B72.3 second generation monoclonal antibodies,” Cancer
Res. 48, 4597-4603 (1988).
107
J. Schlom, D. Eggensperger, D. Colcher, A. Molinolo, D. Houchens. L.
S. Miller, G. Hinkle, and K. Siler, “Therapeutic advantage of highaffinity anticarcinoma radioimmunoconjugates,” Cancer Res. 52, 10671072 (1992).
108
S. M. Andrew, R. W. Johnstone, S. M. Russell, I. F. C. McKenzie, and
G. A. Pietersz, “Comparison of in vitro cell binding characteristics of
four monoclonal antibodies and their individual tumor localization
properties in mice,” Cancer Res. 50, 4423-4428 (1990).
567
Buchsbaum, Langmuir, and Wessels: Experimental radioimmunotherapy
109
D. R. McCready. C. M. Balch, I. J. Fidler. and J. L. Murray, “Lack of
comparability between binding of monoclonal antibodies to melanoma
cells in vitro and localization in vivo.” J. Natl. Cancer Inst. 81, 682-687
(1989).
110
V. J. Philben. J. G. Jakowatz. B. G. Beatty, W. G. Vlahos, R. J.
Paxton, L. E. Williams, J. E. Shively, and J. D. Bratty, “The effect of
tumor CEA content and tumor size on tissue uptake of indium 111labeled anti-CEA monoclonal antibody,” Cancer 57, 571-576 (1986).
111
R. D. Blumenthal, R. M. Sharkey, R. Kashi, and D. M. Goldenberg,
“Comparison of therapeutic efficacy and host toxicity of two different
131
I-1abelled antibodies and their fragments in the GW-39 colonic cancer xenograft model,” Int. J. Cancer 44, 292-300 (1989).
112
R. D Blumenthal, R. M. Sharkey, R. Kashi, A. M. Natale, and D. M.
Goldenberg, “Influence of animal host and tumor implantation site on
radioantibody uptake in the GW-39 human colonic cancer xenograft,”
Int. J. Cancer 44, 1041-1047 (1989).
113
T. R Shockley, K. Lin, C. Sung, J. A. Nagy, R. G. Tompkins, R. L.
Dedrick, H. F. Dvorak, and M. L. Yarmush, “A quantitative analysis
of tumor specific monoclonal antibody uptake by human melanoma
xenografts: Effects of antibody immunological properties and tumor
antigen expression levels,” Cancer Res. 52, 357-366 (1992).
114
G. Rowlinson, F. Balkwill, D. Snook, G. Hooker, and A. A. Epenetos,
“Enhancement by y-interferon of in vivo tumor radiolocalization by a
monoclonal antibody against HLA-DR antigen,” Cancer Res. 46,
6413-6417 (1986).
115
F. Guadagni, J. Schlom, S. Pothen, S. Pestka, and J. W. Greiner,
“Parameters involved in the enhancement of monoclonal antibody targeting in vivo with recombinant interferon,” Cancer Immunol. Immunother. 26, 222-230 (1988).
116
M. Matsui, S. Yoshimura, T. Nakanishi, and S. Ferrone, “Effect of
tumor size on the enhancement by y-interferon of the localization of
radiolabeled F(ab’)2 f r a g m e n t s of anti-intercellular adhesion
molecule-l monoclonal antibodies in human colon carcinoma cells
grafted in nude mice,” Cancer Res. 52, 1309-1313 (1992).
117
M. G. Rosenblum, L. M. Lamki, J. L. Murray, D. J. Carlo, and J. U.
Gutterman, “Interferon-induced changes in pharmacokinetics and tumor uptake of “‘In-labeled antimelanoma antibody 96.5 in melanoma
patients,” J. Natl. Cancer Inst. 80, 160-165 (1988).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
118
567
R. D. Blumenthal, R. M. Sharkey, R. Kashi, A. M. Natale, and D. M.
Goldenberg, “Physiological factors influencing radioantibody uptake:
A study of four human colonic carcinomas,” Int. J. Cancer 52, 1-7
(1992).
119
R. K. Jain and L. T. Baxter, “Mechanisms of heterogeneous distribution of monoclonal antibodies and other macromolecules in tumors:
Significance of elevated interstitial pressure,” Cancer Res. 48, 70227032 (1988).
120
K. Fujimoti, D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “Modeling analysis of the global and microscopic distribution of immunoglobulin G, F(ab’)2, and Fab in tumors,” Cancer Res. 49, 5656-5663
(1989).
121
R, K. Jain. “Vascular and interstitial barriers to delivery of therapeutic
agents in tumors,” Cancer Metastasis Rev. 9, 253-266 (1990).
122
R. K. Jain, “Haemodynamic and transport barriers to the treatment of
solid tumours,” Int. J. Radiat. Biol. 60, 85-100 (1991).
123
S. M. Andrew, J. G. Teh, R. W. Johnstone, S. M. Russell, R. H.
Whitehead, I. F. C. McKenzie, and G. A. Pietersz, “Tumor localization by combinations of monoclonal antibodies in a new human colon
carcinoma cell line (LIM1899),” Cancer Res. 50, 5225-5230 (1990).
124
R. D. Blumenthal, R. Kashi, R. Stephens, R. M. Sharkey, and D. M.
Goldenberg, “Improved radioimmunotherapy of colorectal cancer xenografts using antibody mixtures against carcinoembryonic antigen and
colon-specific antigen-p,” Cancer Immunol. Immunother. 32, 303-310
(1991).
125
H. Sands, P. L. Jones, S. A. Shah, D. Palme, R. L. Vessella, and B. M.
Gallagher, “Correlation of vascular permeability and blood flow with
monoclonal antibody uptake by human Clouser and renal cell xenografts,” Cancer Res. 48, 88-193 (1988).
126
R. D. Blumenthal, R. M. Sharkey, R. Kashi, and D. M. Goldenberg,
“Suppression of tumor vascular activity by radioantibody therapy: Implications for multiple cycle treatments,” Selective Cancer Therapeutics 7, 9-16 (1991).
127
D. A. Cope, M. W. Dewhirst, H. S. Friedman, D. D. Bigner, and M. R.
Zalutsky, “Enhanced delivery of a monoclonal antibody F(ab’) 2 fragment to subcutaneous human glioma xenografts using local hyperthermia,” Cancer Res. SO, 1803-1809 (1990).
An overview of imaging techniques and physical aspects of treatment
planning in radioimmunotherapy
Peter K. Leichner
University of Nebraska Medical Center, Department of Radiology, Omaha. Nebraska 68198-1045
Kenneth F. Koral
The University of Michigan Medical School, Department of Internal Medicine, Ann Arbor,
Michigan 48109
Ronald J. Jaszczak
Duke University Medical Center, Department of Radiology, Durham, North Carolina 27710
Alan J. Green
The Department of Clinical Oncology, The Royal Free Hospital School of Medicine, London, NW3 2PF
United Kingdom
George T. Y. Chen and John C. Roeske
Michael Reese/University of Chicago, Center for Radiation Therapy, Chicago, Illinois 60637
(Received 18 March 1992; accepted for publication 15 December 1992)
Planar and tomographic imaging techniques and methods of treatment planning in clinical
radioimmunotherapy are reviewed. In clinical trials, the data needed for dosimetry and treatment planning are, in most cases, obtained from noninvasive imaging procedures. The required
data include tumor and normal organ volumes, the activity of radiolabeled antibodies taken up
in these volumes, and the pharmacokinetics of the administered activity of radiolabeled antibodies. Therefore, the topics addressed in this review include: ( 1) Volume determinations of
tumors and normal organs from x-ray-computed tomography and magnetic resonance imaging,
(2) quantitation of the activity of radiolabeled antibodies in tumors and normal organs from
planar gamma camera views, (3) quantitative single-photon emission computed tomography
and positron emission tomography, (4) correlative image analysis, and (5) treatment planning
in clinical radioimmunotherapy.
1. INTRODUCTION
Knowledge of the absorbed dose in tumors and normal
tissues in clinical and experimental radioimmunotherapy
(RIT) is essential for an understanding of the underlying
radiobiological principles of tumor dose-response relationships and normal-tissue toxicity. In clinical RIT, the dose
is calculated rather than measured, and calculations are
usually based on noninvasive imaging procedures. To develop a treatment plan for an individual patient, prospective dose estimates can be made by using a tracer activity of
radiolabeled antibody to obtain phamacokinetic information prior to the administration of a larger therapeutic activity. As the pharmacokinetics depend in part on the mass
of antibody administered, the mass used for treatment
planning purposes should be nearly the same as that used
for the therapeutic administration. Additionally, dose calculations often require that tumor and normal organ
masses be estimated. This can be done by using one or
more of the tomographic methods discussed in this review.
Currently, it is impractical to determine the mass of every
organ that can be imaged for every patient. However, it is
often feasible to compute the mass of those tumors that can
be imaged, the mass of the tumor-bearing organ and the
masses of those organs that demonstrate a significant uptake of radiolabeled antibody. The dose to other organs can
be approximated by making a class dose estimate which
can, for example, be based on tabulated values of "S"
589
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
factors. 1 This is particularly important for radionuclides
that emit high-energy photons (e.g., 1 3 1I) which irradiate
the whole body.
For beta-particle dosimetry, knowledge of tumor and
normal organ volumes is not essential as long as the source
volumes are large enough so that only a negligible fraction
of the energy of the contained activity escapes. For diagnostically detectable tumors this condition is usually met.
For calculations of the mean dose only the mean value of
the concentration of activity and kinetic information are
required. However, for calculations of the variation in local
dose, knowledge of the distribution of activity in the source
volume is necessary. The quantitation of activity distributions in tumors is an area of considerable current research
interest.
Even after all methods of quantitation have been used,
the information about the spatial distribution and temporal
activity of radiolabeled antibodies in patients is rather limited. It is, therefore, necessary to interpolate and extrapolate the available information and construct a model so
that dose calculations can be carried out. In this sense, the
dose is calculated for a model rather than the patient. 2 The
overall effort in RIT dosimetry and treatment planning is
to make the model resemble the patient as much as possible.
In the past decade, much work has been done to develop
methodology, computer algorithms and software for quantitative imaging and image analysis to generate the information required for dosimetry in RIT and the development
0094-2405/93/020569-l0$01.20
© 1993 Am. Assoc. Phys. Med.
569
570
Leichner et al.: imaging techniques and treatment planning in radioimmunotherapy
of better models. The principal purpose of this review is to
summarize these developments so that they will become
more readily accessible to those who have an interest in or
are entering the field of radioimmunotherapy. The body of
this review is organized into five sections: (1) volume determinations from computed tomography (CT) and magnetic resonance (MR) scans, (2) activity quantitation
from planar gamma camera views, (3) quantitative singlephoton emission computed tomography (SPECT) and
positron emission tomography (PET) of radiolabeled antibodies, (4) correlative image analysis, and (5) treatment
planning in RIT. The presentation of this material is intended for the nonspecialist and is intentionally nonmathematical. For an in-depth understanding of any of the topics covered, the reader is referred to the literature cited.
A. Volume determinations from CT and MR scans
In the context of RIT, tumor and normal organ volume
computations are used for two purposes: dosimetry and
followup studies of patients to assess tumor response to
therapy. Although normal-organ volume computations
had been carried out by several investigators, 3-5 hepatic
tumor volume determinations from CT scans were developed independently by Moss et al. 6 and Leichner et al.7
Similar volume determinations for pheochromocytoma tumors were later made by Koral et al. 8 These methods were
labor intensive and slow because regions of interest (ROIs)
corresponding to tumor and normal tissues were generated
manually.
Volume computations were automated to some extent
by Yang et al.9 who have described interactive computer
software for generating ROIs in transverse CT slices of
patients with primary hepatic cancers. This method required an operator to specify lower and upper CT numbers
for boundary pixels of the liver and define a “seed pixel”
within the liver for a computer search of the first boundary
pixel. After the first boundary pixel was located, nearest
neighboring pixels were analyzed by the computer software
for the same boundary condition. In this manner, a connecting vector was specified for the first and second pixels.
This process was repeated until a complete ROI was traced
and displayed on a computer graphics work station. If the
computer went astray, the operator eliminated the incorrect portion of the ROI interactively. Discrimination between normal liver and tumor was achieved using a histogram method. Histograms of CT number distributions
within each ROI were obtained. However, individual histograms did not contain sufficient statistical information to
distinguish between tumor and normal liver. Global histograms were, therefore, generated by summing over individual histograms. The global histograms were analyzed by
fitting them to the sum of three Gaussian distribution functions. Threshold CT numbers for assigning volume elements (voxels) to either tumor or normal tissues were determined in this manner. Tumor and normal liver volumes
were computed by summing over the corresponding voxels.
Although the computer software was initially developed
for volume computations from CT examinations of patients with primary hepatic cancers, it has been generalized
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
570
to include MR scans and applied to volumetric analyses of
diverse cancers and benign lesions. 10,11 Comparison of CTbased volume computations of liver tumors and normal
liver with autopsy data for four patients demonstrated that
computations were accurate to within 2.0%-6.4%.1 2
As discussed by Udupa, 1 3 volume determinations from
transverse CT and MR slices represent only one aspect of
image segmentation in the field of three-dimensional (3D)
imaging in medicine. It is anticipated that 3D imaging will
play an important future role in improving dosimetry and
treatment planning in clinical RIT.
B. Activity quantitation from planar gamma camera
views
The most widely used methods for quantitating tumor
and normal organ uptake of radiolabeled antibodies are
based on conjugate (180-deg opposed) gamma camera
views. Two methods have been and are used in clinical
RIT. One of these was introduced by Sorenson 14 and further developed by Thomas et al. 15,16 It requires the acquisition of a transmission scan and conjugate-view count
rates for the quantitation of activity. This approach was
adopted by Leichner et al. 7 to estimate the activity of
131
I-labeled antiferritin in the tumor and liver of patients
with hepatoma. In view of the large tumor and liver volumes and the variation of body thickness over these volumes, a pixel-by-pixel attenuation correction was included
in a computer program for activity calculations. For
smaller tumors in locations where body thickness does not
vary greatly, regional attenuation correction should be satisfactory. The same method was used by Hammond et al. 17
to quantitate the distribution of 1 3 1I-labeled F (ab’)2 fragments of monoclonal antibody in humans. These authors
evaluated the validity of this method in phantom studies
using a fillable, tissue-equivalent organ-scanning phantom
with tumors and organs of various sizes. Less than 10%
error was found in quantitating 1 3 1I activities in a 4-cmdiam lesion. However, in a 2-cm tumor the error was
greater than 21%. Similar results were obtained by Eary
et al.18 in a study using phantoms and dogs.
A variation of the conjugate-view method was developed by Wu and Siegel. 1 9 This technique also requires
count rates for opposing gamma camera views, but the
need for a transmission scan is obviated by measuring the
buildup factor. The buildup factor results from the increase
in transmission under broad-beam conditions in clinical
nuclear medicine. It depends on photon energy, source geometry, collimator, and other measurable parameters. By
making careful measurements of the buildup factor, these
authors demonstrated improved accuracy in quantitating
99m
Tc activities, as compared to the transmission method.
More recently, Siegel et al. 2 0 have used the buildup factor
method to quantitate the pharmacokinetics of 131 I-labeled
monoclonal antibodies in patients with B-cell lymphomas.
Although the results obtained in phantom studies have
demonstrated the validity of the conjugate-view approach,
the errors in patient measurements are likely to be significantly greater than phantom results indicate. In part, this
is due to the fact that intravenous administrations of cur-
571
Leichner et al.: lmaging techniques and treatment planning in radioimmunotherapy
rently available radiolabeled antibodies result in a systemic
distribution, with blood pool and liver activities that can
persist for days post injection. Consequently, there is a
superposition of activities that is difficult to resolve in planar images. On the other hand, if the tumor-to-blood and
tumor-to-normal tissue ratios are sufficiently high, measurement errors will be reduced. There are, however, two
additional problems associated with planar imaging that
can best be resolved with emission tomographic methods.
As stated previously, planar gamma camera images do not
provide the volumetric information needed for dosimetry.
Volumes obtained from CT and MR scans are in most
cases used in radiation absorbed-dose calculations. However, CT- and MR-derived volumes need not necessarily be
the same as the volumes in which radiolabeled antibodies
localize (localization volumes) because the physiological
uptake of antibodies may not correspond exactly to the
anatomical configuration of an organ or tumor. The second
problem is that planar images do not provide sufficient
information about the distribution of activity within an
organ or tumor. Therefore, only the mean value of the
absorbed dose can be calculated. This may be an overestimate in hypoxic or necrotic regions at the core of a tumor
and an underestimate at the periphery where the dose may
be significantly higher than the mean. To improve dosimetry in clinical RIT, it is important that improvements in
quantitative emission tomography continue to be pursued.
C. Quantitative SPECT and PET imaging of
radiolabeled antibodies
The long-term goals of quantitative emission-computed
tomography (ECT) include: (1) the determination of localization volumes corresponding to tumors and normal
organs, (2) measurements of the distribution and range of
radiolabeled antibody activities within large tumors, and
(3) the measurement of activity concentration within as
small an anatomic ROI as possible. The achievement of
these goals is to a large extent governed by the physical
characteristics of the imaging system, the emission characteristics of radionuclides, the reconstruction algorithm employed, and the method of data analysis (e.g., definition of
ROIs).
Physical factors that affect quantitative SPECT have
been discussed by Jaszczak et al. 21 and perhaps the most
important of these are: (1) scatter and attenuation corrections, (2) limited spatial and energy resolutions of gamma
cameras, (3) septral penetration within conventional collimators by high-energy photons (e.g., 1 3 1I), and (4) statistical noise resulting from low count densities.
For SPECT, the spatial resolution is primarily determined by the collimator selected and the radius of rotation
used. The collimator also determines the geometric sensitivity or the number of gamma photons that will be detected and, hence, the statistical fluctuations (“noise”)
that will result in the reconstructed image. The intrinsic
resolution of a NaI scintillation crystal is about 3.5 mm;
however, at a distance of 15 cm from the camera surface,
the geometric resolution of a high-resolution collimator is
approximately 8 mm. Therefore, the resulting system resMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
571
olution is about 9 mm. In general, the full-width-at-halfmaximum (FWHM) of SPECT devices ranges from about
7-18 mm. For PET systems, the spatial resolution ranges
from about 6-13 mm. As a result, activity quantitation of
small tumors, such as metastatic lesions, by ECT methods
may be subject to large errors.
One approach to correct for Compton scattering in
SPECT is based on the method proposed by Jaszczak
et a1.22 This approach requires the acquisition of two planar projection data sets, one in the photopeak of the radionuclide and the other suitably windowed to image Compton scattered photons. A fraction (ƒ) of the scatter image
is then subtracted from the photopeak image to compensate for Compton scatter and improve quantitation. In
their original work, Jaszczak et al. 22 imaged a 9 9 m Tc line
source in air and water, and from the reconstructed photopeak and scatter images determined a value of ƒ=0.5.
23,24
demonstrated in phantom
Subsequently, Koral et al.
99m
131
studies with Tc and I as imaging agents that the value
off depends on a number of parameters. Using 9 9 mTc and
a particular algorithm and ROI, ƒ was independent of
source location and background activity.
The Compton scatter subtraction method was employed
by Green et al. 2 5 in phantom and clinical studies with
131
I-labeled monoclonal anti-CEA. Energy windows were
set at 364 keV±10% for the photopeak and 277 keV
± 18% for the scatter window. With these window settings, the count rates for the photopeak and scatter images
were the same. The gamma camera employed by Green
et al. was equipped with a 400-keV high-resolution collimator, and the system was calibrated in a series of phantom studies. The reconstruction algorithm included an attenuation correction using the method of Chang. 26 F o r
their gamma camera system and reconstruction algorithm
used, Green et al. determined that ƒ=0.54, was optimal
for 1 3 1I which is quite close to that obtained by Jaszczak
et al.22 for 9 9 m Tc. In clinical studies with 1 3 1I anti-CEA,
Green et al. validated scatter-corrected SPECT by estimating the activity concentration in the heart obtained from
ROIs and comparing it to the activity in blood samples.
This yielded a correlation coefficient of 0.96. Additionally,
scatter-corrected SPECT was compared with the transmission conjugate-view method by measuring the activity in
the liver and spleen. Planar imaging resulted in significantly higher values than SPECT for the spleen but
showed no significant difference for the liver. This is consistent with the statements made earlier that the activity in
a small tumor or organ is likely to be overestimated if it is
surrounded by underlying and overlying activity.
131
SPECT quantitation of I has also been reported by
27
Israel et a1. who used filtered backprojection to generate
tomographic slices. SPECT studies were validated in a series of phantom measurements and in patients by measuring bladder urine concentrations. A different approach to
quantitative SPECT was adopted by Denardo et al. 28 who
used an empirical method of scatter correction for 123 I and
111
In. These authors generated a post reconstruction matrix using a linear attenuation coefficient that varied with
the distance of pixels from the boundary. This removed
572
Leichner et al.: Imaging techniques and treatment planning in radioimmunotherapy
scattered photons and image counts in transverse slices
were related to the counts from an equivalent source in air.
There is considerable interest in developing special image processing techniques for quantitative imaging of radiolabeled antibodies29-31 and improved reconstruction algorithms to more accurately compensate for scatter,
attenuation, and collimator blur.32-34 An analysis of four
intrinsic attenuation correction methods by Glick et al. 3 5
has shown that of the methods studied, those developed by
Bellini et a1.33 and Hawkins et al. 34 have the least nonstationary 3D modulation transfer functions and 3D pointspread function with minimal noise amplification. For a
uniform attenuation medium, these two algorithms are
good choices when post-reconstruction filtering is considered. Furthermore, the intrinsic reconstruction algorithm
described by Hawkins et al. 34 has been validated in phantom studies36 with nonuniform activity distributions of
99m
Tc and 1 1 1In and for 1 1 1In-labeled antibodies in the livers of beagle dogs.37 Preliminary data obtained for patients
who were administered 1 1 1 In- or 1 3 1 I-labeled antibodies
have shown that this algorithm yields activity concentrations (Bq/ml) that are the same as those in patients’ tissue
samples. 38 Much interest is also being shown in maximum
likelihood-expectation maximization (ML-EM) reconstruction algorithms.39,40 Recent work has demonstrated
that these techniques can result in smaller relative noise
magnitude as compared to filtered back projection 3 0’ 31 and
produce fewer artifacts.4 1’ 4 3 Additionally, there are ongoing efforts in image reconstruction to use a priori information concerning the source. 44,45 These approaches have the
potential of significantly improving quantitative SPECT in
clinical studies.
Although the emphasis in this review is on recent developments in imaging related to clinical RIT and radioimmunodiagnosis (RAID), quantitative SPECT has been
studied by many investigators, 46-54 and it is, in part, their
work that has provided the foundation for the ongoing
efforts discussed above.
In addition to the development of improved reconstruction algorithms, progress has been made in developing better imaging systems. The resolution and sensitivity of
SPECT devices can be improved simultaneously by using
specially designed collimators55-59 and SPECT systems
having larger detector areas. 60-65
The common denominator of all the quantitative
SPECT studies cited is careful validation of the methodology used to extract quantitative information from reconstructed images. Validation is absolutely essential because
different SPECT devices and reconstruction algorithms
have a profound effect on the quality of reconstructed images.
The use of PET devices in oncologic imaging has been
limited in the past but there is growing interest in the
application of positron emitters in the diagnosis and treatment of cancer. As is the case for SPECT devices, there is
a variety of PET systems. Positron instrumentation has
been described in reviews by Brownell et al. 66 a n d
Ter-Pogossian. 67 PET reconstruction algorithms have, for
example, been reported by Phelps et al. 68,69 The advantages
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
572
of PET over SPECT imaging are increased spatial resolution, as discussed, and attenuation correction with a high
degree of precision. The resulting image quality is superior
to that achieved with SPECT. The growing interest in oncologic PET imaging is, in part, related to the increasing
number of whole-body devices and the fact that PET studies have the potential to provide the physiological information for the diagnosis of cancer based on altered tissue
metabolism and to monitor the effects of therapy on metabolism. A detailed description of the applications of PET
in oncologic imaging has recently been given by Strauss
and Conti.70 In the field of clinical RIT, Larson et al. 71 and
Pentlow et al.72 have reported PET scanning of 124 I-labeled
3F8 monoclonal antibody as a method of tumor dosimetry
and treatment planning prior to the administration of
131
I-3F8 for the therapy of neuroblastoma. These authors
conclude that this technique shows promise for determining the radiation-absorbed dose for 131 I-3F8 RIT.
D. Correlative image analysis
Three-dimensional (3D) representations of 2D tomographic data and correlative analysis of CT, MR, PET, and
SPECT scans have become increasingly important in medicine. Work in 3D rendering of bony structures carried out
by Hemmy et al.73 and Herman et al.74 was based on CT
scans and proved clinically useful in craniofacial surgery
and orthopedics. In this early work only bony surfaces
were visualized and soft-tissue information was lost or not
used in the process of reformatting the CT data. However,
subsequent investigations by Goldwasser et al., 75 Jackel, 7 6
Lenz et al.,7 7 and Hoehne et al.78 have addressed the software and hardware problems of 3D displays that preserve
the gray-scale information of the original data. These efforts have produced display systems that are generally applicable to diagnostic radiology and surgical planning. In
the past few years, computer systems for 3D displays of
medical images have become commercially available.
Three-dimensional correlative imaging has been employed by several authors in the treatment of brain tumors
and neurological disorders. For example, Schad et al. 7 9
have used 3D correlative imaging in radiotherapy treatment planning of brain tumors. Their technique required a
stereotactic head holder made of wood to precisely and
reproducibly localize the target volume during CT, MR,
and PET imaging and radiotherapy. Magnetic resonance
scans were obtained in addition to CT because of MRs
superior s o f t t i s s u e c o n t r a s t . F o r P E T i m a g i n g ,
( 1 8F)-2-deoxyglucose (FDG) and H 2 1 5O tracers were used
to assess the rate of glucose utilization and perfusion of
brain tumors. The target volume was defined by manually
drawing ROIs in tomographic slices and subsequently generating 3D displays of this volume and the patients’ head
contour. Others, for example, Vannier and Gayou, 80 have
advocated computer solutions for automated registration
of multimodality images because these are noninvasive and
can be applied retrospectively.
One such approach has been described by Pelizzari
et al81 who generated surface models of the head based on
CT, PET, and MR scans to derive the coordinate transfor-
573
Leichner et al.: Imaging techniques and treatment planning In radioimmunotherapy
mations required for 3D congruence of these models. After
the transformations were determined, volume information
could be transferred between scans and displayed three
dimensionally or in tomographic slices. As the work of
Levin et al.82 has shown, this technique can result in striking 3D and 2D representations of MR and PET images
that are of clinical importance in planning brain surgery.
Although correlative imaging has not yet been employed in
the RIT of malignant brain tumors, it is quite possible that
MR and PET imaging would be useful in assessing tumor
response to therapy. For example, FDG and H 2 1 5O PET
studies following RIT could be used to monitor changes in
glucose utilization and perfusion and related to possible
anatomic changes in MR images.
Correlative CT-SPECT imaging was used by Kramer
et al.83 to identify anatomic sites corresponding to uptake
of 1 1 1In-labeled monoclonal anti-CEA ( 1 1 1In-MAb) in patients with colorectal adenocarcinoma. SPECT and CT
studies of the abdomen were acquired for each patient. In
the initial studies, 5 7Co point sources were placed at anatomic landmarks to provide coordinate information for
subsequent matching of CT and SPECT data sets. In later
studies, flexible 57Co line sources were used because these
yielded information about the shape and location of the
body surface in SPECT scans and permitted matching with
the body surface in CT scans. For this reason, separate
SPECT acquisitions were made for 1 1 1 In-MAb and the
57
Co markers. Transaxial CT and SPECT slices were reformatted into a common matrix size. Initial matching of
pairs of CT and SPECT slices was achieved by identifying
coordinates belonging to anatomic landmarks (CT) and
markers (SPECT). If necessary, CT slices were translated
and rotated until superposition of anatomic landmarks and
the corresponding 57Co markers was achieved in a “fused”
image. Once the CT and SPECT studies had been
matched, ROIs in SPECT slices representing tissue uptake
of 1 1 1In-MAb were transferred to CT slices. Correlative
CT-SPECT imaging enabled identification of anatomic
sites of tumor uptake of 1 1 1 In-MAb as well as nonspecific
tissue accumulation and confirmed a small lesion detected
by CT.
Although the work of Kramer et al. was qualitative in
that quantitation of the activity of 1 1 1In-MAb was not the
goal of their investigation, it opens up the possibility of
relating quantitative SPECT to anatomical imaging modalities (CT and MRI) for dosimetry and treatment planning
in clinical RIT. In preliminary work, Koral et a. 84 u s e d
five point markers for superimposing SPECT and CT images of a lymphoma RIT patient. Patient dosimetry was
based on volumes of interest transferred from CT to
SPECT after superposition had been achieved.
E. Treatment planning
Treatment planning relies on quantitative imaging, radiation absorbed-dose estimates, and biological input parameters for the development of treatment strategies. An
example of a biological input parameter is hematopoietic
toxicity, often the dose-limiting toxicity in clinical RIT.
The development of clinical protocols for the treatment of
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
573
hepatoma with 131 I- and 9 0Y-labeled polyclonal antiferritin
IgG is an example of how dosimetric and medical considerations can be used in clinical RIT. 85,86 In a Phase I-II
Trial, administered activities of “‘I-labeled antiferritin
ranged from 1.18 to 5.81 GBq. It was determined that an
administered activity of 1.11 GBq “saturated” most hepatomas and that larger activities did not result in increased tumor uptake. Additionally, an evaluation of the
hematopoietic toxicity associated with the intravenous injection of 1 3 1I antiferritin IgG demonstrated that an activity of 1.85 GBq was well tolerated by most patients. 8 7
These considerations led to a treatment regimen of administering 1.11 GBq on Day 0 and 0.74 GBq on Day 5. The
time interval between administrations was approximately
equal to the effective half-life of 131 I antiferritin IgG in the
hepatoma. The second injection, therefore, “re-saturated”
or maximized the activity and dose rate in the tumor and
led to an increase in the integrated absorbed dose. Bone
marrow toxicity has remained a limiting factor in RIT. In
a effort to alleviate marrow suppression, Meredith et al. 8 8
used fractionation in the administration of radiolabeled antibodies in patients with metastatice colon cancer. Up to
three weekly fractions were used to administer a total activity of 1.33 GBq of 131I-labeled antibodies. These authors
reported only a minimal reduction in bone marrow toxicity
for this fractionation schedule and the antibody and radiolabel used. To date, the most promising responses to RIT
have been achieved by Press et al. 89 through the use of
large a d m i n i s t e r e d a c t i v i t i e s ( 8 . 5 8 - 2 2 . 5 G B q ) o f
131
I-labeled antibodies and autologous bone marrow transplantation in the treatment of refractory non-Hodgkin’s
lymphoma.
90
The development9 0 of Y-labeled antiferritin IgG was
based on the fact that, due to their higher energy, 9 0Y beta
particles would produce a higher absorbed-dose rate and a
more uniform absorbed-dose distribution than 1 3 1I beta
particles. Vriesendorp et al. 91 have compared two groups
of patients with refractory non-Hodgkin’s disease who
were treated with 131 I- and 9 0Y-labeled antiferritin IgG and
shown that the frequency and duration of tumor response
was significantly greater in those patients who were administered y-labeled antiferritin. An obvious disadvantage is
that 90Y cannot be imaged quantitatively and that a second
radionuclide, 111 In, has to be conjugated to the same antibody for imaging and dosimetry. A review of imaging,
dosimetry, and treatment planning for 131 I-labeled antiferritin and anti-AFP in hepatoma, 131 I-labeled anti-CEA in
intrahepatic biliary cancer, and 111 In-labeled antiferritin in
hepatoma and Hodgkin’s disease has been given by Leichner et al.1 0
The general requirements for treatment planning is clinical RIT have been discussed by DeNardo et al. 92 A computer program and imaging methodology, specifically developed for this purpose, have been described by Macey
et al.93 In this approach, a whole-body transmission image
is acquired, using a line source containing 131 I, prior to the
administration of 131 I-labeled antibodies. Following intravenous infusion of 131I-labeled MoAb, serial conjugate images of the whole-body, brain, chest, abdomen, and pelvis
574
Leichner et al.: Imaging techniques and treatment planning In radioimmunotherapy
are acquired. The activity in a tumor or normal organ is
calculated from these data by the transmission conjugateview method, previously described. Radiation absorbeddose calculations are made according to the MIRD
schema.
A computer simulation for treatment planning, applicable to RIT, has been reported by Sgouros et al. 94 In this
calculational method, it is assumed that tumor and normal
organ uptake of nonuniformly distributed radionuclides is
accurately known and that this information can be transferred readily to CT images. Radiation absorbed-dose calculations are based on independently determined cumulated activities, the corresponding CT volumes, and a
convolution of the source volume cumulated activity with
a point-source kernel. The electron-gamma shower (EGS)
Monte Carlo code, discussed elsewhere in this volume, is
used to generate point-source kernels in the form of lookup
tables. The results of absorbed-dose calculations are stored
in a two-dimensional dose matrix which is converted into a
set of color-coded isodose contours. The contours are then
displayed superimposed on CT images corresponding to
the target plane. As the point-source kernels are generated
for an infinite medium of uniform composition, tissue inhomogeneities and boundary effects, such as soft-tissue
bone interfaces, are not taken into account. However,
methods for including these effects in absorbed-dose calculations are presented in another section of this volume.
The commonality in the various approaches to treatment planning is that radiation absorbed-dose calculations
for tumors and normal tissues are made as accurately as
possible within the limitations of available imaging devices
and reconstruction algorithms for quantitative ECT. Accurate dosimetry is essential for gaining a better understanding of tumor dose-response relationships and assessments of the toxicity associated with the administration of
radiolabeled antibodies. It is anticipated that with continued progress in biotechnology, immunochemistry, quantitative imaging and dosimetry, treatment planning in clinical RIT will play an increasingly important role. To
maximize the radiation absorbed dose in tumors and reduce normal-tissue toxicity, treatment planning may include the route of administration (e.g., intravenous, intraarterial, intraperitoneal, intrapleural, etc.) a choice of
antibodies or fragments of antibodies, and a choice of radionuclides (e.g., low-energy electron or alpha emitters for
micrometastases and high-energy beta emitters for large
tumors). To optimize the therapy of primary and metastatic lesions it may, in fact, be advantageous to administer
combinations of antibodies labeled with different radionuclides. The number of permutations is potentially very
large, and it will be the objective of treatment planning to
optimize RIT for each individual patient.
II. SUMMARY AND DISCUSSION
In this overview of imaging techniques and treatment
planning in RIT, we have described the physical aspects of
these methods based principally on the recent literature. A
summary of the steps involved in quantitative imaging and
treatment planning for macroscopic tumors that can be
Medical Physics, Vol. 20, No. 2, Pt. 2. Mar/Apr 1993
574
imaged using CT, MR, or ECT is given below. We recognize that these methods are not applicable to micrometastases or circulating leukemia cells. However, there are
many ongoing clinical trials in RIT for which quantitative
imaging and treatment planning provide important information about tumor targeting, radiation-absorbed doses in
tumors and normal organs, and an assessment of response
to treatment.
A. Data acquisition and calculations prior to therapy
Radiolabeled antibody imaging using a tracer activity
before the administration of a therapeutic activity is essential to determine tumor and normal organ uptake and provide a rationale for therapy. In general, at least one and
preferably two or more SPECT or PET studies should be
acquired in addition to planar views to reliably determine
clearance rates and cumulated activities for tumors and
normal organs. The mass of antibody used in the imaging
studies should be nearly the same as that for the therapeutic administration to avoid differences in pharmacokinetics
due to differences in administered antibody masses. In addition to ECT studies, CT or MR scans in conjunction
with correlative image analysis are important for volume
determinations and a definitive identification of anatomical
structures that show uptake of radiolabeled antibodies.
As hematopoietic toxicity is a limiting factor in RIT,
information about the marrow dose is necessary for gaining
a better understanding of the relationship between marrow
dose and toxicity in patients who may have had prior treatment with chemotherapy, radiotherapy, or a combination
of both. Activity in bone marrow can be estimated from
serial gamma camera images using a method described by
Siegel. 95 This should be compared with the activity in serial
blood samples to estimate the fraction of blood in the marrow for use in absorbed-dose calculations.
As the spatial resolution of imaging devices is limited,
image-based dosimetry provides macroscopic information
about absorbed-dose distributions. Additionally, the errors
in quantitating tumor and normal organ uptake of radiolabeled antibodies depend on the radiolabel used, the volume, and the imaging device. In a SPECT study of
111
In-labeled antibodies in the livers of beagle dogs, 37 absolute values of percent differences between autopsy data
and computed activities ranged from 2.3% to 7.5%. However, these were relatively large volumes (in the range of
400 ml) and from the discussion of the FWHM of SPECT
devices it follows that for smaller volumes the percent differences will be larger. Similarly, from the discussion of
PET devices it follows that PET imaging will provide more
accurate data than SPECT imaging of radiolabeled
antibodies. 71,72 With SPECT or PET, activity distributions
can be determined in sufficiently large tumors.” Nevertheless, the local absorbed dose on the multicellular level will
need to be determined from autoradiographs or histologic
measurements of tumor biopsies. As shown by Hui et al. 96
in a study of absorbed-dose distributions in follicular lymphoma, the local absorbed dose may vary from the average
dose by a factor of two and 70% to 80% of the tissue may
receive less than the average dose. These data are indicative
575
Leichner et al.: lmaging techniques and treatment planning in radioimmunotherapy
of the variations in absorbed dose to be expected in clinical
RIT.
For photon-emitting radionuclides (e.g., 1 3 1I) “S” values for tumors and tumor-bearing organs can be estimated
by at least two methods. A computer program developed
by Johnson9 7 accounts for the presence of tumors using
Monte Carlo calculations. These calculations were made
for spherical tumors only, and organ distortion due to the
presence of a tumor was not taken into account. A more
general approach to tumor geometry was adopted by
Stinchcomb et al.98 who calculated “S” values for tumors
and host organs on the basis of tabulated values of the
specific absorbed fractions calculated by Berger. 9 9’ 100 This
had the advantage of making calculations faster than those
based on the Monte Carlo approach. Additionally, the tumor was modeled as a rectangular solid with three shape
parameters which made this method more flexible, and
organ distortion was taken into account in the computations. By interfacing their computations with a computer
program 1 0 1 available for implementing the MIRD system,
Stinchcomb et al.98 were thus able to compute the dose to
tumors and normal organs, including the tumor-bearing
organ.
After all available methods of quantitation have been
employed and dose calculations made, medical and radiobiological considerations enter into the treatment decision.
For example, in a study of v-labeled antiferritin in patients with hepatoma,8 6 treatment was based on achieving a
calculated minimum initial tumor dose rate of 10 cGy/h. If
calculations indicated that this minimum dose rate was not
achievable at a given level of administered activity, patients
were entered into other protocols. In other studies, administered activities were fractionated because of limited tumor uptake85 or in an effort to reduce marrow toxicity.” If
marrow toxicity is circumvented by autologous bone marrow transplantation, second-organ toxicity may become
the constraint in administered activity. 8 9
B. Data acquisition and calculations following the
therapeutic administration
The radionuclide imaging that is feasible after the administration of a therapeutic activity of radiolabeled antibodies depends on the radiolabel used and the administered
activity itself. Although it has been suggested by Clarke
et al.102 that quantitative bremsstrahlung imaging is feasible for therapeutic activities of 90Y-labeled antibodies, this
is an as yet untried method. A difficulty is that if
“‘In-labeled antibodies are used for treatment planning, a
large fraction of the bremsstrahlung spectrum will be obscured by the photopeaks and Compton scattered photons
of 111 In. For radionuclides that emit beta particles and also
have photopeaks (e.g., 1 3 1I, 6 7Cu, 1 8 6Re, 1 8 8Re) imaging is
constrained only by dead time considerations of gamma
cameras. This problem is more severe for 131 I than for the
other radionuclides mentioned because of the relatively
large abundance of the 364-keV photons (0.82/dis) of 131I.
For most commercially available large-field-of-view
gamma cameras, a total-body activity of approximately
1.11-1.85 GBq of 1 3 1 I appears to be the upper limit for
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
575
imaging. The importance of imaging therapeutic activities
lies in monitoring therapy and testing whether scaling from
the tracer to the therapeutic activity introduced changes in
the pharmacokinetics and hence the absorbed dose. In addition to imaging, blood and urine samples are obtained to
determine clearance rates and test for immune complexes,
anti-antibodies and metabolites.
Followup CT or MR scans to assess tumor response to
therapy are currently employed by most investigators as an
objective means of determining this important parameter.
ACKNOWLEDGMENTS
One of the authors (PKL) acknowledges support under
DOE Grant No. DE-FG02-91ER61195. Co-author KFK
acknowledges support of PHS Grant No. RO1-CA38790
awarded by the National Cancer Institute. Co-author RJJ
acknowledges support of DOE Grant No. DE-GF0591ER60894 and PHS Grant No. RO1-CA33541 awarded
by the National Cancer Institute.
1
W. S. Snyder, M. R. Ford, G. G. Warner, and S. B. Watson, "'S,'
Absorbed dose per unit cumulated activity for selected radionuclides
and organs,” Medical Internal Radiation Dose (MIRD) Committee,
Pamphlet No. 11 (The Society of Nuclear Medicine, NY, 1975).
2
R. Loevinger, “Distributed radionuclide sources,” in Radiation Dosimetry, edited by F. H. Attix and E. Tochilin (Academic, NY, 1969), Vol.
3.
3
S. B. Heymsfield, T. Fulenwider, B. Nordinger, R. Barlow, P. Sones,
and M. H. Kutner, “Accurate measurement of liver, kidney, and spleen
volume and mass by computerized axial tomography,” Ann. Int. Med.
90, 185-187 (1979).
4
J. M. Henderson, S. B. Heymsfield, J. Horowitz, and M. H. Kutner,
“Measurement of liver and spleen volume by computed tomography,”
Radiology 141, 525-527 (1981).
5
A. A. Moss, M. A. Friedman, and A. C. Brito, “Determination of liver,
kidney and spleen volumes by compted tomography: An experimental
study in dogs,” J. Comput. Assist. Tomogr. 5, 12-14 (1981).
6
A. A. Moss, C. E. Cann, M. A. Friedman, F. S. Marcus, K. J. Resser,
and W. Berninger, “Volumetric CT analysis of hepatic tumors,” J.
Comput. Assist. Tomogr. 5, 714-718 (1981).
7
P. K. Leichner, J. L. Klein, J. B. Garrison, R. E. Jenkins, E. L. Nickoloff, D. S. Ettinger, and S. E. Order, “Dosimetry of 131I labeled antiferritin in hepatoma: A model for radioimmunoglobulin dosimetry,”
Intl. J. Radiat. Oncol. Biol. Phys. 7, 323-333 (1981).
8
K. F. Koral, X. Wang, J. C. Sisson, J. Botti, L. Meyer, S. Mallette, G.
M. Glazer, and R. S. Adler, “Calculating radiation absorbed dose for
pheochromocytoma tumors in 131-I MIBG therapy,” Int. J. Radiat.
Oncol. Biol. Phys. 17, 211-218 (1989).
9
N.-C. Yang, P. K. Leichner, E. K. Fishman, S. S. Siegelman, T. L.
Frenkel, J. R. Wallace, D. M. Loudenslager, W. G. Hawkins, and S. E.
Order “CT volumetrics of primary liver cancers,” J. Comput. Assist.
Tomogr. 10, 621-628 (1986).
10
P. K. Leichner, N.-C. Yang, B. W. Wessels, W. G. Hawkins, S. E.
Order, and J. L. Klein, “Dosimetry and treatment planning in radioimmunotherapy,” in Frontiers of Radiation Therapy and Oncology, edited by J. M. Vaeth and J. M. Meyer (Karger Verlag, Basel, Switzerland, 1990), pp. 109-120.
11
A. Rahmouni, A. Yang, C. Tempany, T. Frenkel, J. Epstein, P. Walsh,
P. K. Leichner, C. Ricci, and E. Zerhouni, “Accuracy of in-vivo assessment of prostatic volume by magnetic resonance imaging and transrectal ultrasonography,” J. Comp. Assist. Tomogr. 16, 935-940
(1992).
12
D. S. Ettinger, P. K. Leichner, S. S. Siegelman, E. K. Fishman, J. L.
Klein, and S. E. Order, “Computed tomography assisted volumetric
analysis of primary liver tumor as a measure of response to therapy,”
Am. J. Clin. Oncol. 8, 413-418 (1985).
13
J. K. Udupa, “Computer aspects of 3D imaging in medicine: A tutorial” in 3D Imaging in Medicine, edited by J. K. Udupa and G. T.
Herman (CRC, Boca Raton. FL, 1991).
576
Leichner et al.: Imaging techniques and treatment planning in radioimmunotherapy
14
J. A. Sorenson, “Quantitative measurement of radioactivity in-vivo by
whole-body counting, ” in Instrumentation in Nuclear Medicine, edited
by G. J. Hine and J. A. Sorenson (Academic, New York, NY, 1974),
Vol. 2.
15
S. R. Thomas, H. R. Maxon, and J. G. Kereiakes, “In-vivo quantitation
of lesion radioactivity using external counting methods,” Med. Phys. 3,
253-255 (1976).
16
S. R. Thomas, R. C. Purdom, J. G. Kereiakes, M. J. Gelfond, and H.
R. Maxon. "Dose to the liver and spleen in pediatric patients undergoing technetium -99m sulfur colloid scans," Radiology 133,465-467
(1979).
17
N. D Hammond, P. J. Moldofsky, M. R. Beardsley, and C. B. Mulhem, Jr., “External imaging techniques for quantitation of distribution
of I-131 F(ab’) fragments of monoclonal antibody in humans,” Med.
Phys. 11, 778-783 (1984).
18
J. F. Eary, F. L. Appelbaum, L. Durack, and P. Brown, “Preliminary
evaluation of the opposing view method for quantitative gamma camera imaging,” Med. Phys. 16, 382-387 (1989).
19
R. K. Wu and J. A. Siegel, “Absolute quantitation of radioactivity
using the buildup factor,” Med. Phys. 11, 189-192 (1984).
20
J. A. Siegel, D. M. Goldenberg, J. A. Horowitz, R. M. Sharkey, T. C.
Hall, S. Murthy, H. Goldenberg, R. E. Lee, and L. C. Swayne, “Tumor
and organ dosimetry for I-131 labeled LL2 (EPB-2) monoclonal antibody in patients with B-cell lymphomas,” Antib. Immunoconj. Radiopharm. 4, 26 (1991).
21
R. J. Jaszczak, R. E. Coleman, and F. R. Whitehead, “Physical factors
affecting quantitative measurements using camera-based single-photon
emission computed tomography,” IEEE Trans. Nucl. Sci. NS-28,
69-80 (1981).
22
R. J. Jaszczak, K. L. Greer, C. E. Floyd, C. C. Harris, and R. E.
Coleman, “Improved SEPCT quantification using compensation for
scattered photons,” J. Nucl. Med. 25, 893-900 ( 1984).
23
K. F. Koral, F. M. Swailem, S. Buchbinder. N. H. Clinthome, W. L.
Rogers, and B. M. W. Tsui, “SPECT dual-energy window compton
correction: Scatter multiplier required for quantification,” J. Nucl.
Med. 31, 90-98 (1990).
24
K. F. Koral, F. M. Swailem, N. H. Clinthome, W. L. Rogers, and B.
M. W. Tsui, “Dual-window compton scatter correction in phantoms:
errors and multiplier dependence on energy,” J. Nucl. Med. 31, 798799 (abst.) (1990).
25
A. J. Green, S. E. Dewhurst, R. H. Begent, K. D. Bagshawe. and S. J.
Riggs, “Accurate quantification of 131I distribution by gamma camera
imaging,” Eur. J. Nucl. Med. 16, 361-365 (1990).
26
L. T. Chang, “A method for attenuation correction in radionuclide
computed tomography,” IEEE Trans. Nucl. Sci. NS-25, 638-643
(1978).
27
O. Israel, G. Iosilevsky, D. Front, L. Bettman, A. Frenkel, S. IshShalom, M. Steiner, M. Ben-Harush, and G. M. Kolodny, “SPECT
quantitation of iodine-131 concentration in phantoms and human tumors,” J. Nucl. Med. 31, 1945-1949 (1990).
28
G. L. DeNardo, D. J. Macey, S. J. Denardo, C. G. Zhang, and T. R.
Custer, “Quantitative SPECT of uptake of monoclonal antibodies,”
Semin. Nucl. Med. 19, 22-32 (1989).
29
S. J. Cullom, L. P. Clarke, B. C. Penney, M. A. King, A. V. Heal, J. A.
Madden, and M. L. Silbiger, “Importance of collimator and restoration
filter for quantitative imaging with “‘I-labeled antibody (HMFG),” J.
Nucl. Med. 30, 876 (abst.) (1989).
30
D. R. Gilland, R. J. Jaszczak, K. L. Greer, and R. E. Coleman, “Quantitative SPECT reconstruction of I-123 data,” J. Nucl. Med. 32, 527533 (1991).
31
D. R Gilland, R. J. Jaszczak, T. C. Turkington, K. L. Greer, and R.
E. Coleman. “Quantitative SPECT imaging with In-111.” IEEE Trans.
Nucl. Sci. 32, 761-766 (1991).
32
E. Tanaka, H. Toyoma, and H. Muriyama, “Convolutional image reconstruction for quantitative single-photon emission computed tomography,” Phys. Med. Biol. 29, 1489-1500 (1984).
33
S. Bellini, M. Piacentini, and C. Cafforio, “Compensation of tissue
absorption in emission tomography,” IEEE Trans. ASSP 27, 213-218
(1979).
34
W. G Hawkins, P. K. Leichner, and N. C. Yang, “The circular harmonic transform for SPECT and boundary conditions on the fourier
transform of the sinogram,” IEEE Trans. Med. Imag. 7, 135-148
(1988).
35
S. J. Glick, W. G. Hawkins, M. A. King, B. C. Penney, E. J. Soares,
and C. L. Byrne, “The effect of intrinsic attenuation correction meth-
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
576
ods on the stationarity of the 3-D modulation transfer function of
SPECT,” Med. Phys. 19, 1105-1112 (1992).
36
W. G. Hawkins, N.-C. Yang, and P. K. Leichner, “Validation of the
circular harmonic transform (CHT) algorithm for quantitative
SPECT,” J. Nucl. Med. 32, 141-150 (1991).
37
P. K. Leichner. H. M. Vriesendorp, W. G. Hawkins, S. M. Quadri,
N.-C. Yang, R. L. Stinson, D. M. Loundenslager, T. L. Frenkel, X.
Chen, and J. L. Klein, “Quantitative SPECT for In-111 antibodies in
the livers of beagle dogs,” J. Nucl. Med. 32, 1442-1444 (1991).
38
P. K. Leichner, W. G. Hawkins, and N.-C. Yang, “Quantitative
SPECT in radioimmunotherapy,” Antib. Immunoconj. and Radiopharm. 4, 25 (abst.) (1991).
39
K. Lange and R. Carson, “EM reconstruction algorithms for emission
and transmission tomography,” J. Comput. Assist. Tomogr. 8, 306-316
(1984).
40
L. A. Schepp, and Y. Vardi, “Maximum likelihood reconstruction for
emission tomography,” IEEE Trans. Med. Imag. MI-l, 113-122
(1982).
41
A. J. Green, R. H. J. Begent, and K. D. Bagshawe, “Maximum likelihood reconstruction incorporating line spread function data,” (abst.)
Eur. J. Nucl. Med. 14, 226 (1988).
42
B. C. Penny, N. Rajechan, C. L. Bume, and M. A. King, “Maximum
likelihood SPECT reconstruction: Use of a 2D blurring model,” J.
Nuc. Med. 32, 936 (1991).
43
A. J. Green, D. E. Lane, R. H. J. Begent, and K. D. Bagshawe, “A new
projector/backprojector for improved image reconstruction with high
energy gamma emitters,” (abst.) Antib. Immunoconjug. and Radiopharm. 4, 58 (1991).
44
Z. Liang, R. J. Jaszczak, and K. Greer, “On Bayesian image reconstructions from projections: Uniform and nonuniform a priori source
information.” IEEE Trans. Med. Imag. 8, 227-235 (1989).
45
Z. Liang, R. Jaszczak, R. Coleman, and V. Johnson, “Simultaneous
reconstruction, segmentation, and edge enhancement of relatively
piecewise continuous images with intensity-level information,” Med.
Phys. 18, 394-401 (1991).
46
L. G. Strauss, J. H. Clorius, F. Frank, and G. Van Kaick, “Singlephoton emission-computerized tomography (SPECT) for estimates of
liver and spleen volume,” J. Nucl. Med. 25, 81-85 (1984).
47
W. N. Tauxe, F. Soussaline, and A. Todd-Pokropek, “Determination
of organ volume by single-photon emission computed tomography,” J.
Nucl. Med. 23, 984-987 (1982).
48
R. J. Jaszczak, F. R. Whitehead, C. B. Lim, and R. E. Coleman,
“Lesion detection with single-photon emission computed tomography,” J. Nucl. Med. 23, 97-102 (1982).
49
D. Osborne, R. Jaszczak, R. E. Coleman, K. Greer, and M. Lischko,
“In-vivo regional quantitation of intrathoracic Tc-99m using SPECT:
Concise communication,” J. Nucl. Med. 23, 446-450 (1982).
50
B. Soderberg, M. Dahlborn, and J. Virgin, “Determination of organ
volume by single-photon emission tomography,” J. Nucl. Med. (letter)
24, 1197 (1983).
51
L T. Kircos, J. E. Carey, and J. W. Keyes, “Quantitative organ visualization using SPECT,” J. Nucl. Med. 28, 334-341 (1987).
52
K. H. Lee, H. T. H. Liu, D. C. P. Chen, M. E. Siegel, and S. Ballard,
“Volume calculation by means of SPECT: Analysis of imaging acquisition and processing factors,” Radiology 167, 259-262 ( 1988).
53
G. T. Gullberg and T. F. Budinger, “Three-dimensional reconstruction
in nuclear medicine emission imaging,” IEEE Trans. Nucl. Sci. NS-21,
2-20 (1974).
54
A. M. Cormack, “Reconstruction of densities from their projections
with applications in radiological physics,” Phys. Med. Biol. 18, 195207 (1973).
55
R. J. Jaszczak, L. T. Chang, and P. H. Murphy, “Single-photon emission computed tomography using multi-slice fan beam collimators,”
IEEE Trans. Nucl. Sci. NS-26, 610-619 (1979).
56
B. M. W. Tsui, G. T. Gullberg, and E. R. Edgarton, “Design and
clinical utility of a fan-beam collimator for SPECT imaging of the
head,” J. Nucl. Med. 27, 810-819 (1986).
57
R. J. Jaszczak, C. E. Floyd, S. H. Mangles, K. L. Greer, and R. E.
Coleman, “Cone beam collimation for single-photon emission computed tomography: Analysis, simulation, and image reconstruction using filtered backprojection,” Med. Phys. 13, 484-489 (1987).
58
E. G. Hawman and J. Hsieh, “An astigmatic collimator for highsensitivity SPECT of the brain,” J. Nucl. Med. 27, 930 (1986).
59
N. Nohara, H. Murayama, and E. Tanaka, “Single-photon emission
577
Leichner et al.: Imaging techniques and treatment planning In radioimmunotherapy
tomography with increased sampling density at central region field-ofview,” IEEE Trans. Nucl. Sci. NS-34, 359-363 (1987).
60
R. J. Jaszczak, L. T. Chang, N. A. Stein, and F. E. Moore, “Wholebody single-photon emission computed tomograph using dual, largefield-of-view scintillation cameras,” Phys. Med. Biol. 24, 1123-I 143
(1979).
61
C. B. Lim, L. T. Chang, and R. J. Jaszczak, “Performance analysis of
three camera configurations for single-photon emission computed tomography,” IEEE Trans. Nucl. Sci. NS-27. 559-568 (1980).
62
S. Genna and A. Smith, “The development of ASPECT, an annular
single-crystal brain camera for high-efficiency SPECT,” IEEE Trans.
Nucl. Sci. NS-35, 654-658 (1988).
63
S. C Moore, M. D. Doherty, R. E. Zimmerman, and B. L. Homan,
“Improved performance from modifications to the multidetector
SPECT brain scanner,” J. Nucl. Med. 25, 688-691 (1984).
64
E. M. Stokley, E. Sveinsdottir, N. A. Lassen, and P. Rommer, “A
single-photon dynamic computer-assisted tomograph (DCAT) for imaging brain function in multiple cross sections,” J. Comput. Assist.
Tomogr. 4, 230-240 (1980).
65
W. L Rogers, N. H. Clinthome, and J. Stamos, “Performance evaluation of SPRINT, a single-photon ring tomograph for brain imaging,”
J. Nucl. Med. 25, 1013-1018 (1984).
66
G. L. Brownell, J. A. Correia, and R. G. Zamenhof, “Positron instrumentation,” in Recent Advances in Nuclear Medicine, edited by J. H.
Lawrence and T. F. Budinger (Grune and Stratton, New York, NY,
1978).
67
M. M. Ter-Pogossian, “Positron emission tomograph instrumentation,” in Positron Emission Tomography (Alan R. Liss, Inc., New
York, NY, 1985).
68
M. E Phelps, E. J. Hoffman, N. A. Mullani, and M. M. Ter-Pogossian,
“Application of annihilation coincidence detection to transaxial reconstruction tomography,” J. Nucl. Med. 16, 210-224 (1975).
69
M. E. Phelps, E. J. Hoffman, S. C. Huang, and D. E. Kuhl, “ECAT: A
new computerized tomographic imaging system for positron-emitting
radiopharmaceuticals,” J. Nucl. Med. 19, 635-647 (1978).
70
L. G. Strauss and P. S. Conti, “The application of PET in clinical
oncology,” J. Nucl. Med. 32, 623-648 ( 1991).
71
S. M Larson, K. S. Pentlow, N. C. Volkow, A. P. Wolf, R. D. Finn, M.
C. Graham, G. D. Resta, F. Augenson, O. Mawlawi, B. Bendriem, S.
D. J. Yeh, G. J. Wang, L. Birch, R. M. Lambrecht, J. Kalaigian, M.
LaQuaglia, B. Kushner, and N-K. V. Cheung, “PET scanning of
124
I-3F8 as a novel method of tumor dosimetry during treatment planning for radioimmunotherapy in a child with neuroblastoma,” Antib.,
Immunoconj. Radiopharm. 4, 34 (1991).
72
K. S. Pentlow, M C. Graham, R. M. Lambrecht, N-K. V. Cheung, and
S. M. Larson, “Quantitative imaging of I-124 using positron emission
tomography with applications to radioimmunodiagnosis and radioimmunotherapy,” Med. Phys. 18, 357-366 (1991).
73
D. C. Hemmy, D. J. David, and G. T. Herman, “Three-dimensional
reconstruction of craniofacial deformity using computed tomography,”
Neurosurgery 13, 534-541 (1983).
74
G. T. Herman, W. F. Vose, and W. B. Gefter, “Stereoscopic computed
three-dimensional surface displays,” Radiographics 5, 825-852 (1985).
75
S. M. Goldwasser, R. A. Reynolds, and T. Bapty, “Physicians work
station with real-time performance,” Comput. Graphics Applic.5,
44-57 (1985).
76
D. Jackel, “The graphics PARCUM system: A 3D memory-based
computer architecture for processing and display of solid objects,”
Comput. Graphics Forum 4, 21-32 (1985).
77
R. Lenz, P. E. Danielsson, S. Cronstroem, and B. Gudmundson, “Interactive display of 3D medical objects, ” in 3D Image Segmentation in
Medicine, edited by K. H. Hoehne (Springer Verlag, Berlin, 1986).
78
K. H Hoehne, R. L. Delapaz, R. Bernstein, and R. C. Taylor, “Combined surface display and reformating for the three-dimensional analysis of tomographic data,” Invest. Radiol. 22, 658-664 ( 1987).
79
L. R. Schad, R. Boesecke, W. Schlegel, G. H. Hartmann, V. Sturm, L.
G. Strauss, and W. J. Lorenz, “Three-dimensional image correlation of
CT, MR. and PET studies in radiotherapy treatment planning of brain
tumors,” J. Comput. Assist. Tomogr. 11, 948-954 (1987).
80
M.. W. Vannier and D. E. Gayou, “Automated registration of multimodality images,” Radiology 169, 860-861 (1988).
81
C. A. Pelizzari, G. T. Y. Chen, D. R. Spelbring, R. R. Weichselbaum,
and C-T Chen, “Accurate threedimensional registration of CT, PET,
and/or MR images of the brain,” J. Comput. Assist. Tomogr. 13,
20-26 (1989).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
82
577
D. N. Levin. X. Hu, and K. K. Tan, “The brain: integrated threedimensional display of MR and PET images,” Radiology 172, 783-789
(1989).
83
E. L. Kramer, M. E. Noz, J. J. Samger, A. J. Megibow, and G. Q.
Maquire, “CT-SPECT fusion to correlate radiolabeled monoclonal antibody uptake with abdominal CT findings,” Radiology 172, 861-865
(1989).
84
K. F. Koral, R. K. Ten Haken, D. L. McShan. M. L. Kessler, S.
Buchbinder, F. M. Swailem, I. R. Francis, M. S. Kaminski, and P. L.
Wahl, “Superimposition of SPECT and CT images and transfer of ROI
for quantitation,” (abst.) J. Nucl. Med. 31, 872 (1990).
85
P. K. Leichner, J. L. Klein, S. S. Siegelman, D. S. Ettinger, and S. E.
Order, “Dosimetry of “‘I-labeled antiferritin in hepatoma: Specific activities in the tumor and liver,” Cancer Treat. Rep 67, 647-658 (1983).
86
P. K. Leichner, N. C. Yang, T. L. Frenkel, D. M. Loudenslager, W. G.
Hawkins, J. L. Klein, and S. E. Order, “Dosimetry and treatment
planning for 9 0Y-labeled polyclonal antiferritin in hepatoma,” Int. J.
Radiat. Oncol. Biol. Phys. 14, 1033-1042 (1988).
87
D. S. Ettinger, S. E. Order, M. D. Wharam, M. K. Parker, J. L. Klein,
and P. K. Leichner, “Phase I-II study of isotopic immunoglobulin
therapy for primary liver cancer,” Cancer Treat. Rep. 6, 289-297
(1982).
88
R. F. Meredith, M. B. Khazaeli, T. Liu, G. Plott, R. H. Wheeler, C.
Russell, D. Colcher, J. Schlom, D. Shochat, and A. F. LoBuglio, “Dose
fractionation of radiolabeled antibodies in patients with metastatic colon cancer,” J. Nucl. Med. 33, 1648-1653 (1992).
89
O. W. Press, J. F. Eary, C. C. Badger, P. J. Martin, F. R. Applebaum,
R. Levy, R. Miller, S. Brown, W. B. Nelp, K. A. Krohn, D. Fisher, K.
DeSantes, B. Porter, P. Kidd, E. D. Thomas, and I. D. Bernstein,
“Treatment of refractory non-Hodgkin’s lymphoma with radiolabeled
MB-1 (anti-CD37) antibody,” J. Clin. Oncol. 7, 1027-1038 (1989).
90
S. E. Order, J. L. Klein, P. K. Leichner, J. Frinke, C. Lollo, and D. J.
Carlo, “90Y antiferritin-a new therapeutic radiolabeled antibody,” Int.
J. Radiat. Oncol. Biol. Phys. 12, 277-281 (1986).
91
H. M. Vriesendorp, J. M. Herpst, M. A. Germack, J. L. Klein, P. K.
Leichner, D. M. Loudenslager, and S. E. Order, “Phase I-II studies of
yttrium-labeled antiferritin treatment for endstage Hodgkin’s disease,
including RTOG 87-01,” J. Clin. Oncol. 9, 918-928 (1991).
92
G. L. Denardo, A. Raventos, H. H. Hines, P. O. Scheibe, D. J. Macey,
M. T. Hays, and S. J. DeNardo, “Requirements for a treatment planning system for radioimmunotherapy,” Int. J. Radiat. Oncol. Biol.
Phys. 11, 335-348 (1985).
93
D. J. Macey, G. L. DeNardo, and S. J. DeNardo, “A treatment planning program for radioimmunotherapy,” in Frontiers of Radiation
Therapy and Oncology, edited by J. M. Vaeth and J. M. Meyer (Karger
Verlag, Basel, Switzerland, 1990), Vol. 24, pp. 109-120.
94
G. Sgouros, G. Barest, J. Tekkumthala, C. Chui, R. Mohan, R. Bigler,
and P. B. Zanzonico, “Treatment planning for internal radionuclide
therapy: Three-dimensional dosimetry for nonuniformly distributed radionuclides,” J. Nucl. Med. 31, 1884-1891 (1990).
95
J A. Siegel, “Quantitative measurements of activity in bone marrow,”
Antibod. Immunoconj. Radiopharm. 3, 263-264 (1990).
96
T. E. Hui, D. R. Fisher, O. W. Press, J. F. Eary, J. N. Weinstein, C. C.
Badger, and I. D. Bernstein, “Localized beta dosimetry of 131I-labeled
antibodies in follicular Lymphoma,” Med. Phys. 19, 97-104 (1992).
97
T. K. Johnson, “MABDOS: A generalized program for internal radionuclide dosimetry,” Comput. Math. Prog. Biomed. 27, 159-167
(1988).
98
T. G. Stinchcomb, J. S. Durham, and D. R. Fisher, “Obtaining S
values for rectangular-solid tumors inside rectangular-solid host organs,” Med. Phys. 18, 555-558 (1991).
99
M.. J. Berger, “Energy deposition in water by photons from point isotropic sources,” MIRD Pamphlet No. 2, J. Nucl. Med. 9, Suppl. 1,
15-25 (1968).
100
M. J. Berger, “Distribution of absorbed dose. around point sources of
electrons and beta particles in water and other media,” MIRD Pamphlet No. 7, J. Nucl. Med. 12, Suppl. 5, l-23 (1971).
101
E. E. Watson, M. Stabin, and W. E. Bolch, Documentation Package for
MIRDOSE, version 2 (Oak Ridge Associated Universities, Oak Ridge,
TN, 1988).
102
L. P. Clarke, S. J. Cullom, R. Shaw, C. Reece, B. C. Penney, M. A.
King, and M. Silbiger, “Bremsstrahlung imaging using the gamma
camera: Factors affecting attenuation,” J. Nucl. Med. 33, 161-166
(1992).
Radioimmunotherapy dose estimation in patients with B-cell lymphoma
J. A. Siegel
Cooper Hospital/University Medical Center, Camden, New Jersey 08103
D. M. Goldenberg
The Garden State Cancer Center at the Center for Molecular Medicine and Immunology, Newark,
New Jersey 07103
C. C. Badger
The Fred Hutchinson Cancer Research Center, Seattle, Washington 98104
(Received 18 March 1992; accepted for publication 28 October 1992)
Trials of radiolabeled antibody therapy in patients with B-cell lymphoma have been the most
promising of any in radioimmunotherapy. Response rates of greater than 90% with many
complete remissions have been reported by several groups using either low ( 185-370 MBq) or
high (8.6-22.5 GBq) doses of I-13 l-labeled antibodies against B-cell antigens. Estimated doses
delivered to normal organs have ranged from 0.2 to 2.2 mGy/MBq and have shown similar
interpatient variation in all series, despite differences in antibody specificity and dosimetric
techniques. Tumor doses have ranged from 0.5 to 5.4 mGy/MBq. There has been little correlation of tumor response with estimated tumor dose. Toxicity has been limited to bone marrow
suppression which has been greater with the higher amounts of I-131. An advantage for a
particular antibody specificity or for high dose compared to multiple low doses has yet to be
demonstrated.
Key words: lymphoma, radioimmunotherapy, dosimetry
1. INTRODUCTION
Although long-term survival is in the 40%-50% range for
patients with high grade lymphomas who have received
aggressive third generation chemotherapy regimens, patients who relapse following initial therapy and those with
low grade lymphomas are incurable with standard
chemotherapy.’ Because the non-Hodgkin’s lymphomas
are relatively radiosensitive, they are particularly attractive
targets for treatment with radiolabeled antibodies. In patients with low grade lymphomas, remission but not cure
can occur following doses of 100-250 cGy of total body
irradiation.’ In patients with advanced disease, complete
remission and long term survival can be achieved, at the
expense of substantial toxicity and cost, in up to 40% of
patients following 10-1575 cGy of total body irradiation
and chemotherapy in combination with bone marrow
transplantation (BMT).3 Thus a modest increase in radiation dose delivered to tumor, relative to normal tissues,
could potentially result in improving long term survival in
patients with low grade lymphomas without the need for
bone marrow transplantation. Similarly, in patients with
advanced lymphoma, radiolabeled antibodies used in conjunction with bone marrow support have the potential to
increase cure rates.
An additional advantage for the treatment of lymphoma
with radiolabeled antibodies is the observation that unlabeled antibodies can have significant antitumor effects. Unmodified antibodies can cure experimental animals with
lymphoma 4 - 6 a n d c a n i n d u c e r e m i s s i o n i n t r e a t e d
patients. 7-11 Although frequent, these responses have usually been transient with the exception of a few patients
treated with anti-idiotype antibodies. The causes of the
579
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
limited effect of unmodified antibody include antigenic
modulation, the emergence of antigen negative variants,
and the requirement for a host effector system. 6,12-14 Radiation delivered by radiolabeled antibodies can overcome
these limitations of unmodified antibodies while the intrinsic antitumor activity of the antibody is maintained, potentially resulting in a synergistic antitumor effect.
II. THERAPY OF LYMPHOMA WITH
RADIOLABELED ANTIBODIES
Radiolabeled antibodies have been demonstrated to
have significant antitumor effects both in experimental animals and in patients with lymphoma. Cure of mouse lymphoma using either radioiodinated polyclonal or monoclonal antibodies has been reported. 15,16 Response rates in
clinical trials in patients with lymphoma are the most encouraging of any radioimmunotherapy trials. High dose
(8.6-22.5 GBq) I-131-labeled antibodies against the CD37
or CD20 antigens in combination with bone marrow support has resulted in responses in 5/5 patients with 4 complete responses.17,18 Complete and partial responses to both
Y-90 and I-131-labeled anti-idiotype antibodies have also
been observed.19,20 The use of high dose therapy is not
required for response, since tumor regression has occurred
in patients receiving 185-370 MBq of I-131-labeled Lym-1,
LL2, MBl, and 1F5 antibodies. 21-24 Because lymphomas
can respond to infusion of unlabeled antibody, the responses seen with small, as well as large, amounts of radionuclide may be due to deposited radiation, antitumor effects of the antibody itself, or a combination of effects.
0094-2405/93/0205794$01.20
© 1993 Am. Assoc. Phys. Med.
579
590
Siegel, Goldenberg, and Badger: Radioimmunotherapy dose estimation In B-cell lymphoma
580
III. RADIATION DOSIMETRY IN PATIENTS WITH
LYMPHOMA
Similar significant responses have been observed following
radiolabeled antibody therapy in patients with T-cell
lymphoma 25 and Hodgkin’s disease.25-28
Toxicity in all studies has been limited to bone marrow
suppression which, as expected, has been more severe with
larger doses of I-131. Transient reductions in circulating
B-lymphocytes have also been observed, 17,29 in part due to
nonspecific radiation from circulating radionuclide. 2 9
Whether repetitive treatment with low, nontoxic amounts
of labeled antibody24,30-31 or with a single maximally tolerated dose requiring bone marrow support19-20 will yield
the best long term results remains to be determined. A
single treatment course will minimize problems resulting
from human antimouse antibody (HAMA) in immunocompetent patients. However, HAMA has occurred infrequently in patients with lymphoma, even with multiple
courses of murine antibodies, presumably because patients
with lymphoma are immunosuppressed as a result of their
disease. 32 Thus HAMA has not limited the delivery of multiple infusions in most patients with lymphoma to the same
extent it has in the treatment of other tumors.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
Clinical radiation dosimetry in patients with lymphoma
has been obtained according to the MIRD schema, which
requires accurate determination of the time-dependent
amount of radioactivity in situ. Source region activity data
have been collected by whole body counting, tissue and
fluid sampling, and gamma camera imaging (Table I). Organ and tumor absolute activity measurements have usually been performed with conjugate view planar scintillation camera imaging, and several methods have been used
to account for attenuation.3 3’ 34 Single-photon emission
computed tomographic (SPECT) imaging has also been
used to normalize time-activity data from planar imaging
in lymphoma patients,3 5 and has been used in a number of
different radiolabeled antibody studies of solid tumors. 3 6’ 3 7
The addition of SPECT to planar imaging may increase the
accuracy of the planar data, 35 however the ability of
SPECT to perform quantitative studies remains controversial. Organ and tumor volumetrics, which are also necessary for absorbed dose estimation, have been obtained by
computed tomography, SPECT, or by simply using the
published values of the MIRD committee.
Dose estimates for tumor and normal organs have varied widely among patients in all reported series (Table II).
Estimated doses to lymphoma masses have ranged from
0.5 to 2.5 mGy/MBq. These estimates must be regarded as
approximations because of the difficulty in quantitating activity in small, irregular masses by external gamma imaging. In addition, lymphoma masses have not been visualized in all patients, 1 8 and absorbed doses to nonvisualized
tumors are presumably less than those reported. Of interest, the range of estimated doses is similar in all series, in
spite of the use of different antibodies and different techniques for computing estimated dose. The variation in estimated absorbed doses in all series suggests that interpatient differences in antibody behavior will be important in
determining toxicity as well as tumor response, regardless
of which antibody and radionuclide are used for therapy.
Thus determination of dosimetry in individual patients appears to be a necessary component of clinical studies.
Microdosimetric considerations have not been taken
581
Siegel, Goldenberg, and Badger: Radioimmunotherapy dose estimation In B-cell lymphoma
into account in clinical trials of the treatment of lymphoma. However, nonuniformity of antibody deposition
can result in substantial variation in radiation dose within
lymphomatous masses. In patients with follicular lymphoma, preferential anti-B-cell antibody binding to cells in
malignant follicles resulted in estimated absorbed doses to
follicles (30% of tissue) that were up to twofold higher
than the mean dose, while interfollicular areas (70% of
tissue) received up to twofold less than the mean. 4 0
Whether such variation is of clinical significance is unknown.
Further uncertainty in tumor and marrow radiation
doses following treatment of patients with lymphoma results from the fact that tumor and hematopoietic responses
are seen as early as 24 h after infusion of labeled
antibody.” In experimental animals, high dose radiation
from either external beam or from radiolabeled antibodies
themselves can alter subsequent uptake of radiolabeled
antibody. 4 1 , 4 2 Similar changes in antibody uptake, and
therefore dose to tumor and marrow, may occur in patients
following radiolabeled antibody therapy. However, direct
determination of estimated absorbed doses, and the possibility that these differ from doses extrapolated from trace
labeled antibody, has been limited by the difficulty in imaging large amounts of activity. 4 3
IV. CONCLUSIONS
In summary, significant responses have been observed in
patients with lymphoma treated with several radiolabeled
antibodies. Current dosimetric techniques appear to be adequate to conduct phase I-II trials. In trials to date, a
definite dose-response relationship has not been shown, although complete response is more frequent in patients receiving large doses of radiolabeled antibody requiring bone
marrow support. Because of the rapid response to radiation, direct determination of radiation doses delivered to
tumor by therapeutic infusions will be particularly important in defining dose-response relationships in patients with
lymphoma. The optimal antibody specificity and radionuclide for treatment of these patients, whether microdosimetric considerations are of importance, and whether doses
requiring bone marrow transplantation will be needed for
cure remain to be determined.
ACKNOWLEDGMENT
This work was supported in part by USPHS Grants CA
39841 and CA44991 from the NIH.
1
V. T. DeVita, E. S. Jaffe, P. Mauch, and D. L. Longo, “Lymphocytic
lymphomas” in Cancer Principals and Practice of Oncology, edited by
V. T. DeVita, S. Hellman, and S. A. Rosenberg (J. B. Lippincott.
Philadelphia, PA 1989), 3rd cd., pp. 1741-1798.
2
S. C. Carabell, J. T. Chaffey, D. S. Rosenthal, W. C. Moloney, and S.
Hellman, “Results of total body irradiation in the treatment of advanced non-Hodgkin’s lymphomas,” Cancer 43, 994-1000 ( 1979).
3
F. Appelbaum, K. Sullivan, C. D. Buckner, R. A. Clift, H. J. Deeg, A.
Fefer, R. Hill, J. Mortimer, P. E. Neiman, J. E. Sanders, J. Singger, P.
Stewart, R. Storb, and E. D. Thomas, “Treatment of malignant lymphoma in 100 patients with chemotherapy, total body irradiation and
marrow transplantation,” J. Clin. Oncol. 5, 1340-1347 (1987).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
4
581
C. C. Badger, C. Anasetti. J. Davis, and I. D. Bernstein, “Treatment of
malignancy with unmodified antibody.” Pathol. Immunopathol. 6,
419-434 (1987).
5
M. E. Kirch and U. Hammerling, “Immunotherapy of murine leukemias by monoclonal antibody. I. Effect of passively administered antibody on growth of transplanted tumor cells,” J. Immunol. 127, 805810 (1981).
6
W. W. Young and S. I. Hakomori, “Therapy of mouse lymphoma with
monoclonal antibodies to glycolipid: Selection of low antigenic variants
in vivo,” Science 211, 487-489 (1981).
7
O. W. Press, F. Appelbaum, J. A. Ledbetter, P. J. Martin, J. Zarling, P.
Kidd, and E. D. Thomas, “Monoclonal antibody 1F5 (anti-CD20)
serotherapy of human B-cell lymphomas,” Blood 69, 584-591 ( 1987).
8
G. Hale, M. J. S. Dyer, M. R. Clark, J. M. Phillips, R. Marcus, L.
Riechmann, G. Winter, and H. Waldmann, “Remission induction in
non-Hodgkin’s lymphoma with a reshaped human monoclonal antibody CAMPATH-1H,” Lancet 2, 1394-1399 (1988).
9
M. J. S. Dyer, G. Hale, F. G. J. Hayhoe, and H. Waldman, “Effects of
CAMPATH-I antibodies in vivo in patients with lymphoid malignancies: Influence of antibody isotype,” Blood 73, 1431-1439 (1989).
10
R. A. Miller, R. Maloney, R. Warnke, and R. Levy, “Treatment of
B-cell lymphoma with monoclonal anti-idiotype antibody,” N. Engl. J.
Med. 306, 517-522 (1982).
11
T. C. Meeker, J. Lowder, R. G. Maloney, R. A. Miller, K. Thielemans,
R. Warnke, and R. Levy, “A clinical trial of anti-idiotype therapy for
B-cell malignancy,” Blood 65, 1349-1363 (1985).
12
H. S. Shin, M. Hayden, S. Langley, N. Kaliss, and M. R. Smith,
“Antibody-mediated suppression of grafted lymphoma. III. Evaluation
of the role of thymic function, non-thymus-derived lymphocytes, macrophages, platelets, and polymorphonuclear leukocytes in syngeneic
and allogeneic hosts,” J. Immunol. 114, 1255-1263 (1975).
13
R. J. Johnson, R. F. Siliciano, and H. S. Shin, “Suppression of
antibody-sensitized cells by macrophages: Insufficient supply or activation of macrophages within large tumors,” J. Immunol. 122, 379-382
(1979).
14
T. C. Meeker, J. Lowder, M. Cleary, S. Stewart, R. Warnke, J. Sklar,
and R. Levy, “Emergence of idiotype variants during treatment of
B-cell lymphoma with antiidiotypic antibodies,” N. Engl. J. Med. 312,
1658-1665 (1985).
15
T. Ghose and A. Guclu, “Cure of a mouse lymphoma with radioiodinated antibody,” Eur. J. Cancer. 10, 787-792 (1974).
16
C. C. Badger, K. A. Krohn, A. V. Peterson, H. Shulman, and I. D.
Bernstein, “Experimental radiotherapy of murine lymphoma with
131I-labeled anti-Thy 1.1 monoclonal antibody,” Cancer Res. 45,
1536-1544 (1985).
17
O. W. Press, J. F. Eary, C. C Badger, P. J. Martin, F. R. Appelbaum,
R. Levy, R. Miller, S. Brown, W. B. Nelp, K. A. Krohn, D. Fisher, K.
DeSantes, B. Porter, P. Kidd, E. D. Thomas, and I. D. Bernstein,
“Treatment of refractory non-Hodgkin’s lymphoma with radiolabeled
MB-l (anti-CD37) antibody,” J. Clin. Oncol. 7, 1027-1038 (1989).
18
J. F. Eary, O. W. Press, C. C. Badger, L. D. Durack, K. Y. Richter, S.
J. Addison, K. A. Krohn, D. R. Fisher, B. A. Porter, D. L. Williams,
P. J. Martin, F. R. Appelbaum, R. Levy, S. L. Brown, R. A. Miller, W.
B. Nelp, and I. D. Bernstein, “Imaging and treatment of B-cell lymphoma,” J. Nucl. Med. 31, 1257-1268 (1990).
19
B. A. Parker, A. B. Vassos, S. E. Halpern, R. A. Miller, H. Hupf, D.
G. Amox, J. L. Simoni, R. J. Starr, M. R. Green, and I. Royston,
“Radioimmunotherapy of human B-cell lymphoma with 9OYconjugated antiidiotype monoclonal antibody,” Cancer Res. 50, 1022s1028s (1990).
20
C. C. Badger, J. F. Eary, S. Brown, O. Press, J. Davis, F. Appelbaum,
W. Nelp, K. Krohn, R. Miller, R. Levy, and I. D. Bernstein, “Therapy
of lymphoma with I-131-labeled anti-idiotype antibodies,” Proc. Am.
Assoc. Cancer Res. 28, 388 (1987).
21
S. J. DeNardo, D. L. DeNardo, L. F. O’Grady, N. B. Levy, S. L. Mills,
D. J. Macey, J. P. McGahan, C. H. Miller, and A. L. Epstein, “Pilot
studies of radioimmunotherapy of B-cell lymphoma and leukemia using I-131 Lym-1 monoclonal antibody,” Antib. Immunoconj. Radiopharm. 1, 17-33 (1988).
22
S. J. DeNardo, G. L. DeNardo, L. F. O’Grady, E. Hu. V. M. Sytsma,
S. L. Mills, N. B. Levy, D. J. Macey, C. H. Miller, and A. L. Epstein.
“Treatment of B-cell malignancies with I-131 Lym-I monoclonal antibodies,” Int. J. Cancer Suppl. 3, 96-101 (1988).
23
M. S. Kaminski, L. Fig, K. Zasadny, K. Koral, I. Francis, R. Miller, R.
L. Wahl, “Phase I evaluation of 131-I MB-1 antibody radioimmunc-
582
Siegel, Goldenberg, and Badger: Radioimmunotherapy dose estmation In B-cell lymphoma
therapy (RIT) of B-cell lymphoma,” Blood 76, 355a (1990).
D. M. Goldenberg, R. M. Horowitz, R. M. Sharkey, T. C. Hall, S.
Murthy, H. Goldenberg, R. E. Lee, R. Stein, J. A. Siegel, D. O. Izon,
K. Burger, L. C. Swayne, E. Belisle, H. J. Hansen, and C. M. Pinsky,
“Targeting, dosimetry, and radioimmunotherapy of B-cell lymphomas
with iodine-131-labeled LL2 monoclonal antibody,” J. Clin. Oncol. 9,
548-564 (1991).
25
S. T. Rosen, A. M. Zimmer, R. Goldman-Leikin, L. I. Gorodon, J. M.
Kazikiew, E. H. Kaplan. D. Variakojis, R. J. Marder, M. S. Dykewicz,
A. Pierfies, E. A. Silverstein, H. H. Roenigk, and S. M. Spies, “Radioimmunodetection and radioimmunotherapy of cutaneous T cell lymphomas using a 131I-labeled monoclonal antibody: An Illinois Cancer
Council study,” J. Clin. Oncol. 5, 562-573 ( 1987).
26
R. E. Lenhard, S. E. Order, J. J. Spunberg, S. O. Asbell, and A. Leibel,
“Isotopic immunoglobin: A new system therapy for advanced
Hodgkin’s disease,” J. Clin. Oncol. 3, 1296-1300 (1985).
27
H. M. Vriesendorp, J. M. Herpst, P. K. Leichner, J. L. Klein, and S. E.
Order, “Polyclonal 9 0yttrium labeled antiferritin for refractory
Hodgkin’s disease,” Int. J. Radiat. Oncol. Biol. Phys. 17, 815-821
(1989).
28
H. M. Vriesendorp, S. M. Quadri, R. L. Stinson, O. C. Onyekwere, Y.
Shao, J. L. Klein, P. K. Leichner, and J. R. Williams, “Selection of
reagents for human radioimmunotherapy,” Int. J. Radiat. Oncol. Biol.
Phys. 22, 37-45 (1992).
29
R. Stein, R. M. Sharkey, and D. M. Goldenberg, “Haematological
effects of radioimmunotherapy in cancer patients,” Br. J. Haematol. 80,
69-76 ( 1992).
30
S. J. DeNardo, D. L. DeNardo, L. F. O’Grady, N. B. Levy, G. P.
Adams, and S. L. Mills, “Fractionated radioimmunotherapy of B-cell
malignancies with 1311-Lym-1,” Cancer Res. SO, 1014-1016 (1990).
31
D. M. Goldenberg, R. M. Sharkey, S. Murthy, H. J. Hansen, and C. M.
Pinsky, “Initial evaluation of repeated low-dose radioimmunotherapy
(RAIT) using I-131-LL2 monoclonal antibody (MAb) in patients
with lymphoma,” J. Nucl. Med. 33, 863 ( 1992).
32
S. B. Sutcliffe, Immunotherapy of the Lymphomas (CRC, Boca Raton,
FL, 1985).
33
J. F. Eary, F. R. Appelbaum, L. Durack, and P. Brown, “Preliminary
validation of the opposing view method for quantitative gamma camera
imaging,” Med. Phys. 16, 382-387 (1989).
34
R. K. Wu and J. A. Siegel, “Absolute quantitation of radioactivity
24
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
582
using the buildup factor,” Med. Phys. 11, 189-192 (1984).
K. F. Koral. K. R. Zasadny, F. M. Swailem, S. F. Buchbinder. I. R.
Francis, M. S. Kaminski, and R. L. Wahl, “Importance of intratherapy single-photon emission tomographic imaging in calculating tumor dosimetry for a lymphoma patient,” Eur. J. Nucl. Med. 18, 432435 (1991).
36
G. L. DeNardo, D. J. Macey, S. J. DeNardo, C. G. Zhang, and R.
Custer, “Quantitative SPECT of uptake of monoclonal antibodies,”
Semin. Nucl. Med. 19, 22-32 (1989).
37
R. H. J. Begent, J. A. Ledermann, A. J. Green, K. D. Bagshawe, S. J.
Riggs, F. Searle, P. A. Keep, T. Adam, R. G. Dale, and M. G. Glaser,
“Antibody distribution and dosimetry in patients receiving radiolabeled antibody therapy for colorectal cancer,” Br. J. Cancer 60, 406
412 (1989).
38
J. A. Siegel, D. M. Goldenberg, R. M. Sharkey, T. C. Hall, S. Mm-thy,
R. E. Lee, D. A. Pawlak, and L. C. Swaney, “Tumor and organ dosimetry for I-131-labeled LL2 (EPB-2) monoclonal antibody in patients with B-cell lymphomas,” Antib. Immunoconj. Radiopharm. 4,
649-654 (1991).
39
D. A. Scheinberg, D. J. Strauss, S. D. Yeh, C. Divgi, P. Garin-Chesa,
M. Graham, K. Pentlow, D. Coit, H. F. Oettgen, and L. J. Old, “A
phase I toxicity, pharmacology, and dosimetry trial of monoclonal antibody OKB7 in patients with non-Hodgkin’s lymphoma: Effects of
tumor burden and antigen expression,” J. Clin. Oncol. 8, 792-803
(1990).
40
T. E. Hui, D. R. Fisher, O. W. Press, J. F. Eary, J. N. Weinstein, C. C.
Badger, and I. D. Bernstein, “Localized beta dosimetry of 131I-labeled
antibodies in follicular lymphoma,” Med. Phys. 9, 97-104 (1992).
41
R. M. Macklis, W. D. Kaplan, J. L. Ferrara, B. M. Kinsey, A. I.
Kassis, and S. J. Burakoff, “Biodistribution studies of anti-Thy 1.2 IgM
immunoconjugates: Implications for radioimmunotherapy,” Int. J. Radiat. Oncol. Biol. Phys. 15, 383-389 (1988).
42
C. C. Badger, J. Davis, C. Nourigat, Z. M. Wu, T. E. Hui, D. R.
Fisher, J. Shulman, F. R. Appelbaum, J. F. Eary, K. A. Krohn, D. C.
Matthews, and I. D. Bernstein, “Biodistribution and dosimetry following infusion antibodies labeled with large amounts of 131I,” Cancer Res.
51, 5921-5928 (1991).
43
K. R. Pollard, A. N. Bite, J. F. Eary, L. D. Durack, and T. K. Lewellen, “Imaging therapeutic doses of iodine-131 with a clinical gamma
camera,” J. Nucl. Med. 32, 923 ( 1991).
35
Dosimetry of solid tumors
Ruby F. Meredith
Department of Radiation Oncology, University of Alabama, Comprehensive Cancer Center,
Birmingham, Alabama 35233
Timothy K. Johnson
Department of Radiology. University of Colorado Health Sciences Center, Denver, Colorado
Gene Plott
Department of Radiation Oncology, University of Alabama, Comprehensive Cancer Center,
Birmingham, Alabama 35233
Daniel J. Macey
Radiation Physics, MD Anderson Cancer Center, Houston, Texas
Robert L. Vessella
Department of Urology, University of Washington Medical Center, Seattle, Washington
Latresia A. Wilson
Division of Radiation Oncology, City of Hope Medical Center, Duarte, California
Hazel B. Breitz
Nuclear Medicine Section, Department of Radiology, Virginia Mason Medical Center,
Seattle, Washington
Lawrence E. Williams
Division of Radiation Oncology, City of Hope Medical Center, Duarte, California
(Received 18 March 1992; accepted for publication 24 July 1992)
Dosimetry data arising from a decade of radioimmunotherapy are summarized along with
techniques utilized to arrive at the reported dose estimates. Generality of the MIRD methodology allows it to serve as a vehicle for the calculation of solid tumor dosimetry although several
limitations exist. Nonstandard geometries of solid tumors will ultimately necessitate determination of absorbed fractions for the individual tumors. Several approaches currently under investigation are described. For reasons of practicality, solid tumor dosimetry estimates continue to
use the assumption of homogeneous activity distribution in a source organ, accounting for either
all radiation or only nonpenetrating radiation. As computation tools become available for incorporating inhomogeneous cellular level data, the currently used “average dose” as an index of
tumor sterilization will likely be replaced with a statistical distribution based on the number of
viable cells in the tumor volume. Estimates of a tumor control dose would be based upon a linear
extension of dose coupled with a threshold dose for cell sterilization.
Key words: radioimmunotherapy, tumor dose, clinical dosimetry
I. INTRODUCTION
In the preceding decade, over 100 clinical trials have utilized radiolabeled antibodies against tumors.’ A variety of
tumors have been treated including hepatoma, neuroblastoma, melanoma, cancer of the ovary, breast, kidney, lung,
colon, lymphoma, and other malignancies. Doses reported
have varied widely. Some of the most recent trials reviewed
by Langmuir report a tumor dose range from 2 Gy for a
hepatoma patient to greater than 120 Gy fractionated delivery for non-Hodgkins lymphoma. Dose variations are
noted among different tumor types, individual patients
given similar treatment for the same type of malignancy
and even among multiple lesions of the same patient. Lymphoma dosimetry has been separately reviewed by Siegel
and Goldenberg.
The MIRD methodology4 serves as the framework for
most solid tumor dosimetry calculations. Organ and tumor
specific radioactivity is quantitated, time-activity curves
are constructed and integrated, and cumulated activities
583
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
are multiplied by the absorbed dose constant and specific
absorbed fraction to yield estimated dose. Targeting of radioactivity in a nonstandard volume positioned in a nonstandard geometry, however, creates several problems distinct from those encountered in normal organ dosimetry.
Because published "S" tables make provision only for standard organ systems as sources/targets of radiation, the frequently used MIRD Pamphlet No. 11 5 is not easily applied
to solid tumor dose estimates. For nonpenetrating radiation, the contribution to tumor dose may be computed
assuming an absorbed fraction of unity. Determining the
absorbed fractions for penetrating radiation is not so simple. MIRD Pamphlets No. 3 and No. 8 provide a partial
solution with tables of absorbed fractions for spherical and
ellipsoidal volumes that contain uniform distributions of
photon emitters.6 ’ 7 Such tables allow the calculation of
dose to tumor from activity in the tumor, but fail to provide estimates for other source organs that may contribute
appreciably to tumor dose. The following deals with major
0094-2405/93/020583-10$01.20
© 1993 Am. Assoc. Phys. Med.
583
584
Meredith et al.: Dosimetry of solid tumors
aspects of the MIRD formalism as applied to solid tumor
dosimetry, including calculation of dose per unit cumulated activity and limitations of current methodologies for
estimating tumor dose. Therapeutic interventions and the
type of circulating protein that may impact tumor kinetics
and dose are also discussed.
584
radioimmunotherapy.’ The difficulty in determining a
dose/response relationship is compounded by multiple factors. These include the variance of responsiveness among
multiple lesions and between individual patients, the degree of dose heterogeneity within tumor masses at the cellular level and the limited dosimetry information reported
from most clinical trials.
II. CLINICAL DOSE ESTIMATES
A summary of clinical dose estimates for administration
of radioimmunoconjugates is presented in Table 1. 8-37 The
most outstanding feature of this compilation is the wide
variation of doses even when the range of administered
activity is taken into account. Doses have generally been
calculated by indirect quantitation since direct measurement of activity from biopsy specimens is uncommon and
even when available usually represents only a single time
point during the several days of radiation delivery via radioimmunoconjugates. Although most dose estimates to
date have utilized the MIRD formalism with activity quantitation by means of planar scintigraphy, the details for
implementing these methodologies varied substantially.
Despite this, most of the variance in tumor dose undoubtedly results from real differences in biological and physical
factors. This is suggested by the fact that significant dose
differences are reported for multiple lesions in the same
patient when identical calculation techniques, assumptions, and the same time periods for quantitative measurements are used. (Table II compares the dose variation between multiple lesions noted by four groups.)
Tumor dose estimates presented in Tables I and II were
derived from intravenous or intra-arterial administration
of radioimmunoconjugates (with the exception of intralesional injection to 7 patients 3 5). Radioimmunoconjugate
therapy by other routes of infusion including intrapleural,
intrapericardial, intraperitoneal or intrathecal have generally been used for tumor deposits too small to be quantitated by techniques currently used. Thus dose estimates
have not always been reported for those studies. Studies in
this category that have reported dosimetry aspects include
131
intrathecal
I-antibody
t r e a t m e n t o f neoplastic
38
meningitis, and intraperitoneal dosimetry using thermoluminescent dosimeters and biopsy quantitation in conjunction with gamma camera imaging methods. 39 In some
other studies, the choice of radionuclide precluded quantitative dosimetry for measurable tumors. For example, the
gamma component of 125 I emissions is not sufficiently energetic to allow quantitation by gamma camera imaging.@
Various substitute radionuclides have been used for pretherapy imaging studies to determine localization.
No definite dose/response relationship has been established to date from the results of clinical trials. Overall, the
most extensive patient experience and greatest success in
clinical use of radioimmunotherapy of solid tumors has
been with the relatively radioresponsive lymphomas. Although responses vary considerably among lymphoma patients, a dose/response relationship is suggested by the fact
that some of the best response rates have resulted from
such marrow toxic levels of 1 3 1I-MB-l antibody that marrow transplantation may be necessary for recovery from
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
Ill. CALCULATION OF TUMOR-ABSORBED DOSE
After time-activity curves for organ specific radioactivity have been constructed and integrated as has been detailed by Leichner and Kwok41 the resulting cumulated
activities must be multiplied by appropriate absorbed dose
constants and specific absorbed fractions. The degree of
sophistication applied to this portion of the problem varies
within the medical physics community. Three general
methods found or alluded to in the literature are outlined
below for dealing with the second portion of the tumor
dosimetry equation.
A. Method No. 1: Homogeneous distribution of
radioactivity throughout the tumor volume, only
nonpenetrating radiations contribute to tumor
dose
In this approach, the distribution of radioactivity is
assumed to be uniform in the tumor and the range of the
radiation emitted is less than the tumor dimensions. The
assumption of a homogeneous distribution of activity
throughout the tumor is a gross oversimplification at the
cellular leve1.42,43 However, since noninvasive techniques
with sufficient resolution to characterize the microscopic
radioactivity distribution are not available, the assumption
of a uniform distribution is accepted as a first approximation. This approach can be modified at a later time pending
pattern analysis of the nonuniform antibody deposition.
Two assumptions may be made about the deposition of
nonpenetrating radiation in the tumor: (1) all of the nonpenetrating radiation is deposited within the tumor volume
[φ (np) = 1], or (2) a fraction of the nonpenetrating radiation is deposited within the tumor [φ (np) < 1]. For small
tumors, the assumption of np = 1 would clearly be an overestimation.
Because of the finite range of the beta radiation and the
resultant escape of some particles, the edge of the tumor
will receive a lower dose than other locations within the
lesion. If one assumes spherical tumors, a simple correction
can be made using two geometrical corrections. 44 The corrections involve two factors which, when multiplied together, give the average spherical lesion dose relative to
that calculated via assuming an infinitely large medium
containing the beta source. 44 Using a 9 0Y source, the resultant calculations are summarized in Table III.
For example, if a 1.0-cm 3 lesion were to be treated with
a uniform deposition of 90Y, the actual average dose within
that volume would only be 68% of that estimated using
standard methods which neglect edge effects. For very
small tumors, the correction factor is 0.36; i.e., only about
one-third of the estimated dose would be, on the average,
found in the smallest volume. Corrections are not as dra-
585
Meredith et al.: Dosimetry of solid tumors
matic for lower energy radionuclides such as 1 3 1 I or
67
Cu. Low energy sources, however, offer reduced crossfire capability so as to make them less effective for the
irradiation of tumor cells located at some distance from
where the antibody molecule has come to rest in the
tumor. 4 5’ 46 The latter problem, essentially one of differential tumor perfusion, is of great importance in radiation
therapy using monoclonal antibodies.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
585
The assumption of dose contributions arising only from
nonpenetrating radiations is, if one neglects braking radiation, exactly true for pure beta emitters such as 90Y. Without an imaging photon, however, it is difficult to determine
kinetics in patients, which are necessary for the determination of the cumulated activity. Since some animal
studies 47 have shown similar biodistribution for 1 1 1In and
90
Y, the biodistribution of “‘In-antibody conjugates has
566
Meredith et al.: Dosimetry of solid tumors
been utilized to calculate the dose that would be achieved
for 9 0Y-labeled antibodies.” Alternatively, one may add a
small amount of “‘In-labeled antibody to the q-labeled
antibody to trace its movement in vivo.
In addition to corrections due to the finite range of beta
radiation, there is a second correction to tumor and other
organ radiation dose estimates in the case of pure beta
emission. High-energy beta emitters, while being stopped
in a medium, cause the production of a wide spectrum of
secondary photon emissions called braking radiation or
Bremsstrahlung. 4 8 It should be noted that attempts have
been made to measure the Bremsstrahlung x-rays following
90
Y administration.49 The dosimetry of braking radiation
associated with 90Y has been measured in an anthropomorphic phantom and analyzed with two mathematical
forms.5 0’ 51 The first analysis was based on an analogy with
the MIRD framework and permits organ-to-organ dose
estimates. A second strategy51 utilized a multi-exponential
function to provide the dose at a distance from a point
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
586
source. These two methods were found to agree with each
other within the accuracy of the computations. There was,
however, a 20% discrepancy between both analyses and
the measurements at short distances (<5 cm) from a
point source in the humanoid phantom. Here the measured
braking radiation doses were lower than those predicted by
the two computational methods. It is likely that the photon
spectrum may have to be corrected at these short distances
to account for local attenuation. Measured braking radiation doses were on the order of 0.1 mGy/MBq for 9 0Y at
distances of 3 cm from a point source.
B. Method No. 2: Homogeneous distribution of
radioactivity throughout the tumor volume,
all radiations accounted for
Both penetrating and nonpenetrating radiations are
accounted for in this approach. The difficulty in calculating
absorbed fractions for penetrating radiations has resulted
587
Meredith et al.: Dosimetry of solid tumors
in them often being ignored. Three methods exist to include the energy deposition from penetrating radiations
along with that from nonpenetrating radiations. The simplest of these strategies relies on interpolating existing S
values for standard organs as found in MIRD tabulations.
Interpolations are based on knowing actual tumor volume(s).
Knowledge of individual organ or tumor volumes or
masses is an essential parameter for calculation of radiation
doses in radioimmunotherapy. The volume of a particular
organ in the human shows a broad distribution that cannot
be adequately predicted from the height and weight of a
patient. In some disease states, significant changes can occur that affect the size, shape and location of organs in the
body. Usually these variations result in a uniform change
in size with little distortion in shape. In lymphoma patients, for example, the spleen can be enlarged by a factor
of two or three with minimal distortion of its shape. These
changes in the dimensions and locations of tumors and
organs in the body can result in over-or underestimations
in radiation absorbed dose compared with the values derived using the MIRD model for standard man.
Morphometric volumes of organs and tumor sites can
be provided from CT and MRI. Functioning volumes can
be provided by SPECT. If no information on the volumes
can be provided by imaging modalities, we must resort to
scaling the volume from the total body weight or height of
the patient. This is done in the same way as the administered radioactivity was prescribed in nuclear medicine; e.g.,
depending on the total body weight, body area, or even
patient height.
To estimate the dose to target organs from activity in
the rest of the body, the MIRD table S values show little
change with organ mass and the S values for the whole
body as source for each target organ or site in the body
may be considered adequate for the dosimetry estimates
required in RIT.
Let us consider the S value for a situation where the
source and target organ are identical so that nonpenetrating (np) radiation becomes significant. In the MIRD
tables, 52 S can be written as:
where S is the tabulated MIRD S factor for any source as
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
587
target organ. S np is the nonpenetrating component of S and
S p is the penetrating component, which is required.
Dividing Eq. (1) by S yields:
Figure 1 shows the variation in the ratio S p /S versus
mass, based on four contiguous-volume organs of the
MIRD phantom, for five commonly used radionuclides. It
is clear from this figure that a doubling of organ mass from
20 to 40 g results in a change in S p /S of less than 5% for
each of these radionuclides. For paired organs with noncontiguous volume components (e.g., adrenals, ovaries and
kidneys), the S p /S’ ratios are even less sensitive to organ
mass. It is therefore reasonable to separate S factors from
the MIRD tables into penetrating and nonpenetrating
components and to estimate S p for a tumor by interpolating the MIRD S p values. This estimate of the penetrating
component could be combined with S np, calculated directly
from the known radiations emitted by the radionuclide
involved, to obtain an S factor for the tumor. The volumes
of tumors and organs should be determined as accurately
as possible to minimize errors in the calculation of the
nonpenetrating component of the dose where source and
target are the same volume. Table IV contains the numerical values used in constructing Fig. 1.
588
Meredith et al.: Dosimetry of solid tumors
A second dose estimation strategy, which is somewhat
more intensive computationally, uses convolution techniques. This is exemplified by the software program of
Sgouros et al.53 Briefly, a dose-distance function (i.e., the
point source kernel) is stored in a table. The two sources of
code for generating point source kernels are the EGS
c o d e5 4,55 and the ETRAN code. 56 Alternatively, a simple,
empirical function can be solved to provide dose as a function of distance.57 Lookup tables appropriate to a given
radionuclide’s decay spectrum are fashioned to account for
all prominent radiations.
Each voxel of a source organ has an associated discrete
amount of activity, the integral of which represents that
voxel’s cumulated activity. For a defined target organ
voxel, the distance separating it from each source organ
voxel is calculated. This distance serves as an offset into the
point source kernel lookup table, and the dose per unit
cumulated activity is obtained. Absorbed dose to a target
organ voxel is obtained by summing the contributions from
all source organ voxels. In this manner, a nonuniform activity distribution can be taken into account at the macroscopic level.
A third strategy by which penetrating radiation contribution to dose can be estimated is via a Monte Carlo simulation similar to the original code that generated the data
found in MIRD Pamphlets No. 5 and No. 11. An example
can be seen in the software program of Johnson and Vessella termed MABDOS, an acronym for Monoclonal AntiBody DOSimetry. 58,59 The MABDOS code allows the operator to enter up to five tumor foci acting as sources of
and targets for radiation in the Standard Man Model. Initial simulations for 131I indicate the possibility that photons
originating in the liver, spleen and whole body may contribute more than 20% of the tumor’s dose, depending on
the amount of tumor specific uptake.
The MABDOS program initiates a dosimetry session by
taking interactive input from the user. The user identifies
each source organ to be included in the dosimetry calculation, and enters a series of time/activity data points associated with that source organ. The question of source
organ identification and selection will be specific to a given
radiopharmaceutical, and dependent on its biodistribution
properties in the human body. If an organ system can be
resolved on a nuclear medicine scintigram, the assumption
is made that the organ system localizes activity to a degree
greater than that of radioisotope distributed throughout
the whole body. This qualifies it by definition as a source
organ. MABDOS is completely flexible in that it allows
a dosimetry treatment of any radioisotope/
radiopharmaceutical complex.
A graph mode (linear, semilog, or logit) is selected
which initiates a display of the individual time activity
curves. Methodology (curve peeling, trapezoidal integration or mathematical modeling) to fit the time/activity
data points is chosen to achieve an estimate of cumulated
activity for each source organ.
If a tumor has been identified as a source organ, the
coronal projection of Standard Man then appears on the
graphics screen. Identifying the height of the tumor center
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
588
in the Standard Man reference frame with a mouse initiates
the drawing of the corresponding transverse slice of Standard Man. The tumor center is next defined on the transverse slice, thereby positioning the tumor center with coordinates in x, y, and z. The tumor is approximated as a
sphere, and the tumor radius is entered. This identifies the
tumor in three dimensions; the entered radius subsequently
declares a volume of space in the Standard Man as representing a tumor.
The source organ information, tumor geometry information (x/y/z location of center, and radius)) and selected isotope are uploaded to a CRAY. Beta radiation is
assumed to be locally absorbed as in MIRD 11. A simulation of photon transport is carried out to estimate penetrating radiation absorbed fractions. The output consists of
an S table having an additional row and column for each
identified tumor. The "S" table is downloaded to the microcomputer host where it is combined with the cumulated
activity and generates a dose table similar to those presented in the MIRD 11 tables.
There are drawbacks to both the convolution and the
Monte Carlo simulation approaches. The convolution technique requires that anatomic boundaries be defined for
source and target organs. Invariably this means that a sequence of CT or MRI slices be placed on a viewing screen
and borders traced. The amount of time required is substantial. Although this shortcoming could be addressed
with automated edge detection by a computer, the variation of human anatomy from patient to patient virtually
precludes current algorithms from consistently working
correctly. This would necessitate review by a human observer, with subsequent interventional correction of anatomic boundaries.
A second shortcoming of the convolution technique is
the use of a point dose kernel. The kernels are derived for
homogeneous media, typically water. The makeup of the
human body, however, is exceedingly complex. An inhomogeneous mixture of bone and soft tissue predominates
throughout the body. Recent work by Kwok et al. indicates that tissue dose at a bone interface is underestimated
by 20%-40% because of the backscatter of low-energy
electrons. 6 0 A solution would be to derive a point dose
kernel for each voxel in the human body or Standard Man
Model. The point dose kernel derivation being based on a
Monte Carlo simulation leads back to the implementation
of a Monte Carlo solution. The backscatter phenomena
reported by Kwok et al. at a bone interface represents an
additional error that can only be replicated by Monte
Carlo simulation.60 The use of convolutions are derived for
homogeneous media, and do not allow the inclusion of
different media.
The shortcomings of the Monte Carlo approach are
principally ones of computation time economy, and the use
of a model rather than the patient’s own anatomy. Under
the assumption of homogeneous activity deposition, model
applicability to an individual is reasonable since small
changes in organ shape should not appreciably alter the
absorbed fraction.‘* With regard to the computation time,
Monte Carlo solutions are by nature time-consuming, be-
589
Meredith et al.: Dosimetry of solid tumors
ing a statistical answer requiring numerous histories to reliably estimate absorbed fractions. The MABDOS code
currently executes in a “reasonable” amount of time on a
CRAY supercomputer.61 The issues of access and expense
make this technique unattractive to many institutions. The
Monte Carlo simulation code is currently being ported to
an array of INMOS transputers housed on a microcomputer expansion card. This will hopefully obviate the need
for access to a CRAY supercomputer. A complete dosimetry session would be conducted from within the
microcomputer. 6 2 This could potentially deal with the
problem of execution time by using multiple processors to
linearly speed up the calculation. The cost of such a machine with a modest number of transputers would be less
than $50000.
C. Method No. 3: Inhomogeneous distribution of
radioactivity throughout the tumor volume,
all radiations accounted for
While SPECT has improved the quantitation of nonuniform distribution of radioactivity at the macroscopic
level, it is difficult to measure the microscopic inhomogeneity that is known to exist. Microdetectors offer a method
for determining energy deposition at a point, albeit not in
an imaging format.6 3’ 6 4 However, the procedure is invasive
and requires that tumors be accessible for placement of
these measuring devices. Furthermore, multiple detectors
would be required for mapping the dose distributions.
With these limitations microdetectors appear inpractical
for widespread clinical use.
Inclusion of inhomogeneous distribution information in
dose calculations will therefore rely mainly on animal studies, cell culture models 65 and sequential autoradiographs.
Extrapolation from these systems is also fraught with inaccuracies but may allow estimates that are useful in directing clinical trials.
IV. SPECIAL CONSIDERATIONS IN TUMOR
DOSIMETRY
To date, human tumor uptake and clearance of radioimmunoconjugates have not been modeled with confidence. Thus activity versus time measurements are essential for estimating cumulated radiation delivered to tumors
in this manner. Numerous proposals for altering tumor
uptake and washout kinetics such as extracorporeal
immunoadsorption 66,67 and chimeric or engineered antibody fragments further complicate the situation.
Most tumor dosimetry from clinical studies has involved administration of xenogeneic antibodies which have
a relatively short circulating half-life. With the construction of chimeric antibodies (using a xenogeneic variable
region linked to a human constant region), the effective
half-life of the administered antibody has increased several
f o l d .6 8 E a r l y r e s u l t s f r o m a d m i n i s t r a t i o n o f
131
I-mouse/human chimeric B72.3 have demonstrated localization of activity to tumor sites persisting for longer
than 20 days.69 Since it is impractical to scan daily for the
entire period of detectable localization as may be done for
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
589
patients receiving xenogeneic antibody, assumptions must
be made for cumulated radioactivity in tumors for the intervals between relatively wide-spaced scanning times. Initial dosimetry in these cases has been performed assuming
linear accumulation in the site of localization when the
count rate increases with time, and an exponential decrease
of 1 3 1I concentration when the count rate drops between
measurements. 21
Although it may seem less accurate to have intervals of
several days between measurements for long-lived antibodies, dose estimates have not been determined to be less
precise than for antibodies that circulate for a shorter period of time where a large portion of the total cumulated
activity may be accrued quickly. The interval between
measurements may not be as important as the total number
of measurements obtained over the period of high initial
activity.
Another source of potential inaccuracy in tumor dosimetry is the uncertainty as to when the radionuclide concentration in the tumor exceeds background. To minimize the
chance of missing the peak by a considerable period of
time, frequent early scans are recommended even if technical innovations are required in order to protect personnel
from undue radiation exposure.
To alleviate the problem of early scanning of patients
with therapeutic doses of radiolabeled antibodies, a tracer
dose is often used with linear extrapolation of results to
larger doses delivered at a later time. 8,11 Although this
technique will be accurate if the distribution and kinetics of
the two doses coincide, errors of dosimetry can be large if
these parameters are not similar for all administrations. 11,70
In using this technique a verification method should be
used to confirm the linear scaling from tracer dose to therapeutic dose. As a minimum, whole body disappearance
curves should be generated with a GM counter for the
therapeutic dose, a procedure analogous to measurements
made for release of patients undergoing 1 3 1I therapy for
thyroid disease. Alternative methods such as analysis of
plasma clearance or other parameters 71 may prove to be
more reliable in predicting whole body and region of interest half-life of radiolabeled antibody than following the
kinetics of a small preliminary dose of the same agent.
However, such techniques have not been well documented
in the literature to date.
Limited information has been reported comparing the
relative biologic effectiveness of radiation delivered as fractionated high dose rate external beam therapy, low dose
rate brachytherapy and at an exponentially decreasing dose
rate characteristic of radioimmunotherapy. 72-77 Not only is
it difficult to compare radioimmunotherapy with other
techniques of radiation exposure because of the many variables with radioimmunoconjugate therapy, it is also difficult to compare the results within radioimmunotherapy
trials. As in external beam radiation where reporting of a
total dose must be clarified by dose/fraction description,
radioimmunotherapy dose reporting should provide details. Specifics should include the radioimmunoconjugate,
amount administered, injection route, dose rate information, times of activity measurement, calculation methods
590
Meredith et al.: Dosimetry of solid tumors
including assumptions used for calculations, and an estimate of total cumulated dose. These factors may assist in
furthering the field of solid tumor dosimetry and quantitating the probability of tumor control by various doses of
radioimmunoconjugate therapy.
V. SUMMARY
A broad range of absorbed dose estimates to solid tumors is reported in the literature. Most of this dose variation can be traced to differences in injected activity levels,
patient size, biologic behavior of the immunoconjugate and
other real factors. Nevertheless, some portion of the reported dose range undoubtedly results from the diversity of
approaches currently used for quantifying tumor dose. Dosimetry for parenterally administered radionuclides is currently based primarily on the MIRD formalism, with
quantitation of local uptake and clearance by means of
planar imaging computational techniques. This approach
to solid tumor dosimetry presents difficulties that are being
dealt with in various ways. Some of the problems associated with the use of planar imaging for tumor activity
quantitation, such as the inability to accurately measure
volumes or to eliminate contributions from overlying and
underlying tissue, may be alleviated by new developments
in the area of SPECT imaging.
Although well suited for dosimetry of normal organs,
the existing MIRD formalism cannot easily deal with the
arbitrary geometries of solid tumors and their spatial relationship to other sites of localized activity. Convolution
techniques and Monte Carlo simulations which are under
investigation may accommodate nonstandard tumor
masses for MIRD calculations. Alternatively, one may use
the method outlined above for determining S factors for
arbitrary soft tissue masses.
The resolution limits of existing nuclear imaging devices
precludes mapping of uptake heterogeneity, which is
known to exist at the cellular level. In light of this heterogeneity, specification of the dose to a tumor is of questionable value. As measurement and computation techniques are advanced to the point where nonuniform
deposition of activity can be quantitated and incorporated
into dose estimates, the effect of radioimmunotherapy on
solid tumors might be more effectively represented as statistical distributions of dose to populations of tumor cells.
Accurate models for the kinetics of immunoconjugates
in solid tumors can only be developed from extensive serial
sampling of uptake and clearance using measurement techniques that are reasonably accurate and uniformly applied.
Further definition of dose/response relationships for radioimmunotherapy of solid tumors should further stimulate
development of techniques needed to achieve therapeutic
efficacy.
ACKNOWLEDGMENTS
The authors wish to thank Dr. Peter Leichner, Dr.
Barry Wessels, Dr. Jeffry Siegel, Dr. Virginia Langmuir,
and Dr. Donald Buchsbaum for discussion and suggestions, and Charm Pate and Tracy Blevins for preparation
Medical Physics, Vol. 20. No. 2, Pt. 2, Mar/Apr 1993
of the manuscript. This work was supported in part by
grants from the National Institutes of Health NC1 NO1
CM-97611, PO1 CA43904 and 5P30 CA33572.
1
S. M. Larson, “Radioimmunology: Imaging and therapy,” Cancer 67,
Suppl., 1253-1260 (1991).
2
V. K. Langmuir. “Radioimmunotherapy: Clinical results and dosimetric considerations,” Int. J. Radiat. Appl. Instrum. Part B: Nucl. Med.
Biol. 19, 213-225 (1992).
3
J. A. Siegel, D. M. Goldenberg, and C. C. Badgers, “Radioimmunotherapy dose estimation in patients with B-cell lymphomas,” Med.
Phys. 20, 579-582 (1993).
4
R. Loevinger and M. Berman, “A revised schema for calculating the
absorbed dose from biologically distributed radionuclides,” MIRD
Pamphlet No. 1, revised, with a Forward by R. J. Cloutier and E. M.
Smith (Society of Nuclear Medicine, New York. 1976).
5
W. S. Snyder, M. R. Ford, G. G. Warner, and S. B. Watson, “S’:
Absorbed dose per unit cumulated activity for selected radionuclides
and organs,” MIRD Pamphlet No. 11 (Society of Nuclear Medicine,
New York, 1975).
6
G. L. Brownell, W. H. Ellett, and A. R. Reddy, “MIRD Pamphlet No.
3: Absorbed fractions for photon dosimetry,” J. Nucl. ‘Med. 9, Suppl. 1,
28-39 ( 1968).
7
W. H. Ellett and R. M. Humes, “MIRD Pamphlet No. 8: Absorbed
fractions for small volumes containing photon-emitting radioactivity,”
J. Nucl. Med. 12, Suppl. 5, 26-32 (1971).
8
O. W. Press, J. F. Eary, C. C. Badger, P. J. Martin, F. R. Appelbaum,
R. Levy, R. Miller, S. Brown, W. B. Nelp, K. A. Krohn, D. Fisher, D.
DeSantes, B. Porter, P. Kidd, E. D. Thomas, and I. D. Bernstein,
“Treatment of refractory non-Hodgkin’s lymphoma with radiolabeled
MB-l (anti-CD37) antibody,” J. Clin. Onc. 7(8), 1027-1038 (1989).
9
M. S. Kaminski, L. M. Fig, K. R. Zasadny. K. F. Koral, R. B. DelRosario, I. R. Francis, C. A. Hanson, D. P. Normolle, E. Mudgett, C.
P. Liu, S. Moon, P. Scott, R. A. Miller, and R. L. Wahl, “Imaging,
dosimetry, and radioimmunotherapy with iodine-131-labeled antiCD37 (MB-l) antibody in B-cell lymphoma,” J. Clin. Onc. 10(11),
1696-1711 (1992).
10
K. Koral, K. Zasadny, and M. Fayez, “Importance of intra-therapy
SPECT imaging in calculating tumor dosimetry for a lymphoma patient,” Eur. J. Nucl. Med. 18, 432-435 (1991).
11
S. J. DeNardo, G. L. DeNardo, L. F. O’Grady, N. B. Levy, S. L. Mills,
D. J. Macey, J. P. McGahan, C. H. Miller, and A. L. Epstein, “Pilot
studies of radioimmunotherapy of B cell lymphoma and leukemia using
1 -131 LYM-1 monoclonal antibody,” Antib., Immunoconj. Radiopharm. 1(1). 17-33 (1988).
12
D. M. Goldenberg, J. A. Horowitz, R. M. Sharkey, T. C. Hall, S.
Murthy, H. H. Goldenberg, R. E. Lee, R. Stein, J. A. Siegel, D. O.
Izon, K. Burger, L. C. Swayne, E. Belisle, H. J. Hansen, and C. M.
Pinsky, “Targeting, dosimetry, and radioimmunotherapy of B-cell lymphomas with 131I-labeled LL2 (EPB-2) monoclonal antibody,” J. Clin.
Oncol. 9, 548-564 (1991).
13
D. A. Scheinberg, D. J. Straus, S. D. Yeh, C. Divgi, P. Garin-Chesa,
M. Graham, K. Pentlow, D. Coit, H. F. Oettgen, and L. J. Old, “A
phase I toxicity, pharmacology, and dosimetry trial of monoclonal antibody OKB7 in patients with non-Hodgkin’s lymphoma: Effects of
tumor burden and antigen expression,” J. Clin. One. 8(5), 792-803
(1990).
14
S. T. Rosen, A. M. Zimmer, R. Goldman-Leikin, L. I. Gordon, J. M.
Kazikiewicz, E. H. Kaplan, D. Variakojis, R. J. Marder, M. S.
Dykewicz, A. Piergies, E. A. Silverstein, H. H. Roenigk Jr., and S. M.
Spies, “Radioimmunodetection and radioimmunotherapy of cutaneous
T cell lymphomas using an 131I-labeled monoclonal antibody: An Illinois Cancer Council study,” J. Clin. Onc. 5(4), 562-573 (1987).
15
R. E. Lenhard, S. E. Order, J. J. Spunberg, S. O. Asbell, and S. A.
Leibel, “Isotopic immunoglobulin: A new systemic therapy for advanced Hodgkin’s disease,” J. Clin. Oncol. 3, 1296-1300 (1985).
16
H. M. Vriesendorp, J. M. Herpst, P. K. Leichner, J. L. Klein, and S. E.
Order, “Polyclonal 9 0yttrium labeled antiferritin for refractory
Hodgkin’s disease,” Int. J. Radiat. Oncol. Biol. Phys. 17, 815-821
(1989).
17
S. E. Order, H. M. Vriesendorp, J. L. Klein, and P. K. Leichner, “A
phase I study of 90yttrium antiferritin: dose escalation and tumor dose,”
Antib. Immunoconj. Radiopharm. 1, 163-168 (1988).
591
Meredith et al.: Dosimetry of solid tumors
18
P. K. Leichner, J. L. Klein. J. B. Garrison, R. E. Jenkins, E. L. Nickoloff, D. S. Ettinger, and S. E. Order, “Dosimetry of 131I-labeled antifenitin in hepatoma: A model for radioimmunolglobulin dosimetry,”
Int. J. Radiat. Oncol. Biol. Phys. 7, 323-333 ( 1981).
19
P. K. Leichner, N. C. Yang, T. L. Frenkel, D. M. Loudenslager, W. G.
Hawkins, J. L. Klein, and S. E. Order, "Dosimetry and treatment
planning for y-labeled antiferritin in hepatoma:" Int. J Radiat. Oncol. Biol. Phys. 14, 1033-1042 (1988).
20
S. E. Order, G. B. Stillwagon, J. L. Klein, P. K. Leichner, S. S. Siegelman, E. K. Fishman, D. S. Ettinger, T. Haulk, K. Kopher, K. Finney,
M. Surdyke, S. Self, and S. Leibel, “Iodine-131-antiferritin, a new treatment modality in hepatoma: a Radiation Therapy Oncology Group
Study,” J. Clin. Oncol. 3, 1573-1582 (1985).
21
R. F. Meredith, M. B. Khazaeli, G. Plott, M. N. Saleh, T. Liu, L. F.
Allen, C. D. Russell, R. A. Orr, D. Colcher, J. Schlom, D. Shochat, R.
H. Wheeler, and A. F. LoBuglio, “Phase I trial of 131I-chimeric B72.3
in metastatic colorectal cancer,” J. Nucl. Med. 33(l), 23-29 (1992).
22
R. L. Vessella, “Radioimmunoconjugates in renal cell carcinoma,” in
Immunotherapy of Renal Cell Carcinoma, edited by F. M. J. Debruyne,
R. M. Bukowski, J. E. Pontes, and P. H. M. de Mulder (Springer
Verlag, Heidelberg, 1991), pp. 38-46.
23
P. Riva, G. Moscatelli, S. Lazzari, M. Agostini, G. Sarti, A. Spinelli, G.
Vecchietti, R. Gasperoni, D. Tirindelli, and G. Franceschi, “Systemic
and locoregional administration of labelled MOABS for gastrointestinal cancer radioimmunotherapy: Biokinetics, pharmacokinetics and
dosimetry aspects,” J. Nucl. Med. 30, 779 (1989).
24
R. H. J. Begent, J. A. Ledermann, A. J. Green, K. D. Bagshawe, S. J.
Riggs, F. Searle, P. A. Keep, T. Adam, R. G. Dale, and M. G. Glaser,
“Antibody distribution and dosimetry in patients receiving radiolabeled antibody therapy for colorectal cancer,” Br. J. Cancer 60, 406412 (1989).
25
J. A. Siegel, D. A. Pawlyk, R. E. Lee, N. L. Sasso, J. A. Horowitz, R.
M. Sharkey, and D. M. Goldenberg, “Tumor, red marrow, and organ
dosimetry for 131I-labeled anti-carcinoembryonic antigen monoclonal
antibody,” Cancer Res. Suppl. 50, 1039-1042 ( 1990).
26
G. B. Stillwagon, S. E. Order, J. L. Klein, P. K. Leichner, S. A. Leibel,
S. S. Siegelman, E. K. Fishman, D. S. Ettinger, T. Haulk, K. Kopher,
S. M. Brown, and K. Finney, “Multi-modality treatment of primary
nonresectable intrahepatic cholangiocarcinoma with 131I anti-CBA-a
Radiation Therapy Oncology Group study,” Int. J. Radiat. Oncol.
Biol. Phys. 13, 687-695 ( 1987).
27
J. A. Carrasquillo, K. A. Krohn, P. Beaumier, R. W. McGuffin, J. P.
Brown, K. E. Hellstrom, I. Hellstrom, and S. M. Larson, “Diagnosis of
and therapy for solid tumors with radiolabeled antibodies and immune
fragments,” Cancer Treat. Rep. 68, 317-328 (1984).
28
L. Lashford, D. Jones, J. Pritchard, F. Breatnach, and J. T. Kemshead,
“Therapeutic application of radiolabeled monoclonal antibody UJ13A
in children with disseminated neuroblastoma,” NCI Monogr. 3, 53
(1987).
29
R. W. Schroff, P. L. Weiden, J. Appelbaum, M. F. Fer, H. Breitz, J. L.
Vanderheyden, B. A. Ratliff, D. Fisher, D. Foisie, L. G. Hanelin, A. C.
Morgan, Jr., A. R. Fritzberg, and P. G. Abrams, “Rhenium-186 labeled antibody in patients with cancer: Report of a pilot Phase I
study,” Antib. Immunoconj. Radiopharm. 3, 99-110 ( 1990).
30
H. B. Breitz, D. R. Fisher, P. L. Weiden, J. S. Durham, B. A. Ratliff,
M. J. Bjom, P. L. Beaumier, and P. G. Abrams, “Dosimetry of
186
rhenium labeled monoclonal antibodies: Methods, prediction from
99m
Tc-labeled antibodies and results of Phase I trials.” J. Nucl. Med.,
July (1993).
31
H. B. Breitz, P. L. Weiden, J. L. Vanderheyden, J. W. Appelbaum, M.
J. Bjorn, M. F. Fer, S. B. Wolf, B. A. Ratliff, C. Seiler, D. C. Foisie, D.
R. Fisher, R. W. Schroff, A. R. Fritzberg, and P. G. Abrams, “Clinical
186
experience with rhenium-Iabeled monoclonal antibodies for radioimmunotherapy: Results of Phase I trials,” J. Nucl. Med. 33, 1099-1112
(1992).
32
A. M. Markoe, L. W. Brady, D. Woo, B. Amendola, U. Karlsson, S.
Fisher, B. Micaily. M. Rackover, S. Bulova, Z. Steplewski, and H.
Koprowski, “Treatment of gastrointestinal cancer using monoclonal
antibodies,” in Frontiers of Radiation Thempy Oncology, edited by J.
M. Vaeth and J. L. Meyer (Karger, Basel, 1990). Vol. 24, pp. 214-224.
33
B, A. Parker, A. B. Vassos, S. E. Halper, R. A. Miller, H. Hupf, D. G.
Amox, J. L. Simoni, R. J. Starr, M. R. Green, and I. Royston, “Radioimmunotherapy of human B-cell lymphoma with 90Y-conjugated
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
591
anti-idiotype monoclonal antibody,” Cancer Res. Suppl. 50, 1022-1028
(1990).
H. P. Kalofonos, T. R. Pawlikowska, A. Hemingway, N. CourtenayLuck, B. Dhokia, D. Snook, G. B. Sivolapenko, G. R. Hooker, C. G.
McKenzie, P. J. Lavender, D. G. T. Thomas, and A. A. Epenetos,
“Antibody guided diagnosis and therapy of brain gliomas using radiolabeled monoclonal antibodies against epidermal growth factor receptor and placental alkaline phosphatase,” J. Nucl. Med. 30, 1636-1645
(1989).
35
P. Riva, A.. Arista, G. Mariani, E. Seccamani, S. Lazzari, S. G. Moscatelli, C. Sturiale, G. Sarti, G. Franceschi, A. Spinelli, G. Vecchietti,
N. Riva, P. Natali, and P. L. Zardi, “Improved tumor targeting by
direct intralesional injection of radiolabeled monoclonal antibody: A
phase I study in brain glioma,” J. Nucl. Med. 32(5), 922 (1991).
36
S. J. DeNardo, K. A. Warhoe, L. F. O’Grady, D. J. Macey, A. H.
Gobuty, I. Hellstrom, K. E., Hellstrom, L. W. Kroger, and G. L.
DeNardo, “Response to 131I chimeric MoAb L-6 radioimmunotherapy
in patients with advanced metastatic breast cancer,” J. Nucl. Med.
32(5), 922 (1991).
37
S. J. DeNardo, K. A. Warhoe, L. F. O’Grady, G. L. DeNardo, I.
Hellstrom, K. E. Hellstrom, and S. L. Mills, “Radioimmunotherapy
with I-131 chimeric L-6 in advanced breast cancer,” in Breast Epithelial AnTigem, edited by R. L. Ceriani (Plenum, New York, 1991).
38
R.. B. Richardson, J. T. Kemshead, A. G. Davies, G. E. Staddon, P. C.
Jackson, H. B. Coakham, and L. S. Lashford, “Dosimetry of intrathecal Iodine”’ monoclonal antibody in cases of neoplastic meningitis,” Eur. J. Nucl. Med. 17, 42-48 (1990).
39
S. M. Larson, J. A. Carrasquillo, D. C. Colcher, K. Yokoyama, J. C.
Reynolds, S. A. Bacharach, A. Raubitchek, L. Pace, R. D. Finn, M.
Rotman, M. Stabin, R. D. Neumann, P. Sugarbaker, and J. Schlom,
“Estimates of radiation absorbed dose for intraperitoneally administered iodine-131 radiolabeled B72.3 monoclonal antibody in patients
with peritoneal carcinomatoses,” J. Nucl. Med. 32, 1661-1667 (1991).
40
L. W. Brady, D. V. Woo, A. Markoe, S. Dadparvar, U. Karlsson, M.
Rackover, R. Peyster, J. Emrich, C. Miyamoto, Z. Steplewski, and H.
Koprowski, “Treatment of malignant gliomas with 125I labeled monoclonal antibody against epidermal growth factor receptor,” Antibody,
Immunoconjug. Radiopharm. 3 (3), 169-179 (1990).
41
P. Leichner and C. Kwok, “Calculation methods,” Med. Phys. 20,
569-577 (1993).
42
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
43
G. M. Makrigiorgos, S. J. Adelstein, and A. I. Kassis, “Limitations of
conventional internal dosimetry at the cellular level,” J. Nucl. Med. 30,
1856-1864 (1989).
44
G. J. Hine and G. L. Brownell, Radiation Dosimetry (Academic, New
York, NY, 1956). Chap. 16, pp. 734-735.
45
L. F. Mausner and S. C. Srivastava, “Selection of radionuclides for
radioimmunotherapy,” Med. Phys. 20, 503-509 (1993).
46
J. L. Humm, J. C. Roeske, D. R. Fisher, and G. T. Y. Chen, “Microdosimetric concepts in radioimmunotherapy,” Med. Phys. 20, 535-541
(1993).
47
M. Roselli, J. Schlom, O. A. Gansow, A. Raubitschek, S. Mirzadeh, M.
W. Brechbiel, and D. Colcher, “Comparative biodistributions of
yttrium- and indium-labeled monoclonal antibody B72.3 in athymic
mice bearing human colon carcinoma xenografts,” J. Nucl. Med. 30,
672-682 (1989).
48
J. Orear, A. H. Rosenfeld, and R. A. Schuter, Nuclear Physics, A course
Given by Enrico Fermi at the University of Chicago, Revised Edition,
(University of Chicago, Chicago, IL, 1950). Chap. 1, pp. 43-47.
49
L. M. Lamki, J. Kavanagh, M. G. Rosenblum, J. L. Murray, D. Podoloff, T. Burke, V. Bhadkamkar, L. Thompson, J. Shanken, J. Cunningham, E. E. Kim, R. T. MaGuire, and T. P. Haynie, “Intraperitoovarian
cancer
with
neal
radioimmunotherapy of
90
yttrium-GYK-DTPA-B72.3 antibody: Tissue distribution, pharmacokinetics, toxicity, and bremsstrahlung imaging,” J. Nucl. Med. 31,
724 (1990).
50
L. E. Williams, J. Y. C. Wong, D. O. Findley, and B. W. Forell
“Measurement and estimation of organ bremsstrahlung radiation
dose,” J. Nucl. Med. 30, 1373-1377 (1989).
51
M. G. Stabin, K. F. Eckerman, J. C. Ryman, and L. E. Williams,
“Bremsstrahlung dosimetry component in Y-90 monoclonal antibody
therapy,” J. Nucl. Med. 29, 926 (1988).
52
W. S. Snyder, M. R. Ford, and G. G. Warner, “Estimates of specific
34
592
Meredith et al.: Dosimetry of solid tumors
absorbed fractions for photon sources uniformly distributed in various
organs of a heterogeneous phantom,” NM/MIRD Pamphlet No. 5,
Revised.
53
G. Sgouros, G. Barest, J. Thekkumthala, C. Chui, R. Mohan, R. E.
Bigler, and P. B. Zanzonico, “Treatment planning for internal radionuclide therapy: Three-dimensional dosimetry for nonuniformly distributed radionuclides.” J. Nucl. Med. 31, 1884-1891 (1990).
54
R. L. Ford and W. R. Nelson, “The EGS code system,” Stanford
Linear Accelerator Center Report. (210) Stanford, California ( 1978).
55
D. W. O. Rogers and A. F. Bielajew, “Experimental benchmarks of
EGS,” in Monte Carlo Transport of Electrons and Photons, edited by T.
M. Jenkins, W. R. Nelson and A. Rindi, (Plenum, New York, 1988).
56
M. J. Berger and S. M. Seltzer, “ETRAN, Monte Carlo code system for
electron and photon transport through extended media,” ORNL documentation for RSIC computer code package CCC-107 (1973).
57
I.. J. Das, “An empirical method for beta-ray dosimetry at a homogeneous plane interface,” Phys. Med. Biol. 32 (12), 1609-1613 (1987).
58
T. K. Johnson and R. L. Vessella, “A generalized dosimetry schema for
tumor preferential uptake of monoclonal antibodies in radionuclide
immunotherapy,” J. Nucl. Med. Suppl. 28(4), 680 ( 1987).
59
T. K. Johnson, “MABDOS: A generalized program for internal radionuclide dosimetry,” Comput. Meth. Progr. Biomed. 27, 159-167
(1988).
60
C. S. Kwok, P. J. Bialobzyski, S. K. Yu, and W. V. Prestwich, “Effect
of tissue inhomogeneity on dose distribution of point sources of lowenergy electrons,” Med. Phys. 17(5), 786-793 (1990).
61
T. K. Johnson and R. L. Vessella, “On the possibility of ‘real-time’
Monte Carlo calculations for the estimation of absorbed dose in radioimmunotherapy,” Comput. Meth. Progr. Biomed. 29, 205-210 (1989).
62
T. K. Johnson and R. L. Vessella, “On the application of parallel
processing to the computation of dose arising from the internal deposition of radionuclides,” Comput. Phys. 3, 69-72 (1989).
63
B. W. Wessels and M. H. Griffith, “Miniature thermoluminescent dosimeter absorbed dose measurements in tumor phantom models,” J.
Nucl. Med. 27, 1308-1314 (1986).
64
D. J. Gladstone, D. G. Chin, and L. M. Chin, “Automated data collection and analysis system for MOSFET radiation detectors,” Med.
Phys. 18(3), 542-548 (1991).
65
V. K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 (1988).
66
J. L. Lear, R. K. Kasliwal, A. J. Feyerabend, J. P. Pratt, P. A. Bunn,
D. G. Dienhart, R. Gonzalez, T. K. Johnson, D. C. Bloedow, S. W.
Maddock, and S. D. Glenn, “Improved tumor imaging with radiolabeled monoclonal antibodies by plasma clearance of unbound antibody
with anti-antibody column,” Radiology 179, 509-5 12 (1991).
67
T. K. Johnson, S. Maddock, R. Kasliwal, D. Bloedow, C. Hartmann,
A. Feyerabend, D. G. Dienhart, D. Thickman, S. Glenn, R. Gonzalez,
Medical Physics, Vol. 20, No. 2. Pt. 2, Mar/Apr 1993
592
J. Lear, and P. Bunn, Jr., “Radioimmunoadsorption of KC-4G3 antibody in peripheral blood: Implications for radioimmunotherapy,” Antib. Immunoconj. Radiopharm. 4 (4), 885-893 (1991).
68
A. F. LoBuglio, R. H. Wheeler, J. Trang, A. Haynes, K. Rogers, E. B.
Harvey, L. Sun, J. Ghrayeb, and M. D. Khazaeli, “Mouse/human
chimeric monoclonal antibody in man: Kinetics and immune response,” Proc. Natl. Acad. Sci. U.S.A. 86, 4220-4224 ( 1989).
69
R. F. Meredith, M. B. Khazaeli, W. E. Plott, I. A. Brezovich, C. D.
Russell, R. H. Wheeler, S. A. Spencer, and A. F. LoBuglio, “Comparison of two mouse/human chimeric antibodies in patients with metastatic colon cancer,” Antibod. Immunoconj. Radiopham. 5 (1), 75-80
(1992).
70
R. Meredith, G. Plott, I. Brezovich, M. Khazaeli, C. Russell, R.
Wheeler, M. Saleh, T. Simpson, A. Haynes, L. Allen, R. Orr, T. Baker,
S. Spencer, M. Hardin, M. Salter, and A. LoBuglio, “Comparative
dosimetry with repeat courses of 131I-labeled murine or mouse/human
chimeric monoclonal antibodies,” Int. J. Radiat. Oncol. Biol. Phys. 19,
Suppl. 1, 252 (1990).
71
J. B. Slater, J. M. Frincke, D. R. Stickney, and G. A. Kirk, “The role
of CEA as a metabolic indicator to predict the pharmacokinetics of the
bifunctional antibody system (BFA) in colon carcinoma,” J. Nucl.
Med. 30, 905 (1989).
72
J. M. Berkopec, E. Bradley, B. W. Wessels, D. F. Palme, L. Mantilla,
and R. L. Vessella, “Combined external beam irradiation (XRT) and
radioimmunotherapy (RIT) on renal cell carcinoma xenografts,” J.
Nucl. Med. 30 (5), 406 (1989).
73
L. E. Dillehay and J. R. Williams, “Radiobiology of dose-rate patterns
achievable in radioimmunoglobulin therapy,” in Frontiers of Radiation
Therapy and Oncology edited by J. M. Vaeth and J. L. Meyers
(Karger, Basel, 1990), Vol. 23, 93-103.
74
R. L. Vessella, D. F. Palme, J. M. Berkopec, M. K. Elson, B. W.
Wessels, E. W. Bradley, and P. H. Lange, “Radiotherapy of human
renal cell carcinoma (RCC) xenograft: Comparison between single
fraction monoclonal antibody (MoAb) A6H 131-iodine conjugates and
single fraction x-ray external beam irradiation,” Am. Assoc. Cancer
Res. 29, 1707 (1988).
75
S. J. Knox, R. Levy, R. A. Miller, W. Uhland, J. Schiele, W. Ruehl, R.
Finston, P. Day-Lollini, and M. L. Goris, “Determinants of the antitumor effect of radiolabeled monoclonal antibodies,” Cancer Res. 50,
4935-4940 (1990).
76
B. W. Wessels, R. G. Vessella, D. F. Palme, J. M. Berkopec, G. K.
Smith, and E. W. Bradley, “Radiobiological comparison of external
beam irradiation and radioimmunotherapy in renal cell carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 17, 1257-1263 (1989).
77
V. K. Langmuir and R. M. Sutherland, “Radiobiology of radioimmunotherapy,” Antibod. immunoconj. Radiopharm. 1, 195-211 (1988).
Dosimetry of intraperitoneally administered radiolabeled antibodies
John C. Roeske and George T. Y. Chen
Michael Reese/University of Chicago, Center for Radiation Therapy, Department of Radiation
and Cellular Oncology, University of Chicago, Chicago, Illinois 60637
A. Bertrand Brill
University of Massachusetts, Worcester, Massachusetts
(Received 18 March 1992; accepted for publication 24 December 1992)
Intraperitoneal and intracavitary radioimmunotherapy differ from other approaches of radioimmunotherapy in that high activity and dose gradients exist near the solution/tumor interface.
Dose to tumor and normal tissue at the interface is a function of depth and is due to three major
components: (1) the activity concentration of the administered radiolabeled antibody solution
as a function of time within the compartment; (2) the spatial distribution of antibody/
radionuclide complex as a function of depth and time as the biomolecules bind to and permeate
tumor/normal tissues; and (3) the physical characteristics of the radionuclide in relation to
depth of antibody penetration. In this review, the biological and physical aspects of intraperitoneally administered radiolabeled antibodies are discussed, and the state of experimental and
calculational studies for this site is described. Areas requiring future investigation are examined,
and recommendations are made regarding the type of measurements and calculations which are
required for accurate dosimetry.
Key words: intraperitoneal radioimmunotherapy, dosimetry, models, alpha and beta emitters
1. INTRODUCTION
Regional administration of radiolabeled antibodies for
therapeutic intent is advantageous because this approach
delivers relatively high concentrations of biologically specific molecules directly to the site of the disease, thus providing a high tumor-to-normal tissue (T/NT) dose ratio.
Possible anatomic sites include the peritoneum for
ovarian 1-12 and colorectal carcinomas,13-14 the cerebral spinal fluid for leptomeningeal disease, 15,16 the thoracic cavity
for the treatment of pleural/pericardial effusions, 17,18 a n d
within the tumor itself in the therapy of cystic brain
tumors.” In recent years, pilot studies in humans have
shown partial or complete responses to intraperitoneal radioimmunotherapy (IPRIT), spurring additional interest
in this technique. The dose to tumor and normal tissues is
difficult to quantify, yet an understanding of the dosimetry
of radiolabeled antibodies is important in interpreting clinical results and in defining directions to make this type of
treatment more effective. In this review, we discuss (a) the
clinical rationale for IPRIT, (b) those biological and physical parameters which most strongly affect the dose distribution to tumor, (c) the current status of dose measurement and calculations for IPRIT, and (d) research goals
and future directions for IPRIT dosimetry. We focus on
intraperitoneal radioimmunotherapy in the treatment of
ovarian tumors spread to this site. However, the dosimetric
analysis discussed may be applied, with appropriate modification, to other regions treated with a similar methodology.
Ovarian cancer is one of highest causes of mortality
among gynecologic cancers in the western world. The
American Cancer Society has estimated approximately
19 000 new cases were diagnosed in 1986, of which 60% of
593
Med. Phys. 20 (2). Pt. 2, Mar/Apr 1993
these will eventually die due to complications from the
disease. 20 The malignancy originates in the ovaries and is
generally detected during Stage III or IV of the disease,
when it has metastasized to the surface of the peritoneum.
At this stage, only a 10%-20% 5-year survival is
predicted. 2 0 Conventional treatment of this disease involves surgical debulking of the primary tumor, followed
by a regimen of chemotherapy and/or radiation
therapy2 1’ 2 2 to the regions at risk for spread. Because of the
diffuse nature of peritoneal disease, treatment of the entire
abdomen to 2500 cGy is prescribed with external beam
radiation therapy. 22 This dose is inadequate for gross disease, but is limited by normal tissue tolerance of critical
abdominal and pelvic organs. In order to augment the external beam dose, Au-198 colloids 23 and radioactive chromic phosphate (P-32 colloids) 24-26 have been administered
directly into the peritoneal cavity for the treatment of ovarian metastases. However, with lack of specificity, there is
no tumor-to-normal tissue dose advantage. 23-26 Thus a modality is required in which a high dose of radiation is delivered to tumor while limiting the dose to normal tissues.
This is the goal of intraperitoneal radioimmunotherapy.
II. A CONCEPTUAL MODEL FOR IPRIT
DOSIMETRY
In principle, the dose to tumor and normal tissues may
be calculated if the concentration of radioactivity is known
in each volume element of the body as a function of time.
In practice, such detailed knowledge is impossible to obtain. Nevertheless, the formulation of a simplified model
aids in identifying those factors which most significantly
influence the dose distribution and parameters which need
to be measured to reliably estimate the dose.
0094-2405/93/020593-08$01.20
© 1993 Am. Assoc. Phys. Med.
593
594
Roeske et al.: Dosimetry of radiolabeled antibodies
To conceptualize the biological distribution of activity,
consider the following sequence of “events.” Initially, a
therapeutic quantity of radiolabeled antibody is injected
into a cavity of the body which contains the targeted malignancy (i.e, peritoneal cavity). Antibody removal from
the compartment and redistribution occurs through lymphatic and blood circulatory systems. 27-29 A fraction of the
administered antibodies will bind to antigens expressed on
the surface of tumor cells, and to a lesser degree, antigens
expressed on the surface of normal tissue cells. Because of
the high affinity the antibody has for the antigen, penetration within bulk disease may be limited to several cell
layers. 2 9 At later times, activity which escapes from the
peritoneal cavity into the blood may also accumulate
within tumor through vascularization. The therapeutic effect of the treatment will depend on the total dose to tumor
as a function of depth, dose rate, and relative biological
effectiveness of the radiation.
A. Tumor and normal tissue geometry
Geometrical aspects of both tumor and normal tissue,
such as size and shape, influence the dose to these tissues.
There are two principle reasons why the tumor size and
geometry are important for accurate dosimetry. First, antibody uptake per gram of tumor is inversely proportional
to the tumor mass. Typically, the tumor to normal tissue
ratios for the accumulation of activity range from 0.1-8.5
for large tumors, and from 2-8700 for small tumors. 4 ’ 6 ’ 7
Second, similar to external beam therapy, it is expected the
shape of isodose curves within tumor will conform to the
shape of the tumor. If the activity is uniformly distributed
within tumor, the geometry will not be as critical. However, for cases of nonuniform activity confined to the tumor periphery, as observed on tumor autoradiographs, the
tumor geometry may significantly affect the degree to
which the tumor may be treated (see Sec. III C). Additionally, the size of the tumor, in relation to the maximum
range of particulate radiation, will influence the degree of
dose uniformity.
Individual tumor cells or clusters of tumor cells in suspension in ascites define one geometrical condition. However, in IPRIT of colorectal and ovarian carcinoma, the
targets are small metastases from 1 mm to 1 cm in diameter on the surface of the peritoneum. Lesions greater than
2 cm are not considered since these are significantly more
difficult to control.8,9,11 Unlike external beam radiation
therapy, the geometry and the size distribution of the target volumes are generally not well specified. Chatal et al. 30
and Thedrez et al. 31 have demonstrated small ovarian tumor nodules (<5 mm diameter) are nearly spherical
However, visual inspection of biopsy samples of peritoneal
tumor metastases shows the geometry may vary from the
idealized spherical form.32 Laparoscopy may be performed
prior to radioimmunotherapy to assess the volume of the
residual disease to be treated. 8’ 9,11 This method may also be
used to provide some insight into the tumor geometry.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
594
F I G. 1. Schematic diagram of the initial source distribution following
injection of radiolabeled antibody solution into peritoneal cavity. The
peritoneum is represented as a plane, and tumor extends both above and
into the peritoneal surface. Immediately following the infusion, the solution is confined to the peritoneal cavity.
B. Dose components
Dose to individual tumor cells is due to radionuclides
which decay within the maximum range of particulate
emissions (alphas, betas, and Auger electrons), and potentially from all radionuclides which emit photon radiation.
The three dose components to an arbitrary point in tumor
or normal tissue include: (a) dose from solution activity,
(b) dose from the radionuclide/antibody complex specifically bound to the tissues, and (c) dose from activity accumulating in other parts of the body after escape from the
peritoneal cavity.
C. Solution activity
The dependence of dose from nuclear decays in the IP
administered solution as a function of tissue depth can be
understood through a simple model. Consider the peritoneal cavity as semi-infinite plane, above which resides a
uniform solution of radiolabeled antibodies (Fig. 1). This
approximation is valid when the maximum range (R m a x)
of the particulate radiation (for example, Y-90-R m a x=1.1
cm) is much smaller than the radius of curvature of the
solution/tissue interface. Initially after infusion into the
peritoneal cavity, most of the activity will be confined to
the peritoneal solution. Cells on the surface of the cavity
receive dose from those sources of particulate radiation
which decay within R m a x of the point of calculation. Therefore, these cells are irradiated from sources which decay
within a hemisphere of radius R max as shown in Fig. 2.
Cells deeper in the peritoneal tissue will receive a dose
from a spherical segment which diminishes in volume with
increasing depth. Those cells which are at depths deeper
than Rm a x will not receive dose from the peritoneal source
distribution. The total dose which tumor and normal tissues receive from the solution activity will be proportional
to the number of decays within the spherical segment
above the peritoneal surface. Hence, the critical parameter
in calculating the peritoneal source component to the tumor dose will be the activity concentration in the peritoneal solution as a function of time.
The total quantity of radioisotope administered and the
infusion volume are parameters which are often specified in
the literature to describe the characteristics of the irradiating solution.1 - 1 2 For IPRIT, typical initial quantities of
595
Roeske et al.: Dosimetry of radiolabeled antibodies
F IG. 2. Diagram of the contribution of the solution activity to peritoneal
tumors/tissues. For cells located near the surface, the dose from solution
is due to sources which decay within a hemisphere of radius R max Cells
located deeper within the peritoneal surface receive dose from those
sources which decay within a spherical segment. The volume of the spherical segment decreases with depth such that at a depth equal to the
maximum range, there is no contribution of dose from the solution
activity.
activity range from 100 to 157 mCi for I-131, and from 5 to
20 mCi for Y-90 in 1.5 liters of normal saline. 11 However,
in addition to the infusion volume, the total volume of fluid
within the peritoneal cavity is crucial to provide an accurate estimate of the dose from the initial solution activity.
The solution activity as a function of time is a parameter
which is potentially measurable. In theory, the peritoneal
fluid may be periodically sampled during therapy through
the Tenckoff catheter. Additionally, the fluid activity may
also be quantitated through serial conjugate views obtained
from a gamma camera. However, activity within surrounding organs may obfuscate the peritoneal source distribution. Another approach which is useful in determining the
cumulated activity in the peritoneal fluid is through TLD
measurements. Thermoluminescent dosimeters (TLDs)
placed within the peritoneal cavity may provide a direct
dose measurement of the contribution of the peritoneal
source distribution (see Sec. III A).
D. Tumor activity gradients
Radiolabeled antibodies accumulate preferentially in
tumor (Fig. 3), and can also cross react to antigens in
normal tissue (nonspecific binding). Specific binding of radiolabeled antibodies provides the major component of the
dose to the tumor cells. A critical parameter for dose estimation is the activity as a function of time and depth associated with the tumor. When single cells in solution are
595
the targets, the activity as a function of time may be estimated through an in vivo assay. An aliquot of cells within
the radiolabeled antibody solution is taken, spun down,
and separated from the solution at various times and
counted. The production of a time activity curve may be
utilized in calculating the dose to the nucleus due to the
activity on an individual cell, and if the emission has a long
range, due to the ensemble of activity from other cells
within the volume.
The activity distributed in a solid tumor is nonuniform
due to the high affinity of the antibody, and the heterogeneous expression of antigen. 3 3’ 34 Studies by Dedrick and
Flessner35 with radiolabeled serum albumin suggest that
biological macromolecules diffuse into the parietal and visceral tissues of the peritoneum to different depths, and its
concentration versus depth is a function of both tissue type
and molecular weight. Experiments with colon carcinoma
spheroids, irradiated in a solution of radiolabeled antibodies specific for carcinoembryonic antigen (CEA), show activity gradients are a maximum at the tumor surface with
penetration limited to l-3 cell layers. 3 6
Tumor activity is often quantitated through gross biopsy samples. Tumor and normal tissue samples obtained
after sufficient antibody localization have been counted intact in a well counter in numerous biodistribution studies.
A quantity often quoted is the percent injected dose per
gram of tumor (% I.D./g), which represents the percent
of the injected activity which accumulates per gram of
tumor. The percent injected dose per gram of tumor for
intraperitoneally administered radiolabeled antibodies may
vary from 0.001% to 0.1%, or greater. 6 ’ 7 This uptake is a
function of the size of the antibody (IgG, Fab’2, Fab),
antibody affinity or avidity, and the mass of the tumor. 3 7,3 8
While the percent injected dose/g is useful for comparison
of therapeutic effectiveness to indicate relative uptake, it
provides little information on the spatial or temporal distribution of activity, which is essential for accurate tumor
dosimetry. Assumptions concerning the distribution of activity within the gross tissue samples must therefore be
made to utilize these data for dosimetry.
Animal experiments and tumor autoradiography may
provide the spatial and temporal data on tumor and normal tissue activity needed to calculate dose. However, as
with all animal experiments, extrapolation to man is difficult and complex. Pharmacokinetic modeling, such as
work performed by Fujimori et al. 39-41 and Baxter and
Jain, 4 2 has elucidated the distribution of activity within
tumor models for intravenous administrations. These models will be useful in assessing the dose from activity which
escapes into the blood and accumulates in the tumor
through this pathway. Modifications to these calculations
may also result in the ability to provide detailed models of
the percolation of activity from the intraperitoneal solution
into the tumor.
E. Physical characteristics of radionuclides
F I G. 3. Schematic diagram of the distribution of activity at time following infusion. A fraction of the activity which was originally in the intraperitoneal solution has penetrated and bound to peritoneal tissues.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
The physical characteristics of the radionuclide
which influence the dose distribution include the half-life,
energy of emissions and type of radiation. The physical
596
596
Roeske et al.: Dosimetry of radiolabeled antibodies
half-life in relation to the biological half-life of antibody
removal from the cavity will determine the fraction of dose
received from the injectate solution. If the physical half-life
is long with respect to the rate of egress, the dose from the
solution may be minimal. However, if the physical half-life
is short compared to the biological half-life, a large fraction
of the dose to the tumor will be from the radionuclides in
solution. Additionally, these sources will irradiate normal
structures within the cavity, and thus may provide a dose
limiting criterion.
The distribution of antibody within tumor is due to multiple processes.33,34 Consider a simple example in which
diffusion is the dominating process. The time for an antibody to uniformly infiltrate a tumor to a death of 1 mm is
approximately 3 days, while the time to reach a depth of
2.5 mm is 18 days. 3 4 Thus radionuclides with short half
lives will decay near the periphery of the tumor, and the
dose to deeper portions of the tumor from these emissions
may be small. Longer lived radionuclides may provide a
more uniform dose to tumor because a fraction of these
will penetrate into the tumor before decaying. However,
the use of a longer lived radionuclide also results in increased normal tissue dose.
It is also important to examine the depth of penetration
of antibody/radionuclide complex in relation to the range
of the particulate radiation. For example, the depth dose
curve from energetic beta particles of Y-90 (R m a x= 1 . 1
cm) is insensitive to antibody convection and diffusion on
the order of several hundred microns. The reason the depth
dose curve does not vary significantly is because the depth
of penetration represents a small fraction of the maximum
range (see Sec. III C). However, the microscopic depth
dose distribution for alpha emitters (R m a x<100µm) will
be strongly influenced by a penetration depth of several
hundred microns because this distance is much greater
than the maximum range.
F. Activity throughout the body
In principle, the dose to tumor from the remainder of
the body is negligible. For particulate emissions, only those
normal tissues within the maximum particulate range will
contribute dose to the tumor. In the case of beta/gamma
emitters such as I-131, the dose to tumor from the gamma
emissions will most likely result in a constant background
dose. Estimates of the dose contribution from gamma emissions may be determined by using MIRD or image based
treatment planning.
G. Summary of conceptual model
To summarize, the important parameters in estimating
the dose to tumor are ( 1) the antibody/radionuclide solution activity as a function of time; (2) the concentration of
activity associated with the tumor as a function of time;
and (3) the relative rate and depth of antibody penetration
with respect to the half-life and range of particulate radiation. The following section describes the estimation of
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
dose to tumor for both clinical situations and based on
theoretical tumor architectures and antibody source configurations.
III. CURRENT STATUS: MEASUREMENT AND
CALCULATION OF TUMOR DOSE
In the previous section, a conceptual model described
the target specification and the distribution of radiolabeled
antibody with respect to this target. This section will report
the measurements and calculations of dose to tumor. The
role of each of these methods within the framework of the
proposed model will be discussed.
A. Dose measurements
Measurements of dose to peritoneal tissues has been explored principally through two methodologies. Direct measurement of dose with thermoluminescent dosimeters has
been investigated,8,11 where TLD chips are placed in a tube
which is passed into the peritoneal cavity. The advantage
of this technique is the cumulated dose is measured directly. However, spatial resolution is limited as well as
areas of access within the patient. Stewart et al. 8,11 r e ported inserting 20-35 LiF TLD catheters into patients
with ovarian cancer at laparoscopy, prior to radioimmunotherapy. The average nonspecific dose to the peritoneal
wall was estimated from these TLD readings at 374 cGy
(or 2.88 cGy/mCi of I-131) for human antimouse antibody (HAMA) negative patients, and 200 cGy (or 1.94
cGy/mCi of I-131) were measured in HAMA positive patients. These findings suggest that there may be increased
absorption of I-131 in HAMA positive patients due to antibody dehalogenation. Y-90 labeled antibodies resulted in
an average surface dose of 21.7 cGy/mCi of injected
activity.” The variations in the absorbed dose per mCi of
injected activity for I-131 and Y-90 are due to differences
in the effective half-life within the cavity and the energies
of the beta emissions. Within the previously discussed
model, the TLD measurements provide a direct dose from
the solution component at the peritoneal surface. However,
no information regarding the contribution of the solution
activity to the dose as a function of tissue depth is provided.
There are several technical difficulties associated with
the use of TLDs. Dose measurements as described above
provide an average dose estimate and cannot differentiate
easily between dose to tumor or normal tissue. If the TLD
is near the tumor mass, a high concentration of radiolabeled antibody (relative to the solution activity) on or
within the tumor will increase the measured dose signal.
Furthermore, since the peritoneal surface is convoluted,
regions where the radius of curvature is of the same order
of magnitude as the maximum range of the particulate
emissions may result in a measured dose which differs from
the average dose received by the surface. Additional information relating TLD position to the peritoneal source geometry may be obtained by a CT scan. Visualization and
extraction of peritoneal contours can be used to study the
variation of measured dose from the solution.
597
Roeske et al.: Dosimetry of radiolabeled antibodies
B. Activity measurements
Measurement of activity distributions within the patient
as a function of time provides input information into the
MIRD formalism to permit calculation of dose. 5,8-12,43,44
Dose to tumor can be calculated from the quantitation of
% ID/g in gross biopsy samples previously discussed. The
assumption that the activity is uniformly distributed
throughout the tumor mass is frequently made. For example, Hnatowich et al. 1 0 estimated the absorbed dose from
an Y-90 labeled antibody to several peritoneal tissues based
on activity measurements of tissue biopsies. Assuming the
tumor associated activity decayed in place from the time of
administration, these calculations yielded dose estimates of
48 cGy/mCi for tumor. Since these measurements are
based on a 1 mCi administration of the radiolabeled antibody, the activity required to deliver a therapeutic dose
(~50Gy) is approximately 100 mCi.
There are several limitations with this type of tumor
dose estimate. First, as Hnatowich et al. 10 discuss, the assumption of instantaneous uptake in the tumor results in
an overestimate of the cumulated activity, and hence overestimates the absorbed dose. This assumption results in an
underestimate of the therapeutic quantities of isotope
needed for therapy, as in the above example. Second, activity measurements are made and normalized to the mass
of tissue sampled. If an average value of the percent injected dose per gram is used, tumors smaller or larger than
the average tumor size will have larger and smaller values
of the percent injected dose per gram, respectively. Thus
the dose estimates will also be inaccurate. Third, the most
significant limitation of these dose studies is the assumption that activity within the tumor is uniform. If the activity is located primarily near the periphery of the tumor, the
outer portions of the tumor will receive a higher dose than
the central portions. However, while these types of calculations are inaccurate, they are simple to perform and the
biological data (tumor activity) are readily available. Additionally, since these calculations provide an upper tumor
dose limit, they are useful in determining if the administered quantities of radiolabeled antibody provide doses
which are within therapeutic ranges.
C. Calculation/dose modeling
IPRIT dose modeling on the multicellular scale has
been applied by several groups45-48 to study the distribution of dose within tumor and normal tissues. Unlike external photon beam treatment planning and modeling
(where parameters of the model yield relatively accurate
dose distributions), lack of detailed knowledge of the spatial distribution of activity on a very small geometric scale
prevents accurate calculation of dose in the peritoneum.
However, modeling permits the examination of those parameters which affect the isodose distribution and provides
an understanding of how these parameters should be altered to improve the dose distribution.
The scale of dose modeling is chosen to be of the same
order of magnitude of the maximum range of particulate
radiation from the radionuclide decay. Thus distance scales
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
597
range from 50 µm for alpha particle dose calculations to 1
cm for beta emissions. The source distribution is divided
into voxels of uniform activity, and the contribution of
each volume element to the calculation point is computed
by multiplying the number of decays in the volume element
by the appropriate value of the dose point kemel. 45-50 T h e
dose point kernel represents the distribution of dose as a
function of radial position from a point source emitter.
Details of the dose point kernel will be discussed in a separate paper in this issue. Dose calculations are performed
through a superposition process and the computation time
may be reduced by realizing the dose computation process
is a convolution process when the medium is homogeneous. This realization allows for the use of fast Fourier
convolution. 4 8
Bardies et al.45,46 modeled ovarian carcinomas as small
spherical nodules with a high uptake of radiolabeled antibody on the surface. Both the average dose to the sphere
and the dose as a function of radial position were computed for a number of beta emitters considered useful for
radioimmunotherapy. Comparison of the average dose
and dose distribution as a function of radial position
showed that the mean absorbed dose rate within a tumor is
a misleading quantity, since the dose rate varies as a function of distance within the tumor. Bardies extended the
calculations to alpha emitting radionuclides to spheroids of
radii of 5-200 µm. 4 6 The results of these calculations
showed that tumor dose is highly nonuniform. The calculations also showed that the optimal alpha particle energy
for small spherical cells (5 µm radius) is 2-3 MeV, while
the optimal energy for 200 µm spheres is more than 10
MeV.
Watson et al.47 presented a method for calculating the
dose as a function of depth to the peritoneal surface for the
planar geometry. Dose calculations for the planar geometry can be traced to Loevinger et al. 49 who originally presented methods for calculating the dose as a function of
depth to a planar surface from an infinite planar source.
Berger 5 0 extended the work of Loevinger and tabulated
information of the energy dissipation of electrons and common beta emitters in various media. Watson et a1. 47 developed a program which uses the work of Berger 49 in MIRD
Pamphlet No. 7 for the case when the source is uniformly
distributed over the surface in a thin layer. For volumetric
activity distributions above the plane, the contribution of
infinitely thin layers is integrated according to the method
of Loevinger et a1.,49 and the attenuation of the emissions
within the source distribution is taken into account. Tables
were produced for activity confined to a semi-infinite plane
(intraperitoneal solution) and for activity localized on the
surface of a plane (peritoneal surface). By using the appropriate combination of cumulated volumetric and surface activities, the dose as a function of depth to a planar
tumor may be calculated. For each of these dose components, the dose is a maximum at the peritoneal surface, and
decreases rapidly with depth. Typically, the dose decreases
to 50% of the maximum surface dose within 0.1-0.3 R max.
Absolute (versus relative) dose calculations for intraperitoneal administration of radiolabeled ‘antibodies
598
598
Roeske et al.: Dosimetry of radiolabeled antibodies
were performed by Roeske et al. 48 using data based on the
therapeutic quantities of radionuclides administered. A
model for the diffusion and convection of antibodies in
both tumor and normal tissues was used based on measurements of the distribution of human serum albumin in the
peritoneal tissues of mice. 29 Using reported values for the
percent injected dose per gram of tumor, isodose distributions were estimated to geometrical tumors consisting of
planes and hemispheres, representing the two extrema in
the peritoneum, as well as biopsy samples obtained from
second-look surgery.
As an example of the type of dose gradients which may
exist in IPRIT, consider a calculation based on the methodology of Roeske et al.48 The peritoneum is modeled as a
planar surface, above which lies a uniform solution of radiolabeled antibodies (see Fig. 1). Tumor extends below
and lateral to the solution/tissue interface. The depths of
tumors are chosen to be comparable to the range of the
particulate radiation. Tumor depths utilized in these calculations are 0.5, 0.1, and 0.03 cm, for Y-90 (beta emitter),
I-131 (beta/gamma emitter), and At-211 (alpha emitter),
respectively. The therapeutic activities used in this calculation for Y-90, I-131, and At-211 are 15, 120, and 6 mCi,
respectively. These activities are administered in approximately 1500 ml of saline solution. Values of the percent
injected dose per gram of tumor are chosen as 0.01% ID/g
for all isotopes. Furthermore, tumor uptake is assumed
instantaneous with all sources decaying in place. This assumption represents a best case scenario, and will result in
an estimate of the maximum dose distribution tumor will
receive.
Since the exact biodistribution within tumor is difficult
to know in vivo, three scenarios for the microscopic biodistribution of activity in tumor are considered. En the first
situation, the tumor activity is limited to the surface exposed to the peritoneal fluid. This is the worst case where
there is no penetration of the antibody into the tumor. In
the second case, the most favorable situation is considered
in which the radiolabeled antibody is distributed uniformly
throughout the tumor. These biodistributions bracket the
extremes for both activity and dose. A third, more realistic
situation is simulated in which an exponential diffusion
model is used with a half value depth of penetration equal
to approximately 50 µm.
The results of the dose calculations for the tumor depth
dose along the vertical axis are presented in Fig. 4. These
calculations reveal that: (1) when the tumor activity is
confined to the surface, the dose is a maximum at the
surface and falls off rapidly with depth, reaching a 50%
value within 0.1-0.3 R m a x, (2) when the activity is distributed uniformly throughout the tumor, all three radionuclides exhibit depth dose curves which are uniform except
toward the distal portions, and (3) except for At-211, the
effects of diffusion to a half value depth of 50 µm are
similar to the case of activity confined to the surface.
Dose modeling may be used to elucidate the dosimetric
relationship between the physical characteristics of the radionuclide and the biological source distribution within tumor. Important findings of the dose modeling on the mulMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
F I G. 4. Central axis depth dose curves for (a) Y-90, (b) I-131, and (c)
At-211. For each radionuclide, three possible tumor activity distributions
are simulated-activity limited to the tumor surface, activity uniformly
distributed within tumor, and activity diffused within tumor based on an
exponential activity gradient.
ticellular scale include: (a) the tumor is nonuniformly
irradiated over the range of particulate emission; (b) the
depth which receives therapeutic doses is often less than
the maximum particulate range; (c) the functional form of
the dose gradient is dependent upon the tumor source distribution; and (d) no single dose value accurately describes
the range of doses in IPRIT.
IV. SUMMARY AND FUTURE DIRECTIONS
We have developed a conceptual model which may be
used for determining those parameters which are required
for the accurate calculation of tumor dose for IPRIT.
599
Roeske et al.: Dosimetry of radiolabeled antibodies
Based on this model and the work of those in the field,
there are certain parameters which are required to provide
a crude dose estimate. The first quantity which is important is the concentration of antibody solution within the
cavity as a function of time. This quantity is necessary not
only for tumor dosimetry, but is also the major component
in normal tissue dosimetry within the peritoneum. The solution activity as a function of time may be quantitated by
sampling the peritoneal fluid periodically, or the dose component may be measured directly through the insertion of
TLDs. However, certain caveats must be considered in the
interpretation of TLD measurements. The use of CT to
define the patient specific geometry in relation to the TLD
catheter may be useful in this interpretation of dose measurements.
A second important parameter is the dose from activity
associated with tumor. At present, this quantity is often
estimated by measuring the activity per gram of tumor at a
given time, and assuming the activity is due to the physical
decay of isotope from t=O. This tumor dose calculation
will provide an overestimate because of the assumption of
instantaneous uptake. Biodistribution data, such as the tumor activity as a function of mass and time, may be obtained from animal studies. However, this dose calculation
is ultimately limited by the assumption of uniform activity
throughout the tumor. Nevertheless, this measurement
provides a relative measurement of dose and may be useful
in assessing if the tumor dose is within the therapeutic
range.
The above recommendations represent minimum dosimetric requirements. However, the role of dosimetry in
IPRIT is ultimately (1) to aid in the rational interpretation of the therapeutic response (i.e., why one patient responds favorably and another does not for the same injected activity) and (2) to suggest methods for
optimization. This type of detailed analysis will require the
more advanced dose calculation tools developed for external beam radiation therapy such as 3-D dose calculations
and dose volume histograms. Using dose point kernels,
three-dimensional dose distribution may be calculated for
any specified tumor geometry and source configuration.
The methods of Fujimori et al. 39-41 may be applied to IP
therapy with proper modification to yield more accurate
activity gradients within tumor. These biological models
may also be used in conjunction with measured data, such
as the percent injected dose per gram of tumor, to provide
verification of the models. Dose verification on the multicellular scale may be performed through microthin
T L D s .51 Originally applied to quantify autoradiographs,
these TLD rods are sectioned to have dimensions of 20
×200×400 µm. The careful implantation of these TLD
catheters into areas of tumor and normal tissue may provide an in vivo verification of the dose as a function of
distance from the solution/tissue interface.
Methods of optimization required to make therapy
more effective may be elucidated from the depth dose
curves presented in Fig. 4. Therapy will be effective only if
a uniform dose can be delivered to the tumor. This uniformity will not result from the proper selection of radionuMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
599
clide energies, but will be brought about by uniform antibody permeation throughout the tumor. Biologists and
immunologists will need to develop antibodies which have
a high specificity, yet retain the ability to penetrate tumor.
Since this request may be unreasonable, novel approaches
to delivery will need to be developed. These methods include the use of dose fractionation and the use of antibody
“cocktails” in which a variety of antibodies and radionuclides are used to provide a more uniform dose. The challenge of dosimetry will be to develop methods to accurately
calculate and verify dose distributions for these complex
source configurations.
ACKNOWLEDGMENTS
John C. Roeske gratefully acknowledges the support of
UPSHS Grant T32 CA09649. George T. Y. Chen and
John C. Roeske wish to acknowledge the generosity of the
Rice Foundation, Chicago, IL and the Center for Radiation Therapy, Chicago, IL.
1
J. Malamitsi, D. Skarlos, S. Fotiou, P. Papakostas, G. Aravantinos, D.
Vassilarou, J. Taylor-Papadimitriou, K. Koutoulidis, G. Hooker, D.
Snook, and A. Epenetos, “Intracavity use of two tumor associated
monoclonal antibodies,” J. Nucl. Med. 29, 1910-1915 (1988).
2
G. Rowlinson, D. Snook, A. Busza, and A. Epenetos, “Antibodyguided localization of intraperitoneal tumors following intraperitoneal
or intravenous administration,” Cancer Res. 47, 6528-6531 (1987).
3
N. J. Finkler, M. G. Muto, A. I. Kassis, K. Weadock, S. S. Tumeh, V.
R. Zurawski, and R. C. Knapp, “Intraperitoneal radiolabeled OC 125
in patients with advanced ovarian cancer,” Gynecol. Oncol. 34, 339344 (1989).
4
J. F. Chatal, J. C. Saccavini, J. F. Gestin, P. Thedrez, C. Curtet, M.
Kremer, D. Gurreau, D. Nolibe, P. Fumoleau, and Y. Guillard, “Biodistribution of indium-111 labeled monoclonal antibody after intraperitoneal injection in nude mice intraperitoneally grafted with ovarian
carcinoma,” Cancer Res. 49, 3081-3086 (1989).
5
A. A. Epenetos, G. Hooker, T. Krausz, D. Snook, W. Bodmer, and J.
Taylor-Papadimitriou, “Antibody-guided irradiation of malignant ascites in ovarian cancer: A new therapeutic method possessing specificity
against cancer cells,” Obst. Gynecol. (supplement) 68, 71S-74S
(1986).
6
H. Haisma, K. Moseley, A. Battaile, T. C. Griffiths, and R. C. Knapp,
“Distribution and pharmacokinetics of radiolabeled monoclonal antibody OC 125 after intravenous and intraperitoneal administration in
gynecologic tumors,” Am. J. Obstet. Gyncol. 159, 4218-4224 ( 1987).
7
D. Colcher, J. Esteban, J. A. Carrasquillo, P. Sugarbaker, J. C. Reynolds, G. Bryant, S. M. Larson, and J. Schlom, “Complementation of
intracavitary and intravenous administration of a monoclonal antibody
(B72.3) in patients with carcinoma,” Cancer Res. 47, 4218-4224
(1987).
8
J. S. Stewart, V. Hird, D. Snook, M. Sullivan, G. F. Hooker, N.
Courtenay-Luck, G. Sivolapenko, M. Griffiths, M. J. Myers, H. E.
Lambert, A. J. Munro, and A. A. Epenetos, “Intraperitoneal radioimmunotherapy for ovarian cancer: Pharmacokinetics, toxicity, and efficacy of I-131 labeled monoclonal antibodies,” Int. J. Radiat. Oncol.
Biol. Phys. 16, 405-413 (1989).
9
A. A. Epenetos, A. J. Munro, S. Stewart, R. Rampling, H. E. Lambert,
C. G. McKenzie, P. Soutter, A. Rahemtulla, G. Hooker, G. B. Sivolapenko, D. Snook, N. Courtenay-Luck, B. Dhokia, T. Krausz, J.
Taylor-Papadimitriou, H. Durbin, and W. F. Bodmer, “Antibodyguided irradiation of advanced ovarian cancer with intraperitoneally
administered radiolabeled monoclonal antibodies,” J. Clin. Oncol. 5,
1890-1899 (1987).
10
D. J. Hnatowich, M. Chinol, D. A. Siebecker, M. Gionet, P. W.
Doherty, R. Hunter, and K. Kase, “Patient biodistribution of intraperitoneally administered yttrium-w-labeled antibody,” J. Nucl. Med. 29,
1428-1434 (1988).
11
J. Stewart, V. Hird, D. Snook, M. Sullivan, M. J. Myers, and A. A.
Epenetos, “Intraperitoneal I-131 and Y-90 labelled monoclonal anti-
600
600
Roeske et al.: Dosimetry of radiolabeled antibodies
bodies for ovarian cancer: Pharmacokinetics and normal tissue dosimetry,” Int. J. Radiat. Oncol. Biol. Phys. 16, 405-413 (1989).
12
B. G. Ward, S. J. Mather. J. H. Shepherd, K. E. Britton, M. Granowska, and M L. Slevin, “Response to prospects for antibodytargeted radiotherapy of cancer,” Lancet 2, 580-581 (1986).
13
D. Colcher, J. Esteban, J. A. Carrasquillo. P. Sugarbaker, J. C. Reynolds, G. Bryant, S. M. Larson, and J. Schlom, “Comparison of route
of administration of radiolabeled monoclonal antibodies in patients
with colorectal cancer,” J. Nucl. Med. 27(6), 902 (1986).
14
P. Riva, S. Lazzari, M. Agostini, G. Sarti, G. Mosentelli, A. Pagenelli,
L. Rasciti, and A. Siccardi, “The intraperitoneal administration of radiolabelled monoclonal antibodies for the diagnosis and therapy of colon cancer,” J. Nucl. Med. 29(5), 762 (1988) (Abstract).
15
L. S. Lashford, A. G. Davies, R. B. Richardson, S. P. Bourne, J. A.
Bullimore, H. Eckert, J. T. Kemstead, and H. B. Coakham, “A pilot
study of I-131 monoclonal antibodies in the therapy of leptomeningeal
tumours,” Cancer 58, 573-583 (1986).
16
W. T. Miller and A. Barrett, “Dosimetric model for antibody targeted
radionuclide therapy and tumor cells in cerebrospinal fluid,” Cancer
Res. (Supplement) 50, 1043S-1048S (1990).
17
D. Pectasides, S. Stewart, N. Courtenay-Luck, R. Rampling, A. J.
Munro, T. Krausz, B. Dhokia, D. Snook, G. Hooker, H. Durbin, J.
Taylor-Papadimitriou, W. F. Bodmer, and A. A. Epenetos, “Antibodyguided irradiation of malignant pleural and pericardial effusions,” Br.
J. Cancer 5, 727-732 (1986).
18
N. Courtenay-Luck, A. A. Epenetos, K. E. Halnan, G. Hooker, J. M.
B. Hughes, T. Krausz, J. Lambert, J. P. Lavender, W. G. MacGregor,
C. J. McKenzie, A. Munro, M. J. Myers, J. S. Orr, E. E. Pearse, D.
Snook, B. Webb, J. Burchell, H. Durbin, J. Kemstead, and J. TaylorPapadimitriou, “Antibody-guided irradiation of malignant lesions:
Three cases illustrating a new method of treatment,” The Lancet 1,
1441-1443 (1984).
19
P. Riva, A. Arista, G. Mariani, E. Seccamani, S. Lazzari, G. Moscatelli, C. Sturiale, G. Sarti, G. Franceschi, A. Spinelli, G. Vecchietti, N.
Riva, P. Natali, and L. Zardi, “Improved tumour targeting by direct
intralesional injection of radiolabeled monoclonal antibody: A phase I
study in brain glioma,” J. Nucl. Med. 32, 922 (1991).
20
R. F. Ozols and R. C. Young, “Ovarian cancer,” Cur. Prob. Cancer 11,
37-122 (1987).
21
Z. Fuks, J. Yahalom, and H. Brenner, The Treatment of Carcinoma of
the Ovary in a Radiation Therapy of Gynecologic Cancers (Alan R. Liss,
New York, 1987).
22
J. Horyon and T. Caputo, Gynecologic Cancer in Clinical Oncology (W.
B. Saunders, New York, 1977).
23
G. A. Andrews, S. Root, H. D. Kerman, and R. R. Bigelow, “Intracavitary colloidal radiogold in the treatment of effusion caused by malignant neoplasm,” Ann. Surg. 137, 375-381 (1953).
24
E. Boye, M. W. Lindegoard, E. Paus, A. Skretting, M. Davy, and E.
Jacobsen, “Whole-body distribution of radioactivity after intraperitoneal administration of P-32 colloids,” Br. J. Radiol. 57, 395-402
(1984).
25
J. L. Currie, F. Bagne, C. Harris, D. L. Sullivan, E. A. Suruit, R. H.
Wilkinson, and W. T. Creasman, “Radioactive chromic phosphate suspension: Studies on distribution, dose absorption and effective therapeutic radiation in phantoms, dogs and patients,” Gynecol. Oncol. 12,
193-218 (1981).
26
R. J. Ott, M. A. Flower, A. Jones, and V. R. McCready, “The application of SPET to determine the radiation dose from P-32-chromic
phosphate therapy of the peritoneal cavity,” Euro. J. Nucl. Med. 11,
305-308 (1985).
27
B. Rippe and G. Stelin, “Simulations of peritoneal solute transport
during CAPD. Application of the two-pore formalism,” Kidney Int.
35, 1234-1244 (1989).
28
M. F. Flessner, R. L. Dedrick, and J. S. Schultz, “Exchange of macromolecules between peritoneal cavity and plasma,” Am. J. Physiol.
248, H15-H25 (1985).
29
M. F. Flessner, J. D. Fenstermacher, R. G. Blasberg, and R. L. Dedrick, “Peritoneal absorption of macromolecules studied by quantitative autoradiography,” Am. J. Physiol. 248, H26-H32 (1985).
30
J. F. Chatal, J. C. Saccavini, J. F. Gestin, P. Thedrez, C. Curtet, M.
Kremer, D. Guerrcau, D. Nobile, P. Fumoleau, and Y. Guillard, “Biodistribution of indium-111-labeled OC 125 monoclonal antibody intraperitoneally injected into patients operated on for ovarian carcinomas,” Cancer Res. 49, 3087-3094 (1989).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
31
P. Thedrez J. C Saccavini. D. Nolibe. J. P. Simoen, D. Guerreau, I. F.
Gestin, C. Curtet, M. Kremer, and J. F. Chatal, “Biodistribution of
indium-111-labeled OC 125 monoclonal antibody after intraperitoneal
injection in nude mice intraperitoneally grafted with ovarian carcinomas,” Cancer Res. 49, 3081-3086 (1989).
32
J. Rotmensch, J. Roeske, G. Chen, C. Pelizzati, A. Montag, R.
Weichselbaum, and A. L. Herbst, “Estimates of dose to intraperitoneal
micrometastases from alpha and beta emitter in radioimmunotherapy,”
Gynecol. Oncol. 38, 478-485 (1990).
33
L. M. Cobb, “Intratumor factors influencing the access of antibody to
tumour cells,” Cancer Immunol. Immunother. 28, 235-240 (1989).
34
R. K. Jain “Physiological barriers to delivery of monoclonal antibodies
and other macromolecules in tumors,” Cancer Res. (Supplement) 50,
814S-819S (1990).
35
L Dedrick and M. F. Flessner, “Pharmacokinetic considerations on
monoclonal antibodies,” Immunity Cancer 2, 429-438 ( 1989).
36
C. A. Sutherland, J. O. Davis, G. M. Stirrat, F. Buchegger, M.
Schreyer, A. Vacca, and J. P. Mach, “Penetration and binding of radiolabeled anti-carcinoembryonic antigen monoclonal antibodies and
their antigen binding fragments in human colon multicellular spheroids,” Cancer Res. 47, 1627-1633 (1987).
37
G. D. Thomas, M. J. Chappell, P. W. Dykes, D. B. Ramsden, K. R.
Godfrey, J. R. M. Ellis, and A. R. Bradwell, “Effect of dose, molecular
size, affinity, and protein binding on tumor uptake of antibody or
ligand: A biomathematical model,” Cancer. Res. 49, 3290-3296
(1989).
38
L. E. Williams, R. B. Duda, R. T. Proffitt, B. G. Beatty, J. D. Beatty,
J. Y. C. Wong, J. E. Shively, and R. Paxton, “Tumor uptake as a model
of tumor mass: A mathematical model,” J. Nucl. Med. 29, 103-109
(1988).
39
K. Fujimori, D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “Modeling analysis of the global and microscopic distribution of Immunoglobulin G, F(ab’)2 and Fab in tumors,” Cancer Res. 49, 5656-5663
(1989).
40
K. Fujimori, D. G. Covell, J. E. Fletcher, and J. N. Weinstein, “A
modeling analysis of monoclonal antibody percolation through tumors:
a binding site barrier,” J. Nucl. Med. 31, 1191-1198 (1990).
41
K. Fujimori, D. Fisher, and J. N. Weinstein, “Integrated microscopicmacroscopic pharmacology of monoclonal antibody radioimmunoconjugates: The radiation dose distribution,” Cancer Res. 51, 4821-4827
(1991).
42
L. T. Baxter and R. K. Jain, “Transport of fluid molecules in tumors:
I. Role of interstitial pressure and convection,” Microvasc. Res. 48,
77-109 (1989).
43
M. J. Myers, A. A. Epenetos, and G. Hooker, “Practical assessment of
radiation doses using labelled antibodies for therapy,” Nucl. Med. Biol.
13(4), 437-446 (1986).
44
M. J. Myers, G. R. Hooker, and A. A. Epenetos, “Dosimetry of radiolabeled monoclonal antibodies used for therapy,” in Proceedings of the
Fourth International Radiopharmaceutical Dosimetry Symposium (Oak
Ridge, TN, Conf-851113, 1985).
45
M. Bardies, J. Lame, M. J. Myers, and J. P. Simoen, “A simplified
approach to beta dosimetry for small spheres labelled on the surface,”
Phys. Med. Biol. 35, 1039-1050 (1990).
46
M. Bardies and M. J. Myers, “A simplified approach to alpha dosimetry for small spheres labelled on the surface,” Phys. Med. Biol.
35(11), 1551-1561 (1990).
47
E. E Watson, M. G. Stabin, J. L. Davis and K. F. Eckerman, “A
model of the peritoneal cavity for use in internal dosimetry,” J. Nucl.
Med. 30, 2002-2011 (1989).
48
J. C. Roeske, G. T. Y. Chen, R. W. Atcher, C. A. Pelizzari, J. Rotmensch, D. Haraf, A. Montag, and R. R. Weichselbaum, “Modeling of
dose to tumor and normal tissue from intraperitoneal radioimmunotherapy with alpha and beta emitters,” Int. J. Radiat. Oncol. Biol.
Phys. 19(6), 1539-1548 (1990).
49
R Loevinger, E. Japha, and G. Brownell, Radiation Dosimetry (Academic, New York, 1958).
50
M. Berger, “Distribution of absorbed dose around point sources of
electrons and beta particles in water and other media,” MIRD Pamphlet No. 7, J. Nucl. Med. (Supplement 5) (1971).
“M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
Radiobiology of radiolabeled antibody therapy as applied
to tumor dosimetry
V. K. Langmuir a)
Life Sciences Division, SRI International, 333 Ravenswood Avenue. Menlo Park, California 94025
J. F. Fowler
Departments of Human Oncology and Medical Physics, University of Wisconsin Clinical Cancer Center,
600 Highland Avenue, Madison, Wisconsin 53792
S. J. Knox
Department of Radiation Therapy, Stanford University Hospital, Stanford, California 94305
B. W. Wessels
Division of Radiation Oncology and Biophysics, George Washington University Medical Center,
901 23rd Street, N. W. Washington, DC 20037
R. M. Sutherland
Life Sciences Division, SRI International, 333 Ravenswood Avenue, Menlo Park, California 94025
J. Y. C. Wong
Division of Radiation Oncologv. City of Hope National Medical Center, 1500 East Duarte Road, Duarte,
California 91010
(Received 18 March 1992; accepted for publication 24 July 1992)
This paper reviews the radiobiological aspects of radioimmunotherapy (RIT) with radiolabeled
antibodies, including comparisons between RIT and external beam irradiation. The effectiveness
of cell killing by radiation decreases with the dose rate and the rate of decrease is determined by
the size of the shoulder on the radiation survival curve. Tumors with poor repair capabilities
exhibit less of a dose rate effect than tumors with good repair capabilities. Continued tumor cell
proliferation during treatment occurs at very low dose rates and can contribute to the reduced
effectiveness of low dose rate radiation. Toxicity to normal tissues will determine the total dose
of radiolabeled antibody that can be given and this will be influenced by the choice of both the
radionuclide and the antibody. The reported enhanced effectiveness of RIT may be due to
multiple factors including selective targeting of cells responsible for tumor volume doubling,
tumor surface binding rather than homogeneous binding throughout the tumor volume, targeting of the tumor vasculature, or block of cell cycle progression in G 2. During RIT, there is less
time for reoxygenation of hypoxic tumor cells than during a course of conventional external
beam radiotherapy. It has not yet been determined whether this will have a detrimental effect on
RIT. Probably the most important factor in the success of RIT is dose heterogeneity. Any viable
portion of a tumor that is not targeted and does not receive a significant radiation dose will
potentially lead to treatment failure, no matter how high the dose received by the remainder of
the tumor. Comparisons between RIT and external beam radiation have shown a wide range of
relative efficacy. Tumors most likely to respond to RIT are tumors with poor repair capabilities,
tumors that are susceptible to blockage in radiosensitive phases of the cell cycle, tumors that
reoxygenate rapidly, and tumors that express the relevant antigen homogeneously. From a
radiobiological perspective, it appears that RIT alone is unlikely to cure many tumors and that
combination with other treatment modalities will be essential.
I. INTRODUCTION
Most of the predictions of the radiobiological aspects of
radiolabeled antibody therapy are based on studies of continuous low dose rate (LDR) or fractionated irradiation
given by external beam. A majority of these studies were
done at dose rates that are higher than the dose rates
achieved during radioimmunotherapy (RIT) and the dose
rates were constant rather than exponentially decreasing,
as is the case in RIT. This section will discuss what is
known about the radiobiology of LDR irradiation and RIT
as applied to tumor dosimetry and discuss comparisons
between the two. Normal tissue radiobiology, although
601
Med. Phys. 20 (2), Pt. 2, Mar/Apr 1993
very important, will only be peripherally addressed here
for continuity. More complete discussions can be found in
Refs. 1-5.
II. REPAIR OF RADIATION DAMAGE
In general, the effectiveness of cell killing by radiation
decreases with decreasing dose rate 6 (see Fig. 1). In vitro,
the dose rate effect appears to correlate best with the initial
portion of the acute radiation survival curve (single fraction high dose rate). As the initial slope decreases, or as
the shoulder widens, the dose rate effect increases. From
the linear-quadratic model, this would imply that as single-
0094-2405/93/020601-10$01.20
© 1993 Am. Assoc. Phys. Med.
601
602
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
FIG. 1. As dose rate decreases, the cell survival curves become less steep
and straighter: more time is available for repair of sublethal damage as the
duration of exposure exceeds the half-time of repair. Ultimately, at very
low dose rates, cell survival tends toward the (irreparable) initial slope of
the high-dose-rate survival curve. Reprinted with Permission from International Journal of Radiation, Oncology, Biology, and Physics, J. A. Stitt
et al. High Dose Rate Brachytherapy for Carcinoma of the Cervix: The
Madison System I. Clinical and Radiobiological Considerations, copyright (1992), Pergamon Press plc.
hit killing becomes more dominant (and two-hit or potentially reparable killing becomes less so) the dose rate effect
decreases. As a result, cell lines which have a small shoulder such as lymphomas show a much smaller dose rate
effect than lines with a large shoulder.6,7 Thus it should be
possible to predict which tumors are most likely to respond
to radiolabeled antibody therapy. Tumors with a large
shoulder on the radiation survival curve would be predicted to be less responsive than those with small shoulders.
In vitro studies confirm these predictions. 8 Figure 2
shows dose survival curves for two cell lines with different
radiosensitivities and SLD (sublethal damage) repair ca-
F I G. 2. Survival curves for two human colon adenocarcinoma cell lines
possessing different radiosensitivities and SLD repair capacities. Cell lines
were exposed to either high dose-rate 60cobalt external beam irradiation
or exponentially decreasing low dose-rate 90Y irradiation. WiDr was more
radioresistant (α/β =8) compared to LS174T (α/β =25). For a survival
fraction of 0.1, 90Y low dose-rate irradiation was less effective than external beam irradiation by a factor of 2.4 for LS174T and by 3.2 for WiDr
[factor= (Dose 90Y)/(Dose external beam)]. Reprinted with permission
from International Journal of Radiation, Oncology, Biology, and Physics
Volume 20, Wong et al., Radiobiologic Studies Comparing Yttrium-96
Irradiation and External Beam Irradiation in Vitro, copyright (1991),
Pergamon Press, plc.
Medical Physics, Vol. 24 No. 2, Pt. 2, Mar/Apr 1993
602
pabilities exposed to either high dose-rate external beam
irradiation or yttrium exponentially decreasing low dose
rate irradiation (initial dose rates 2.25 to 29 cGy/h). Both
cell lines were more resistant to low dose-rate irradiation.
In addition, the more radioresistant cell line (WiDr) with
a large shoulder demonstrated more of a dose rate effect
and less responsiveness to 9 9Y irradiation than the more
sensitive LS174T cell line. These data indicate that tumors
which are most sensitive to conventional external beam
irradiation would also be most sensitive to RIT.
Several survival curve parameters have been shown to
correlate with clinical radioresponsiveness of tumors to
conventional radiotherapy. 9,10 It is likely that indicators of
shoulder size such as survival at 2 Gy or the initial slope
may predict responsiveness to RIT. From this it would be
predicted that lymphomas should be the most responsive,
followed by small cell lung cancer, adenocarcinomas and
squamous cell carcinomas, and melanomas, gliomas and
sarcomas. It must be remembered that these are average
sensitivities for large numbers of tumors and any one tumor may be more or less radioresponsive than the average
for its category. Individual testing of radiosensitivity may
be useful in patient selection, when more reliable tests are
developed.
III. COMPARISONS OF ALPHA AND BETA
EMITTERS
The repair capacity increases as dose rate decreases but
there is a dose rate beyond which there is no further improvement in survival, presumably because some component of the damage is irreparable. 11,12 If high linear energy
transfer (LET) radiation is used, where most radiation
damage is due to direct effects, there is much less capacity
to repair and there is little if any dose rate effect. This gives
an apparent advantage of alpha emitters over beta emitters
in RIT of tumors if an even distribution of radionuclide
can be attained.13 Because of the short range of alphaparticles, toxicity to normal tissues within and adjacent to
the tumor would be less than with beta-particles although
this is unlikely to be an important problem in either case.
Toxicity to normal tissues receiving a dose of radiation,
because of nonspecific uptake or as an “innocent bystander” such as the bone marrow, would depend on the
radiation sensitivity of the normal tissue relative to the
tumor and to the dose absorbed by the normal tissue relative to the tumor.
Consider the examples in Fig. 3. Figure 3 (a) represents
a tumor that is more resistant than a normal tissue. Representative survival curves are shown. The absolute values
of dose and survival are unimportant for this discussion. If
a surviving fraction of 0.01 in the tumor is chosen, the
surviving fraction for normal tissue is taken from the graph
assuming either that the normal tissue dose (D n t) equals
the tumor dose (D t) or that D nt is one fifth D t. Figure 3 (b)
and (c) show calculations for the circumstances where the
normal tissue (nt) is less sensitive than the tumor and
where it is of equivalent radiosensitivity. It can be seen
that, for bone marrow or other tissues more sensitive than
tumor, alpha-particles will actually have less effect on that
603
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
603
F I G. 3. Plots of surviving fraction vs. dose for the following situations:
(a) Normal tissue (dashed line) more radiosensitive than tumor (solid
line); (b) Normal tissue and tumor of equivalent radiosensitivity; (c)
Normal tissue less radiosensitive than tumor. The upper panels are for
alpha-emitter-labeled antibody, the lower panels beta-emitter-labeled antibody. The surviving fraction for tumor is 0.01 in every plot. Point A is
the surviving fraction for normal tissue if the normal tissue and the tumor
received equal absorbed doses. Point B is the surviving fraction for normal
tissue if it received one-fifth the tumor dose.
Medical Physics, Vol. 20, No. 2, Pt. 2. Mar/Apr 1993
604
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
normal tissue than beta-particles for an equivalent tumor
surviving fraction. This advantage for alpha-particles is reduced as the ratio of tumor dose to normal tissue dose
( Dt/ Dnt) increases. For normal tissues less radiosensitive
than tumor (or with a lower α/β ratio from the linear
quadratic cell survival model), there is an advantage for
beta particles but this advantage also decreases as D t/ Dnt
increases. For tumor and normal tissue of equivalent radiosensitivity, there is no advantage of either form of therapy
if the doses are equal but there is some improved sparing of
normal tissues by beta-emitters as D t/ Dnt increases. Assuming that D t/ Dnt is always greater than unity, normal
tissues will always have better survival than tumor if they
are less radiosensitive (lower α/β ratio) than tumor and
even normal tissues that are more sensitive may have better
survival if D t/ Dnt is high enough.
It appears that, under the usual circumstances of RIT
where D t/ Dnt is greater than unity, beta-emitters will generally spare normal tissues better than alpha-emitters.
However, at least on theoretical grounds, the use of
a-emitters for RIT should not result in enhanced bone
marrow toxicity relative to P-emitters. More radioresistant
normal tissues are at a disadvantage with a-emitters, but
this may be offset by the short treatment time for RIT,
before proliferation of late-responding tissues begins. 14 The
main constraint with a-emitters is adequate tumor localization prior to physical decay of the radionuclide. This
problem could perhaps be alleviated by the improvement of
antibody labeling methods for more long-lived alphaemitters or by pretargeting with bifunctional antibody. 1 5
IV. DOSE RATE COMPARISONS
A useful way to express dose rate effects is by the relative effectiveness (RE) which is the ratio of log kill at a
specified dose rate to that at an extremely low dose
rate.1,2,16 Figure 4 shows the decrease in effectiveness as
dose rate decreases, calculated for a total dose of 1000 cGy.
The series of curves illustrates how the critical dose rateswhere the change is steepest-depend inversely on the halftime of repair. It also illustrates how the magnitude of the
change in RE depends on the shape of the intrinsic cell
survival curve as defined by the ratio α/β. In general tumor cells tend to have high α/β ratios but there are exceptions. There is some evidence that repair half-times are
decreased during continuous LDR irradiation 16-18 possibly
because of lack of saturation of repair mechanisms.
For RIT applications, only the left-hand part of Fig. 4 is
relevant, at dose rates below 20-30 cGy/h where the RE is
approaching its lowest value of 1.0. At RE=1.0, the rate of
log cell kill per Gy is the same as along the initial slope of
the standard single-dose (high dose rate) cell survival
curve. Traditional brachytherapy at 40-60 cGy/h and conventional radiotherapy using fractions of 200 cGy utilize a
large proportion of the repair capacity already, so their RE
values are as low as about 1.2. (This factor does depend on
assuming the linear quadratic model, with α/β = 10 Gy for
tumors and monoexponential repair of T l/2= 1.5 h.) So
RIT is not more than 20% less efficient than conventional
radiotherapy (provided that all cells receive the stated
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
604
F I G. 4. The relative effectiveness (RE) calculated for cells with three
shapes of high dose-rate cell survival curve (α/β =5, 10 and 20 Gy) and
six different half-times of repair. The log, cell kill is obtained by multiplying the total dose (in Gy) by the RE and dividing by the initial slope
(a). The effectiveness of an irradiation is therefore proportional to RE.
Reprinted with permission from International Journal of Radiation, Oncology, Biology, and Physics Volume 18, J. F. Fowler, Radiobiological
Aspects of Low Dose Rates in Radioimmunotherapy, copyright (1990),
Pergamon Press, plc.
dose). If a tumor required 7000 cGy to sterilize it using
conventional fractionated external beam therapy, it could
be sterilized with 8400 cGy (1.2X7000) at very low dose
rates. The conclusion remains broadly true over a range of
reasonable values of the parameters. There is little evidence
of departures from this principle.
IV. CELL CYCLE REDISTRIBUTION
Redistribution within the cell cycle can influence the
effect of radiation. It has been suggested that at certain
dose rates, G2 block can be induced leading to an accumulation of cells in this phase of the cell cycle resulting in
greater radiation-induced cell killing, the so-called inverse
dose rate effect.1 9 - 2 1 It is illustrated schematically by the
dotted lines in Fig. 5. It is thought to be due to the delay of
mitosis by irradiation, so that cells accumulate in the G 2
phase, which is generally more radiosensitive than the average over the whole cycle. When it occurs, it could increase the RE by 20% or 30% so that a better effect is
obtained than would be predicted given the total dose. G 2
block has been seen in some cell lines but not in others, and
over limited ranges of dose rate. It should also be noted
that not all tumors are more radiosensitive in this phase of
the cell cycle. It has also been reported that this block can
be produced by exponentially decreasing dose rate
irradiation. 22 If predictable cell cycle redistributions do occur during RIT, a second dose of RIT or some chemotherapeutic agent may be timed to coincide with when most
tumor cells are in a particular sensitive phase of the cell
cycle. However, this effect may be difficult to predict espe-
605
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
F I G. 5. The full lines are the curves for T1/2= 1.5 h reproduced from
Fig.4 from each of the three panels. The dotted lines show schematically
the possible increase of RE at dose rates around the critical levels where
progression through the cell cycle can occur but cell division is delayed.
Reprinted with permission from International Journal of Radiation, Oncology, Biology, and Physics Volume 18, J. F. Fowler, Radiobiological
Aspects of Low Dose Rates in Radioimmunotherapy, copyright (1990),
Pergamon Press, plc.
cially in heterogeneous populations such as tumors of more
than a few millimeters in diameter, which often have large
numbers of noncycling cells.
V. TUMOR CELL PROLIFERATION
At very low dose rates, cell division can continue leading to repopulation of the tumor during treatment. 23 Even
if the rate of cell death is greater than the rate of cell birth,
this would still lead to a reduction in the cell killing effect
of a given total dose.24 However, in RIT the distribution of
radiolabeled antibody is often heterogeneous and this may
result in “overkill” of some cells and very low dose rates
(and total doses) to other cells leading to continued cell
division or recruitment of noncycling cells into the cell
cycle resulting in treatment failure. 13 The contribution to
the dose rate effect by cell proliferation may be less in vivo
than is predicted by in vitro studies because a smaller proportion of cells may be cycling. The tumor size also contributes to the absorbed dose distribution heterogeneity.
With decreasing tumor size below the radionuclide range,
there is less benefit from cross-fire and an increasing percentage of the absorbed dose is lost outside of the tumor.
This effect may be counteracted by using radionuclides
with a shorter range. There is also evidence that smaller
tumors show increased uptake and less heterogeneity of
antibody deposition.*’
605
toward rapid reoxygenation even during continuous
irradiation. 28 The oxygen enhancement ratio (OER) has
been shown to be reduced at low dose rates and with
fractionation. 29-33 This might mean that hypoxic cells may
not be radiobiologically as much of a problem as during
high dose rate irradiation. However, the cells most likely to
be hypoxic are also the cells most likely to receive a low
radiation dose from RIT because of their location at a
distance from blood vessels and the slow diffusion of antibody molecules. Therefore hypoxic cell sensitizers may
have a role in RIT. Radiosensitization by hypoxic cell sensitizers such as the nitroimidazoles has been demonstrated
at conventional brachytherapy dose rates with enhancement ratios of 1.06-2.7 34-36 and one study has been published demonstrating prolonged growth inhibition in a human colon cancer xenograft when misonidazole was added
to RIT.3 7
VI. RADIOSENSITIZATION BY HALOGENATED
PYRIMIDINES
Radiosensitization by halogenated pyrimidines is a contrasting type of radiosensitization that could be particularly effective at low dose rates because it works by steepening the slope of survival curves. Significant steepening is
observed for modest proportions of thymidine replacement
in DNA. Dose enhancement ratios of 1.5 were found for
5% and 13% replacement of thymidine in two different
cell lines derived from human colon cancer (E. L. Miller,
personal communication).38 The steepening of initial slope
is particularly important at low dose rates, because cell
survival is then very close to the initial slope itself. Recently published results at dose rates between 17 and 73
cGy/h showed enhancement ratios exceeding 2 for three
energies of gamma rays irradiating Chinese hamster lung
cell lines exposed to 10 - 5µ M o f i o d o d e o x y u r i d i n e
(IUdR). 39 Approximately the same enhancement would
be expected for beta particle irradiation.
Further, and even more relevant, IUdR has been reported to enhance the effectiveness of RIT using 131 I conjugated to a monoclonal antibody against human milk fat
globule, MC5, in nude mice transplanted with a human
mammary tumor, MX-1. Inhibitors of thymidine biosynthesis were also administered. The biological endpoint was
tumor regrowth delay and the result was highly statistically significant.4 0 However, other investigators using a human colon cancer xenograft and 131I-anticarcinoembryonic
antigen showed reduced effectiveness when IUdR was
used.3 7
V. HYPOXIA AND REOXYGENATION
It is generally held that reoxygenation of hypoxic cells
between treatment fractions is one of the factors that leads
to the success of conventional fractionated radiotherapy
given over several weeks. 26 Because RIT is continuous and
complete within approximately 2 weeks, it may be that
there is incomplete reoxygenation of initially hypoxic cells
during RIT leading to an increased likelihood of treatment
failure.27 However, LDR brachytherapy given continuously over 3-7 days has been very successful which points
Medical Physics, Vol. 20, No. 2. Pt 2, Mar/Apr 1993
V. THE EFFECT OF DOSE HETEROGENEITY
Most in vivo studies have calculated tumor doses with
the assumption that the radionuclide is evenly distributed
in the tumor. Both direct measurements with TLDs 41 a n d
theoretical dose calculations taking into account the heterogeneity (determined by autoradiography) 4 1 - 4 4 h a v e
shown that this is inaccurate. Therefore the dose to some
areas of tumor is being underestimated and to others it is
being overestimated. Assuming that the viable cells are
606
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
most likely to be targeted by RIT because of their proximity to blood vessels, the dose to these cells is most likely
being underestimated. However many viable cells may not
be targeted at all.
If half of the cells in a tumor (or metastatic cluster)
receive no dose, they will survive and the radiobiological
effect is approximately the same as if only one single fraction of 200 cGy has been given. This is because each fraction of 200 cGy sterilizes about half the cells present. This
is true no matter how great the dose delivered to those cells
which do receive dose. If one quarter of the cells receive no
dose, the effect is the same as two fractions of 200 cGy and
so on. Any region of viable tumor cells that receives no
dose will potentially contain enough cells (one or more) to
regrow the tumor. The question of dose heterogeneity is
therefore vitally important. Groups of cells which receive
rather low doses are also dangerous if the cells remain
clonogenic.
To overcome the problem of dose heterogeneity in RIT,
additional effective treatment is necessary, possibly by using external beam radiotherapy. 2,45 If, for example, 90% of
the cells in a tumor containing 10 10 cells received an effective dose from RIT but 10% of the cells received no dose,
only one out of the ten logs of cells could have been eliminated by RIT (assuming at least 8400 cGy to that 90%).
We would then need to add 90% of a full dose of external
beam radiotherapy in addition to RIT. If 99% of the tumor cells received a full dose, but 1% received no dose,
then two logs could have been eliminated by RIT (assuming 8400 cGy to them), leaving eight logs to kill. We would
then need to add 80% of a full dose of external beam
radiotherapy. 4 6 This picture emphasizes the real limitations of RIT. Dose heterogeneity is probably the largest
unknown variable in both clinical and experimental tumor
work with RIT. But it also demonstrates that effective RIT
can provide a useful boost dose. If it were possible to reduce external beam doses by only 10% or 20%, many of
the complications of radiotherapy could potentially be alleviated.
It is necessary to emphasize that even one log of cell kill
is likely to lead to massive tumor shrinkage; possibly to one
tenth of its original volume. Two logs of cell kill could
cause a tumor to disappear clinically (down to 1%), which
is complete remission clinically. But there would still be
eight logs of cells remaining to be dealt with or else the
tumor would inevitably recur.
It is also clear from the above discussion that the size of
tumor is important. The larger the tumor, the more logs of
cell kill that are required to control it. Micrometastases
may be well targeted by RIT using radionuclides of appropriate energy. Wheldon et al. 46 have made theoretical calculations of optimal tumor sizes for therapy with various
radionuclides and for 1 3 1I it is between 10 5 and 106 cells.
This represents a nodule of less than l-mm diameter. A
lower radiation dose would of course be required to sterilize a micrometastasis than a tumor containing 10 10 cells.
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
606
VI. EXPERIMENTAL BEAM VERSUS RIT STUDIES
A final question is whether the response to exponentially decreasing LDR irradiation is the same as the response to constant LDR. Very few studies have addressed
this question. Differences in response may be due to the
heterogeneous distribution of radionuclide in tumors with
RIT or to the nature of exponentially decreasing low dose
rate radiation itself. There is some evidence that, in some
animal models, exponentially decreasing low dose rate radiation may be at least as effective as fractionated
t h e r a p y . 4 , 4 7 - 5 1 This could be due to ( 1) the measured average dose being lower than the dose that the viable tumor
cells actually received, (2) a dose rate effect leading to
accumulation of cells in sensitive phases of the cell cycle,
(3) a geometric effect dependent on the location of the
radionuclide in the cell and the range of the radionuclide,
or (4) interference with the blood supply to the tumor due
to irradiation of the endothelium leading to a tumor bed
effect. 47 Several experiments have been performed using
different experimental models to study the radiobiology of
RIT, and to compare the relative efficacy of RIT with dose
equivalent external beam radiation. The results of these
studies will be briefly summarized and compared here, and
have been discussed in more detail in a recent review
paper.5 2
Recently, five studies [Refs. 47-50 and J. A. Williams
(personal communication)] have compared the efficacy of
RIT to high dose rate external beam irradiation. Although
these studies differed considerably in terms of the experimental model, design, and methodology employed, several
important comparisons can be made. Tables I and II summarize and compare these studies. The general features of
the tumors and radioimmunoconjugates are shown in Table I and the modes or irradiation and fractionation schedules are shown in Table II. In all studies, RIT was compared to external beam irradiation, given either as a single
fraction (SF) or in multiple fractions (MF). In all but one
study, RIT was compared to local irradiation of the tumor.
Knox et al.48 utilized whole body external beam irradiation
because of a relatively large contribution of whole body
irradiation to the overall effect of RIT in the murine B-cell
lymphoma model studied. There were also important differences in the methods that were used to analyze the tumor response data and these have been summarized in
detail in Table II.
In order to compare the results of the above studies, a
relative efficacy factor was calculated for each study which
represented the relative efficacy of RIT compared to external beam irradiation. Relative efficacy factors were calculated by using reported data for radiobiological endpoints
or parameters measured as well as dosimetric data. The
actual equations used for the different studies as well as the
calculated relative efficacy factors are shown in Table II.
As can be seen, the relative efficacy of RIT varied considerably from study to study. In a renal cell xenograft model,
equivalent doses of RIT were 2.5 times more effective than
MF external beam irradiation for the inhibition of tumor
growth, while less enhancement of efficacy was seen with
SF irradiation (relative efficacy factor 1.5-1.7). 47 Simi-
607
Langmuir et al: Radiobiology and radiolabeled antibody therapy
T ABLE I. Comparison of tumors and monoclonal
607
antibodies studied.
1
VDT=Volume doubling time.
Slow VDT > 4 days.
3
Moderate VDT=3-4 days.
4
Rapid VDT < 3 days.
5
SDT: Size (product of 2 tumor dimensions) doubling time.
2
larly, in the 38C13 murine B-cell lymphoma model, RIT
was 3.25 times more effective (p < 0.001) than dose equivalent MF250 kV X-irradiation, and was 1.99 times more
effective (p < 0.001) than continuous exponentially decreasing LDR external irradiation using a 1 3 7 Cs source
(same effective T1/2 as the radiolabeled MAb). 48 In contrast, relative efficacy factors of 0.33 and 0.32 have been
obtained for the high grade glioma U-251 and LS174T,
respectively (Williams et al., personal communication 4 9).
More recently, a relative efficacy factor of 1.0 was obtained
for LS174T (Buras et al., personal communication). Interestingly, a relative efficacy factor of 0.5 was obtained for
the more radioresistant colorectal cancer xenograft WiDr.
With increasing frequency the question is being raised
as to whether or not 1 cGy of RIT is equivalent to 1 cGy
external beam irradiation in overall effect. If the answer is
no, it is important to know what kind of correction or
calibration factor must be used in order to predict the relative efficacy and toxicity of RIT compared with conventionally fractionated external beam irradiation. The results
obtained thus far from the studies described above are heterogeneous and fail to answer these questions. Once again,
in attempting to compare these studies, it is important to
recognize the differences that exist between the experimental models, designs, and methodologies used to measure the
antitumor effects. It is also important to point out that
these studies differed in terms of the methods that were
used to measure and/or calculate tumor absorbed doses.
S o m e47,50 used TLDs and others calculated absorbed dose
using retention or biodistribution data and MIRD
formulas. 48,49 Both of these approaches have inherent limMedical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
itations such as sampling error with TLDs and the assumption of the MIRD method that there is an even distribution
of radionuclide in tumor.
In spite of these differences, several important patterns
are evident. There tended to be a significant dose rate effect
for those tumors with a large shoulder (small α/β ratio).
This effect was generally considerably less for tumors characterized by a small shoulder (large α/β ratio). It is likely
that, for some tumors, the observed dose rate effect may be
further modified by the tumor doubling time. These preliminary results and observations are therefore consistent
with Fowler’s predictions that the size of the survival curve
shoulder (α/β ratio) and tumor doubling time are important determinants of the magnitude of the dose rate effect. 2
It is possible that when this effect is minimal, other factors
such as redistribution of cells within the cell cycle with
arrest of cells in G 2 , reoxygenation, and/or selective targeting of tumor by antibody may explain in part the increased efficacy of RIT compared with external beam irradiation in some systems.47’ 48 Clearly these issues need to be
addressed by future studies in order to better delineate the
nature of the relationship between the above radiobiological parameters and possible dose rate effects. In addition,
future studies should be designed to elucidate the relationship between tumor control and selective targeting of tumors by radiolabeled antibodies, which results in significant dose heterogeneity. More tumor types, that vary in
terms of repair capacity and proliferative rate, must be
studied in order to determine whether or not the proposed
relationships between radiobiological characteristics and
dose rate effects is valid. In the future, experiments should
606
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
606
TABLE II. Comparison of external beam irradiation schemata and relative tumor responses observed following dose equivalent RIT and external beam
irradiation.
be designed in such a way that external beam fractionation
schedules are clinically relevant and the effect of only one
variable is studied at a time. More tumor control experiments are needed and the use of clonogenicity and DNA
damage assays may be helpful since these endpoints are
more meaningful in terms of the extent of cell killing than
growth delay assays. As discussed in the section entitled
“The Effect of Dose Heterogeneity,” elimination of only
two logs of tumor cells can lead to tumor disappearance,
and thus is not a sensitive measure of therapeutic efficacy.
some of these problems by modifying the repair mechanisms by repair inhibitors or hyperthermia 53 or by targeting the cells that are not well targeted with RIT with some
other modality such as hypoxic cell toxins or biological
response modifiers. By using RIT to provide a substantial
proportion of the treatment to a defined volume, a modest
reduction in external beam total dose could lead to significantly less complications.
ACKNOWLEDGMENTS
VI. SUMMARY
Based on the above observations, tumors most likely to
respond to RIT would be tumors that are inherently radiosensitive, tumors with a poor capacity to repair radiation
damage or long repair half-times, tumors that are susceptible to block in sensitive phases of the cell cycle, tumors
that reoxygenate rapidly, and tumors that express the relevant antigen homogeneously. Beta-emitters will generally
spare normal tissues more effectively than alpha emitters.
However, for tissues such as bone marrow, that are more
radiosensitive than the tumor, alpha-emitters may actually
produce better sparing. It may be possible to get around
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
We would like to acknowledge the careful review and
helpful comments made by Jerry Williams and Larry
Dillehay. This work is supported in part by Grant No.
CA52285 from the National Cancer Institute.
a)
To whom requests for reprints should be addressed.
1
T. E. Wheldon and J. A. O’Donoghue, “The radiobiology of targeted
radiotherapy,” Int. J. Radiat. Biol. 58, 1-21 (1990).
2
J. F. Fowler, “Radiobiological aspects of low dose rates in radioimmunotherapy,” Int. J. Radiat. Oncol. Biol. Phys. 18, 1261-1269 (1990).
3
V. K. Langmuir, and R. M. Sutherland, “Radiobiology of radioimmunotherapy,” Antibody, Immunconj., Radiopharm. 1, 195-211 (1988).
4
V. K. Langmuir, and R. M. Sutherland, “The radiobiology of continuous low dose rate radiation,” in Proceedings of the 1988 ACNP/SNM
609
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
Joint Symposium on the Biology of Radionuclide Therapy (American
College of Nuclear Physicians, Washington, DC, 1989), pp. 270-284.
5
S. J. Adelstein and A. I. Kassis, “Radiobiologic implications of the
microscopic distribution of energy from radionuclides,” Int. J. Radiat.
Applic. Instrum. Part B: Nucl. Med. Biol. 14, 165-169 (1987).
6
J. B. Mitcheli, J. S. Bedford, and S. M. Bailey, “Dose-rate effects in
mammalian cells in culture III. Comparison of cell killing and cell
proliferation during continuous irradiation for six different cell lines,”
Radiat. Res. 79, 537-551 (1979).
7
G. G. Steel, J. M. Deacon, G. M. Duchesne, A. Horwich, L. R.
Kelland, and J. H. Peacock, “The dose-rate effect in human tumour
cells,” Radiother. Oncol. 9, 299-310 (1987).
8
J. Y. C. Wang, L. E. Williams, A. J. Demidecki, B. W. Wessels, and X.
W. Yan, “Radiobiologic studies comparing yttrium-90 irradiation and
external beam irradiation in vitro,” Int. J. Radiat. Oncol. Biol. Phys.
20. 715-722 (1991).
9
J. Deacon, M. J. Peckham, and G. G. Steel, “The radioresponsiveness
of human tumours and the initial slope of the cell survival curve,”
Radiother. Oncol. 2, 317-323 (1984).
10
B. Fertil and E. P. Malaise, “Intrinsic radiosensitivity of human cell
lines is correlated with radioresponsiveness of human tumors: analysis
of 101 published survival curves,” Int. J. Radiat. Oncol. Biol. Phys. 11,
1699-1707 (1985).
11
R. L. Wells and J. S. Bedford, “Dose-rate effects in mammalian cells,”
Radiat. Res. 94, 105-134 (1983).
12
J. B. Mitchell, J. S. Bedford, and S. M. Bailey, “Dose-rate effects in
plateau-phase cultures of S3 HeLa and V79 cells,” Radiat. Res. 79,
552-567 (1979).
13
J. L Humm, “Dosimetric aspects of radiolabeled antibodies for tumor
therapy,” J. Nucl. Med. 27, 1490-1497 (1986).
14
H. D. Thames and J. H. Hendry, Fractionation in Radiotherapy (Taylor and Francis, London, 1987).
15
D. A. Goodwin, C. F. Meares, M. J. McCall, M. McTigue, and W.
Chaovapong, “Pre-targeted immunoscintigraphy of murine tumors
with indium-111-labeled bifunctional haptens,” J. Nucl. Med. 29, 226234 (1988).
16
R. G. Dale, “The application of the linear-quadratic dose-effect equation to fractionated and protracted radiotherapy,” Br. J. Radiol. 58,
515-528 (1985).
17
G. G Steel, “Recovery kinetics deduced from continuous low-dose rate
experiments,” Radiother. Oncol. 14, 337-343 (1989).
18
T. C Stephens, J. J. Eady, J. H. Peacock, and G. G. Steel, “Split-dose
and low dose-rate recovery in four experimental tumour systems,” Int.
J. Radiat. Biol. 52, 157-170 (1987).
19
J. B. Mitchell, J. S. Bedford, and S. M. Bailey, “Dose-rate effects on the
cell cycle and survival of S3 HeLa and V79 cells,” Radiat. Res. 79,
520-536 (1979).
20
H. B. Kal, G. W. Barendsen, R. Bakker-van Hauwe, and H. Raise,
“Increased radiosensitivity of rat rhabdomyosarcoma cells induced by
protracted irradiation,” Radiat. Res. 63, 521-530 (1975).
21
I. E. van Oostrum, S. Erkens-Schulze, M. Petterson, I. S. Wils, and D.
H. Rutgers, “The relationship between radiosensitivity and cell kinetic
effects after low- and high-dose-rate irradiation in five human tumors in
nude mice,” Radiat. Res. 122, 252-261 (1990).
22
L. E. Dillehay and J. R. Williams, “Radiobiological characteristics of
radiolabeled immunoglobulin therapy,” in Proceedings of the 1988
ACNP/SNM Joint Symposium on the Biology of Radionuclide Therapy
(American College of Nuclear Physicians, Washington, DC, 1989), pp.
262-269.
23
W. U. Shipley, J. H. Peacock, G. G. Steel, and T. C. Stephens, “Continuous irradiation of the Lewis lung carcinoma in vivo at clinicallyused ‘ultra’ low-dose rates,” Int. J. Radiat. Oncol. Biol. Phys. 9, 16471653 (1983).
24
A. Szechter, G. Schwarz, and J. M. Barsa, “Continuous and fractionated irradiation of mammalian cells in culture-I. The effect of growth
rate,” Int. J. Radiat. Oncol. Biol. Phys. 4, 991-1000 (1978).
25
L. E. Williams, R. B. Duda, R. T. Proffitt, B. G. Beatty, J. D. Beatty,
J. Y. C. Wong, J. E. Shively, and R. Paxton, "Tumor uptake as a model
of tumor mass: A mathematical model," J. Nucl. Med. 29, 103-109
(1988).
26
R. F. Kallman, “The phenomenon of reoxygenation and its implications for fractionated radiotherapy,” Radiology 105, 135-142 (1972).
27
T. Nylen, H. Acker, B. Bolling, G. Holterman, and J. Carlsson, “Influence of ionizing radiation on oxygen profiles in different types of
multicellular spheroids,” Radiat. Res. 120, 213-226 (1989).
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
28
609
H. B. Kal and G. W. Barendsen, “Effects of continuous irradiation at
low dose-rates on a rat rhabdomyosarcoma,” Br. J. Radiol. 45, 279-283
(1972).
29
C. C. Ling, I. J. Spiro, J. Mitchell, and R. Stickler, “The variation of
OER with dose rate,” Int. J. Radiat. Oncol. Biol. Phys. 11, 1367-1373
(1985).
30
Y. C. Taylor and I. M. Brown, “Radiosensitization in multifraction
schedules, I. Evidence for an extremely low oxygen enhancement ratio,” Radiat. Res. 112, 124-133 (1987).
31
B. Palcic, M. Korbelik, M. Trotter, and L. Revesz. “Oxygen enhancement ratio of fractionated regimens in vitro,” Radiat. Res. 117, 409-418
(1989).
32
J. Hall, J. S. Bedford, and R. Oliver, “Extreme hypoxia; its effect on
the survival of mammalian cells irradiated at high and low dose-rates,”
Br. J. Radiol. 39, 302-307 (1966).
33
I. J Spiro, C. C. Ling, R. Stickler, and J. Gaskill, “Oxygen radiosensitization at low dose rate,” Br. J. Radiol. Res. 58, 357-363 (1985).
34
C. C. Ling, R. Stickler, M. C. Schell, and I. J. Spiro, “The effect of
hypoxic cell sensitizers at different irradiation dose rates,” Radiat. Res.
109, 396-406 (1987).
35
K. K. Fu, S. Hurst, A. C. Begg, and J. M. Brown, “The effects of
misonidazole during continuous low dose rate irradiation,” in Radiation Sensitizers. Their Use in The Clinical Management of Cancer, edited by L. W. Brady (Masson, New York, 1980), pp. 267-275.
36
M Bernstein P. H. Gutin, and D. F. Deen, “Radiosensitization of the
RiF-1 murin; flank tumor by desmethylmisonidazole (Ro 05 9963)
during interstitial brachytherapy,” Int. J. Radiat. Oncol. Biol. Phys. 8,
487-490 (1982).
37
R. B. Pedley, R. H. J. Begent, J. A. Boden, T. Adam, and K. D.
Bagshawe, “The effect of radiosensitizers on radioimmunotherapy, using 131I-labelled anti-CEA antibodies in a human colonic xenograft
model,” Int. J. Cancer 47, 597-602 (1991).
38
R. Rodriguez, E. L. Miller, J. F. Fowler, and T. J. Kinsella, “Continuous infusion of halogenated pyrimidines,” (letter) Int. J. Radiat. Oncol. Biol. Phys. 30, 1380-1382 (1991).
39
R. Nath, P. Bongiorni, and S. Rockwell, “Iododeoxyuridine radiosensitization by low- and high-energy photons for brachytherapy dose
rates,” Radiat. Res. 124, 249-258 (1990).
40
O. Santos, K. D. Pant, E. W. Blank, and R. L. Ceriani, “5Iododeoxyuridine increases the efficacy of the radioimmunotherapy of
human tumors growing in nude mice,” J. Nucl. Med. 33, 1530-1534
(1992).
41
M. H. Griffith, E. D. Yorke, B. W. Wessels, G. L. DeNardo, and W. P.
Neacy, “Direct dose confirmation of quantitative autoradiography with
micro-TLD measurements for radioimmunotherapy,” J. Nucl. Med.
29, 1795-1809 (1988).
42
C. S. Kwok, W. V. Prestwich, and B. C. Wilson, “Calculation of radiation doses for nonuniformly distributed β and γ radionuclides in soft
tissue,” Med. Phys. 12, 405-412 (1985).
43
V K. Langmuir and R. M. Sutherland, “Dosimetry models for radioimmunotherapy,” Med. Phys. 15, 867-873 ( 1988).
44
J. L. Humm and L. M. Cobb, “Nonuniformity of tumor dose in radioimmunotherapy.” J. Nucl. Med. 31, 75-83 (1990).
45
B. Wessels and R. Rogus, “Radionuclide selection and model absorbed
dose calculations for radiolabeled tumor associated antibodies,” Med.
Phys. 11, 638-645 (1984).
46
T. E. Wheldon, J. A. O’Donoghue, T. E. Hilditch, and A. Barrett,
“Strategies for systemic radiotherapy of micrometastases using antibody targeted 131I,” Radiother. Oncol. 11, 133-142 (1988).
47
B. W. Wessels, R. L. Vessella, D. F. Palme, J. M. Berkopec, G. K.
Smith, and E. W. Bradley, “Radiobiological comparison of external
beam irradiation and radioimmunotherapy in renal-cell carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 17, 1257-1263 (1989).
48
S. J. Knox, R. Levy, R. A. Miller, W. Uhland, J. Schiele, W. Ruehl, R.
R. Finston, P. Day-Lollini, and M. L. Goris, “Determinants of the
antitumor effect of radiolabeled monoclonal antibodies,” Cancer Res.
so, 4935-4940 (1990).
49
D. J. Buchsbaum, R. K. Ten Haken, D. B. Heidorn, T. S. Lawrence, A.
A. Glatfelter, V. H. Terry, D. M. Guilbault, Z. Steplewski, and A. S.
Lichter, “A comparison of 131I-labeled monoclonal antibody 17-1A
treatment to external beam irradiation on the growth of Ls174T human colon carcinoma xenografts,” Int. J. Radiat. Oncol. Biol. Phys. 18,
1033-1041 (1990).
50
W. P. Neacy, B. W. Weasels, E. W. Bradley, S. Kovandi, T. Justice, S.
Danskin. and H. Sands, “Comparison of radioimmunotherapy (RIT)
610
Langmuir et al.: Radiobiology and radiolabeled antibody therapy
and 4 MV external beam radiotherapy of human tumor xenografts in
athymic mice (Abst.),” J. Nucl. Med. 27, 902-903 (1986).
51
B. W. Wessels, “Current status of animal radioimmunotherapy,” Cancer Res. (suppl) 50, 970s-973s (1990).
52
S. J. Knox, M. L. Goris, and B. W. Wessels, “Overview of comparative
Medical Physics, Vol. 20, No. 2, Pt. 2, Mar/Apr 1993
610
studies of radioimmunotherapy vs. external beam radiation” Radioth.
Oncol. 23, Ill-117 (1992).
53
C. C. Ling and E. Robinson, “Moderate hyperthermia and low dose
rate irradiation,” Radiat. Res. 114, 379-384 (1988).