Development of Integrated Imaging Techniques for Investigating
Biomarkers in Glioblastoma
HIVE
HEISOOG KIM
B.S., Nuclear Engineering (2004)
Seoul National University
M.D. Certificate, Graduate Education in Medical Sciences (2011)
Harvard-MIT Division of Health Sciences and Technology
SUBMITTED TO THE DEPARTMENT OF NUCLEAR SCIENCE AND ENGINEERING
IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY IN NUCLEAR SCIENCE AND ENGINEERING
AT THE MASSACHUSETTS INSTITUTE OF TECHNOLOGY
SEPTEMBER 2011
@ 2011 Massachusetts Institute of Technology
All rights reserved
Signature of Author:
Heisoog Kim
Department of Nuclear Science and Engineering
A..ust 8"', 2011
Certified by
Bruce R.
n, Professor of Health Science and Technology/Nuclear Engineering
All/7
Thesis Supervisor
Certified by
A. Gregory Sorensen, Professor at Harvard Medical School, Thesis Supervisor
Reviewed by
Elfar Adalsteinsson, Associate professor of Health Science and Technology, Thesis Reader
Accepted by
Mujid S. Kazimi, TEPCO P fess
f Nuclear Engineering
Chair, Department Committee on Graduate Students
Table of Contents
Abstract 5
Acknowledgements 7
List of Figures 9
List of Tables
1. Introduction
11
15
1.1. Significance of Developing Biomarkers 15
2.
Cancer Physiology 19
2.1. Glioblastoma 19
2.2. Vascular Structure and Function in Brain Tumors 20
2.3. Angiogenesis in Tumor 22
2.4. Oxidative Metabolism in Tumors 23
2.5. Hypoxia in Tumors 26
3. Treatment Philosophies 33
3.1. Surgery 33
3.2. Radiotherapy 33
3.3. Chemotherapy 35
3.4. Antiangiogenic Therapy 37
4. Basics of Advanced Imaging Techniques 41
4.1. Magnetic Resonance Imaging Techniques 41
Simultaneous Blood Oxygenation Level Dependent (BOLD) and Arterial Spin Labeling
(ASL) Imaging 42
Proton Magnetic Resonance Spectroscopy ('H MRS) Imaging 44
4.2. Positron Emission Tomography (PET) Imaging Technique 46
18
F-FMISOPET Imaging 47
3
5.
Angiogenesis Biomarker: Serial MR Spectroscopy Revealing an Antitumor Effect of
Cediranib in Glioblastoma 55
5.1.Introduction 55
5.2. Methods 57
5.3. Results 61
5.4. Discussion 68
5.5. Appendix 75
6.
Oxidative Metabolism Biomarker: A Significant Increase in Oxygen Consumption Rate
in Hyperoxia in Glioblastoma 85
6.1. Introduction 85
6.2. Methods 88
6.3. Results 91
6.4. Discussion 99
7.
Hypoxia Biomarker: A Simultaneous Measurement of Relative CMRO 2 with MRI and
'8F-MISO Uptake with PET in Glioblastoma
107
7.1.Introduction 107
7.2. Methods 110
7.3. Results
113
7.4.Discussion
116
8. Conclusion 121
8.1. Current state of Integrated Imaging Techniques for Biomarker Identification 121
8.2. Novel Methodologies
122
8.3. Future Work and Potential Applications 123
4
Development of Integrated Imaging Techniques for Investigating
Biomarkers in Glioblastoma
By
HEISOOG KIM
Abstract
Cancer is a diverse disease with many manifestations. Various imaging modalities including
magnetic resonance imaging (MRI) and positron emission tomography (PET) have been used to
study human cancer. In this study, we developed integrated imaging techniques using advanced
MR and PET to investigate potential biomarkers in glioblastoma (GBM).
First, we applied proton magnetic resonance spectroscopy to assess the therapeutic effects of the
new antiangiogenic drug (cedianib) on GBM. By evaluating changes in the levels of metabolites
predominant in GBM during the treatment, we observed an antitumor response in GBM after one
month. Notably, the index of the ratio of primary metabolites, NAA/Cho, in tumor strongly
predicted 6-month overall survival; these data therefore suggest that NAA/Cho is the MRSdetectable biomarker that relates to tumor angiogenesis.
Second, a simultaneous BOLD-ASL technique was investigated to measure the relative cerebral
metabolic rate of oxygen (CMRO 2 ) in hyperoxia (i.e.,
M
CM 0
) in GBM. Renewed
interest in tumor metabolism, particularly in GBM, has recently prompted a re-examination of the
Warburg effect. Our data have revealed that oxygen-induced CMRO 2 in tumor showed significant
increase, supporting recent hypotheses on the preserved integrity of oxidative pathways in
glycolytically active tumors. These data also propose a second remarkable biomarker for
detecting tumor oxidative metabolic changes.
Finally, and most importantly, we extended our earlier findings to explore the correlation between
changes in oxidative metabolism and hypoxia level in GBM patients undergoing a multi-therapy
5
treatment protocol by acquiring simultaneous MRI-PET data using our novel dual-modality MRPET imaging system. We observed an increase in relative CMRO 2 in regions showing high-level
uptake of our
18
F-MISO probe in pre-treated tumor, and a subsequent large reduction in both
values with tumor regression following treatment. The consistency between tumor oxidative
physiology and hypoxia assessed by our novel integrated imaging approach will be a good
biomarker for detecting oxidative changes with therapeutic effects in gliomas.
Overall, our integrated imaging methods offer great potential to move from the preliminary
biomarker stage to later stages with more clearly established utility. With further investigation,
these imaging tools could contribute in significant ways to the ongoing effort to reduce morbidity
and mortality in cancer.
Thesis Supervisors:
Bruce R. Rosen, M.D., Ph.D.
Professor of Radiology, Harvard Medical School
Professor of Health Science and Technology, Massachusetts Institute of Technology
Director, A.A. Martinos Center, Massachusetts General Hospital
A. Gregory Sorensen, M.D.
Professor of Radiology, Harvard Medical School
6
Acknowledgements
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List of Tables
Table 1 Stages of biom arker developm ent .................................................................................
17
Table 2 Mean and standard deviation of NAA/norCre, Cho/norCre,and NAA/Cho on day -5 and
day -1 for all the patients; their coefficients of variance and p values between two baselines;
in three R O Is..........................................................................................................................64
Table 3 Area Under the ROC curve on early time points (i.e. 1 day, 28 day, 56 day) to determine
the prediction of NAA/Cho to 6-month survival...............................................................67
Table 4 Heart rate (HR) and oxygen saturation level (i.e., saturation of peripheral oxygen, SPo2)
at baseline and at oxygen for all healthy volunteers .........................................................
92
Table 5 Heart rate (HR) and oxygen saturation level (i.e. saturation of peripheral oxygen, SPo2) at
baseline and at oxygen for all nGBM patients.......................................................................92
Table S 1 Number of subjects included in the analysis at each time point ................................
79
9
10
List of Figures
Figure 1 A schematic view of the relationship between biomarkers and the new molecular entity,
its target, the disease pathophysiological cascade, and their impact on stages of drug
developm ent...........................................................................................................................17
Figure 2 Schematic representation of the differences between unicellular and multicellular
organism s in energy m etabolism
....................................................................................
25
Figure 3 a. Chemical structure of '8F-MISO; b. mechanism of '8F-MISO cell trapping............48
Figure 4 Three regions of interest (ROIs) were defined on the corresponding Ti-weighted postcontrast images: (1) enhancing tumor (red voxels), (2) non-enhancing surrounding tumor i.e. peritumoral tissue (blue voxels), and (3) normal tissue on the contralateral side of tumor
(green voxles). To obtain an accurate assessment of tumor metabolism, the voxels in
enhancing tumor were selected by avoiding areas of necrosis, hemorrhage, calcification, or
cy sts. ......................................................................................................................................
60
Figure 5 Serial TI post-contrast MR images and raw spectra in one representative voxel (bluelined box) of enhancing tumor region in the time course of treatment. The spectra exhibit
the dynamic changes of each metabolite's peak in the range of 0.5 - 4 ppm at every time
point of treatm ent...................................................................................................................65
Figure 6 Averaged MRS changes over all eligible patients relative to pretreatment values (%)...66
Figure 7 the relative changes (%) in NAA/Cho separately grouped by the patients' overall
survival (OS) periods based on six-month survival threshold at the early time points posttreatment (i.e days 1, 28, 56) in the enhancing tumor region. ..........................................
67
Figure 8 Ti-weighted anatomical image [a], BOLD signal change map in hyperoxia, signal
changes (%) [b], and CBF signal change map in hyperoxia, signal changes (%) [c] for a
representative healthy subject............................................................................................
93
11
Figure 9 Percent changes (AS) in BOLD signal and in CBF signal, averaged across all ten healthy
93
volunteers, in gray matter ..................................................................................................
Figure 10 post-contrast Ti-weighted anatomical image [a], BOLD signal change map in
hyperoxia, signal changes (%) [b], and CBF signal change map in hyperoxia, signal changes
(%) [c] for a representative newly diagnosed glioblastoma patient. Red circles indicate the
tumor region ...........................................................................................................................
94
Figure 11 [a] Percent changes (AS) in BOLD signal, averaged across all ten glioblastoma
patients, in enhanced tumor (ET) and normal-appearing gray matter, compared to the
average in all ten healthy subjects. [b] Percent changes (AS) in CBF signal, averaged across
all ten glioblastoma patients, in enhanced tumor (ET) and normal-appearing gray matter,
compared to the average in all ten healthy subjects...........................................................94
Figure 12 Post-contrast T 1-weighted image [a] and relative CMRO 2 map in hyperoxia [b] for a
representative newly diagnosed glioblastoma patient. The red circles indicate the tumor
97
region .....................................................................................................................................
CMRO
Figure 13 Averaged relative CMRO 2 (i.e.,
/
C
in newly
0M2|0)
diagnosed glioblastoma
(nGBM) patients. In nGBM patients, the CMRO 2 response at oxygen increased 46% in
enhanced tumor and subtle changes in the normal-appearing gray matter compared to
relative CMRO2 measured in the gray matter in healthy volunteers. An asterisk (*) on the
data point designate statistical significance at a confidence level of 0.95 (* p<0.05) with
Student's paired t-test............................................................................................................97
Figure 14 Model Sensitivity of relative CMRO 2 in tumor to variations in a,
from
P,
M, and
oxygen
[dHb ],
l [dHb]o . ...................................................................................................................
98
12
Figure 15 Combined Brain MR and PET scanner: a BrainPET inserter installed inside the 3T
TimTrio MRI scanner (Left); a BrainPET inserter withdrawn from the MR scanner for
separate M R operation (Right) ............................................................................................
109
Figure 16 Compartment model used to analyze FMISO uptake in tumor ...................................
112
Figure 17 post-contrast Ti-weighted anatomical image [a], BOLD signal change map in
hyperoxia, signal changes (%) [b], CBF signal change map in hyperoxia, signal changes (%)
[c] on 1 day before and 24 days after the treatment for a representative newly diagnosed
glioblastoma patient. The red circles indicate the tumor region..........................................114
Figure 18 [a] percent changes (AS) in BOLD signal, averaged across all three glioblastoma
patients, in enhanced tumor, before and after the treatment, [b] Percent changes (AS) in
CBF signal, averaged across all three glioblastoma patients, in enhanced tumor, before and
after the treatment................................................................................................................114
Figure 19 post-contrast T1-weighted anatomical image [a], relative CMRO 2 map in hyperoxia [b],
18F-MISO uptake (SUV) [c] on 1 day before and 24 days after the treatment for a
representative newly diagnosed glioblastoma patient. The red rounds indicate the tumor
region ...................................................................................................................................
115
CMIRO
Figure 20 [a] averaged relative CMRO 2 (i.e.,
CMR2 10), and [b] averaged '8 F-MISO
uptake [SUV] in three newly diagnosed glioblastoma (nGBM) patients, before and after the
treatm en t ..............................................................................................................................
115
Figure S 1 Mean MRI changes over the same subjects as those of MRS relative to pretreatment
values (%). a) Top: the changes of the MRI indexes demonstrating the vascular effects; b)
Bottom: the changes of the MRI indexes demonstrating the water-related effects...........80
13
Figure S 2 Averaged MRS findings separately grouped by the patients' overall survival (OS)
times based on six-month survival threshold at the early time points post-treatment (i.e days
1, 28, 56) in the enhancing tum or region...........................................................................
81
Figure S 3 Averaged MRI findings separately grouped by the patients' overall survival (OS)
times based on six-month survival threshold at the early time points post-treatment (i.e days
1, 28, 56) in the enhancing tum or region...........................................................................
82
Figure S 4 The relative changes in the ratios of three metabolites before and after one dose of
cediranib, compared to the changes in the absolute value of norCre and the TI relaxation
time constant estimated from various filp angle TI mapping sequences. ........................
83
14
Chapter 1
Introduction
1.1. Significance of Developing Biomarkers
Over the past decade, biomarkers have gained considerably greater visibility and importance in
the development of pharmaceutical drugs, in all therapeutic areas. Aided by recent advances in
fields such as pharmacogenomics, imaging, and molecular diagnostics, as well as better
understanding of the pathophysiology of diseases at the molecular level, biomarkers can enhance
all phases of a drug development program. The recent definition of a biomarker is a characteristic
that is objectively measured and evaluated as an indicator of normal biologic processes,
pathogenic processes, or pharmacologic responses to a therapeutic intervention. Biomarkers can
support validation of mechanism of action, identification of prognostic signatures, patient
selection/stratification to enhance clinical response, development of diagnostic assays, monitoring
of disease progression and response to therapy, and development of surrogate biomarkers. In
addition to these benefits, biomarkers have the potential to significantly impact the commercial
value of a program by enhancing product differentiation, market position, and payer
reimbursement. As a result, biomarkers are now routinely included in clinical research and
development strategies for new molecular entities, extending from drug discovery to regulatory
approval and beyond (Figure 1).
A variety of imaging techniques has been used to establish the wide range of biomarkers, from
the molecular level to the clinical level. An imaging biomarker can be defined as an anatomic,
physiologic, biochemical, or molecular parameter detectable by imaging methods and used to
establish the presence or severity of disease. By this definition, many imaging methods can be
applied to a biomarker, including magnetic resonance (MR) techniques, which provide
information about the resonance of populations of nuclei. These resonances are influenced by
environmental factors, and depending on the encoding scheme, an MR measurement can be
sensitive to a variety of physical and biologic properties of interest. These properties range from
local tissue chemical content to temperature, water diffusion, blood flow, tissue elasticity, and to
the presence of extrinsic contrast agents. This range of sensitivity is one of the great strengths of
15
MRI; however, it also demands that measurement conditions be carefully controlled before
conclusions can be drawn.
The utility of MR imaging biomarkers, especially for clinical decision making for cancer
treatment, extends to more than detection, and requires an understanding of the strengths and
weaknesses of the imaging modality itself, as achieved through an in-depth review. One guide to
introduce imaging biomarkers from a regulatory and drug development perspective describes four
stages of utility ', as listed in Table 1. Many newer MRI techniques fall somewhere between the
pre-biomarker and biomarker stages. This formalism of stages is useful in that it serves as a
reminder of the standard of evidence that rational observers require.
This thesis research provides a preliminary investigation of an integrated approach involving the
advanced MR and PET techniques to examine cancer imaging biomarkers.
16
II
I
A40A. nmchanl!S
&fictaj NAM- wMMdbrenh
Figure 1 A schematic view of the relationship between biomarkers and the new molecular entity,
its target, the disease pathophysiological cascade, and their impact on stages of drug development
Table 1 Stages of biomarker development
Stage
Meaning
Biomarker
Safety and reproducibility established, but utility not yet clear
Licensed
Used in therapeutic decision making
17
References
1. Mills, G. Biomarker Imaging in Drug Development and Licensed Products
18
Chapter 2
Cancer Physiology
2.1. Glioblastoma
An estimated 41,130 primary brain tumors were diagnosed in 2004, 42 percent of which were
gliomas. Glioblastoma (GBM) is the most common type of glioma, accounting for 51 percent of
all gliomas diagnosed between 1997 and 2001 '. Each year approximately 9,000 persons in the
United States are afflicted with glioblastoma, a uniformly fatal disease with an average survival
period of just 12 to 14 months. Less than 4 percent of patients survive five years or more
2,
and
even aggressive treatment involving surgery, radiation and/or chemotherapy fails to extend the
life span of patients beyond more than a few months
3.
In light of these grim statistics and
generally poor prognosis for glioblastoma patients, innovative therapeutic approaches are
desperately needed and their development should be given high priority.
Tumor angiogenesis is an important target in GBM therapy, and endothelial proliferation is a
critical diagnostic criterion for the disease. The classical characteristics of GBM include marked
angiogenesis with microvascular proliferation and severe hypoxia with tumor necrosis ".
Angiogenesis in GBM is driven mainly by VEGF-A 8'9 and signaling via its endothelial receptor
VEGFR2/flk-1 '0. VEGFR2 is the major mediator of several physiological and pathological
effects of VEGF-A on endothelial cells, including proliferation and survival, and migration and
permeability
gliomas
13,14.
11,12.
Levels of VEGF-A and its receptor correlate with the histological grade of
VEGF-induced angiogenesis leads to immature, dysfunctional vessels s. GBM
vessels are dilated, tortuous, disorganized, highly permeable, and characterized by abnormalities
in the pericyte coverage and basement membrane 16-19. Because prognosis remains poor in patients
with GBM, this setting has emerged as an appropriate context to conduct clinical trials of novel
therapeutics, such as, antibodies against VEGF-A or tyrosine kinase inhibitors (TKI).
Two major problems currently plague non-surgical treatment of GBM. First, physiological
barriers impede the delivery of conventional and novel therapeutics. Second, drug resistance
resulting from genetic and epigenetic mechanisms reduces the effectiveness of available drugs.
19
Anti-angiogenic therapy has the potential to circumvent these problems. This therapy targets the
tumor vasculature, derived from local and circulating endothelial cells that are considered
genetically stable. The fact that a large number of cancer cells depend upon a small number of
endothelial cells for their growth and survival might also amplify therapeutic effect.
2.2. Vascular Structure and Function in Brain Tumors
Normal brain vasculature is highly specialized. It is composed of three cell types such as
endothelial cells, pericytes, and astrocytes. These cells form and maintain the blood-brain barrier
(BBB), a structure that selectively restricts the exchange of molecules between the intracerebral
and extracerebral circulatory systems. Tight junctions between endothelial cells prevent
hydrophilic molecules over 500 kDa from passively entering the brain parenchyma. In the brain
endothelium,
several
active,
receptor-mediated
transport
proteins,
including
the
P-
glycoprotein/multi-drug resistance proteins (P-gp/MDR), exclude exogenous compounds from
the brain parenchyma and, consequently, contribute to drug resistance
20
On the other hand, brain tumors also disrupt the brain vasculature. When primary tumors such as
glioblastoma or metastases begin to grow beyond 1-2 mm in diameter within the brain
parenchyma the BBB becomes compromised both structurally and functionally
21-23.
In addition to
the loss of BBB integrity, brain tumors exhibit other pathological features typical of tumors that
arise at other sites. These include marked angiogenesis with endothelial proliferation, severe
hypoxia, and tumor necrosis
metastatic brain tumors
1,
6,',1.
In glioblastoma, as well as in preclinical models of primary and
the basement membrane of tumor vessels is significantly larger in
diameter and thicker than in vessels of the normal brain. These morphological abnormalities are
diagnostic features in brain tumors, particularly glioblastomas. Aberrant microvasculature
typically appears as glomeruloid tufts, consisting of multilayered, mitotically active endothelial
cells and perivascular cells.
The abnormal structure of tumors leads to abnormal function. Functional studies have
characterized the loss of permselectivity in patients with brain tumors. In mice, the vascular
permeability of tumors growing intracranially is generally elevated, although it varies from one
tumor to another, from one location in a tumor to another, and even from one day to another
Some brain tumor vessels have pores in their walls as large as 550 nm in diameter
2.
2.
Although
20
some features of the BBB are, interestingly, retained in the tumor microenvironment, MRI studies
of patients have shown an even bigger difference between normal brain permeability and tumor
vessel permeability. This suggests that disruption of the BBB is not uniform, and that the
transport of molecules across brain tumor vessels is temporally and spatially heterogeneous.
The heterogeneous "leakiness" of tumor vessels causes an abnormal blood flow. Focal leaks can
contribute to nonuniform blood flow and heterogeneous delivery of oxygen and blood-borne
drugs [ref]. This defect, along with the other morphological abnormalities of the network, results
in a red blood cell velocity that is independent of vessel diameter, and is one to three orders of
magnitude lower than that in the surrounding normal pial vessels in glioma and mammary
carcinomas in the mouse brain 2. Although red blood cell velocity cannot be measured in patients,
the blood flow rate measured by functional MRI in patients with malignant gliomas is abnormally
increased within the tumor area 2 6. MRI is routinely used to follow patients with brain tumors, and
advanced vascular MRI techniques are being used to track the structure and function of vessels in
these patients ".
Vascular endothelial growth factor A (VEGFA)-known as VEGF and discovered as the vascular
permeability factor-is a major permeability and pro-angiogenic factor expressed in brain tumors.
VEGF is partly responsible for the disruption of the BBB during tumor growth. Hypoxia and
acidosis, hallmarks of solid tumors, have been shown to independently regulate VEGF
transcription in brain tumors. Multiple oncogenes and tumor suppressor genes (e.g., Ras, SRC
and TP53), hormones, cytokines, and various signaling molecules including nitric oxide and
mitogen-activated protein kinases can also regulate VEGF expression
be released from other cells and the extracellular matrix
12.
11.1228
Finally, VEGF can
A direct consequence of VEGF-
induced vessel leakiness is increased interstitial fluid pressure (IFP)-this is critical in brain
tumors, because increased edema and fluid pressure can cause severe complications. Studies in
both rodents and patients have shown that the IFP increases with brain tumor size; in mice IFP is
higher than the cerebrospinal fluid (CSF) pressure
29.
As a result of elevated IFP, interstitial fluid
leaks from the tumors into the surrounding tissue, raising the CSF pressure until, ultimately, it
equals that of the tumor IFP. In addition to the co-morbidity associated with edema, elevated IFP
forms a barrier to drug delivery. Strategies that can lower fluid accumulation in tumors by
decreasing the leakiness of tumor vessels, or by draining the tumor interstitial fluid artificially,
should be able to lower the tumor IFP and improve drug delivery
24.29
21
Another consequence of elevated VEGF levels and other angiogenic cytokines is their effect on
the expression of adhesion molecules on the tumor vessel endothelium. Intravital studies [ref] of
blood vessels in gliomas and mammary carcinomas in the brain have demonstrated that VEGF
upregulates, whereas basic fibroblast growth factor (bFGF) and angiopoietin 1 downregulate the
adhesion molecules on the angiogenic endothelium. The variance of these growth factors leads to
nonuniform leukocyte recruitment, and thus, growth of primary and metastatic tumors in the brain.
2.3. Angiogenesis in Tumors
Cellular Mechanisms of New Vessel Formation
During the past decade, our knowledge of various angiogenic pathways has grown exponentially.
Similar to extracranial tumors, brain tumors can use four cellular mechanisms to acquire new
blood vessels: co-option, angiogenesis, vasculogenesis, and intussusception. The widely accepted
view is that initial brain tumor growth occurs by co-option pre-existing vessels
84.
As the tumor
grows, cancer cells migrate along blood vessels, compressing and destabilizing the latter, leading
to vessel regression and reduced perfusion, which in turn leads to hypoxia and tumor cell death.
Hypoxia and growth factors secreted by cancer cells recruit new blood vessels through
angiogenesis. Another mechanism by which brain tumors can acquire new vasculature is adult
vasculogenesis. This process is not completely understood, and remains controversial. Bone
marrow-derived cells can enter the blood circulation and contribute to many vessels in some brain
tumors by direct incorporation into the functional vasculature. Stromal-derived factor 1 (SDFl),
expressed in glioma cells, appears to be an important modulator of brain tumor vasculogenesis.
Finally, a mechanism referred to as intussusception, in which tumor vessels remodel and expand
through the insertion of interstitial tissue columns into the lumen of pre-existing vessels, has been
seen in murine models of metastatic colon and lung cancer in the brain. These mechanisms cannot
be easily dissected in patients, since by the time diagnosis is made and/or surgery is done, the
tumors themselves have already induced aggressive angiogenesis.
Molecular Mechanisms of New Vessel Formation
Although VEGF and its receptor (VEGFR2, also known as KDR) are currently the main targets
of anti-angiogenic agents developed for cancer therapy, the number of molecular players involved
in tumor blood vessel survival and growth is expanding. Some key molecules have been known to
be involved in brain tumors. In addition, pathways initially identified in neuronal guidance have
22
recently been shown to have relevance in angiogenesis, and might become therapeutic targets.
Neovascularization of brain tumors, particularly in gliomas, is driven mainly by VEGF signaling
through its endothelial receptor VEGFR2
"'.
VEGFR2 is the main mediator of several
physiological and pathological effects of VEGF on endothelial cells, including proliferation,
migration, and permeability
1122
During sprouting angiogenesis, vessels dilate and become leaky as an initial response to VEGF
secreted by cancer or stromal cells. Angiopoeitin 2 and certain proteinases mediate dissolution in
the basement membrane and interstitial matrix by acting in concert with VEGF. Numerous
molecules stimulate endothelial proliferation, migration and assembly into networks, including
VEGF, angiopoietin angiopoietin 2, and bFGF3 2 .
Cell matrix receptors such as the av@5, atvP3 and a5pl integrins mediate endothelial cell
spreading and migration in response to growth factor signaling
3.
Maintenance of new vessels
depends on the survival of endothelial cells. In normal adult tissues, quiescent endothelial cells
can survive for several years. VEGF, through an interaction with VE-cadherin, and angiopoietin 1
are critical survival factors. Therefore, most angiogenesis inhibitors that target these pathways
cause endothelial apoptosis. By binding VEGF, soluble VEGF receptors such as soluble
VEGFR1, or soluble neuropilin 1 (NRP1), reduce the angiogenic activity of VEGF by
sequestering the ligand. Basic FGF, the first pro-angiogenic factor discovered, is a potent mitogen
for cells of mesodermal origin, including endothelial cells, and has been implicated in
glioblastoma angiogenesis; however, its connection remains to be clarified
12.
VEGF, bFGF,
granulocyte macrophage-colony stimulating factor (GM-CSF), insulin-like growth factor 1
(IGF1), SDF1 and angiopoietins have all been implicated in the mobilization of endothelial
precursors, whereas angiopoietins are known to be important in vessel co-option and
intussusception
123s
2.4. Oxidative Metabolism in Tumors
Cellular respiration is a set of metabolic reactions and processes that take place in the cells of
organisms to convert biochemical energy from nutrients into adenosine triphosphate (ATP) and
then release waste products. Catabolic reactions that involve redox reaction (i.e., oxidation of one
23
molecule and reduction of another) are the reactions in respiration. Respiration is one of the key
processes by which a cell gains useful energy to fuel cellular reformations.
Nutrients commonly used by animal and plant cells in respiration include sugar, amino acids and
fatty acids; a common oxidizing agent (electron acceptor) is molecular oxygen (02). Organisms
that use oxygen as a final electron acceptor in respiration are referred to as aerobic, while those
that do not as anaerobic.
The energy released in respiration is used to synthesize ATP to store this energy. The energy
stored in ATP can then be used to drive processes including biosynthesis, as well as molecule
transport across cell membranes.
For unicellular organisms such as microbes, there is evolutionary pressure to reproduce as quickly
as possible when nutrients are available. Their metabolic control systems have evolved to sense
an adequate supply of nutrients and channel the requisite carbon, nitrogen, and free energy into
generating the building blocks needed to produce a new cell. When nutrients are scarce, the cells
cease biomass production and adapt metabolism to extract maximum free energy from available
resources in order to survive the starvation period (Figure 2
3).
In recognition of these
fundamental differences in metabolic needs, distinct regulatory mechanisms have evolved to
control cellular metabolism in proliferating versus non-proliferating cells.
In multi-cellular organisms, most cells are exposed to a constant supply of nutrients. Survival of
the organism requires control systems that prevent aberrant individual cell proliferation when
nutrient availability exceeds the levels needed to support cell division. Uncontrolled proliferation
is prevented because mammalian cells do not normally take up nutrients from their environment
unless stimulated to do so by growth factors.
Cancer cells overcome this growth factor dependence by acquiring genetic mutations that
functionally alter receptor-initiated signaling pathways. There is growing evidence that some of
these pathways constitutively activate the uptake and metabolism of nutrients that both promote
cell survival and fuel cell growth 7. Oncogenic mutations can result in the uptake of nutrients,
particularly glucose, that meet or exceed the bioenergetic demands of cell growth and
proliferation. This realization has brought renewed attention to Otto Warburg's observation that
cancer cells metabolize glucose in a manner that is distinct from that of cells in normal tissues
39
24
0r1-
r
n-lmi
dI
On-
MIMANABU-w
tie .gbobrn
Cot
Figure 2 Schematic representation of the differences between unicellular and multicellular
organisms in energy metabolism 6
25
By examining how Louis Pasteur's observations of the fermentation of glucose to ethanol might
apply to mammalian tissues, Warburg found that unlike most normal tissues, cancer cells tend to
"ferment"
glucose into lactate, even in the presence of sufficient oxygen, to support
mitochondrial oxidative phosphorylation. A definitive explanation for Warburg's observation has
remained elusive, at least in part because the energy requirements of cell proliferation appear at
first glance to be better met by complete catabolism of glucose using mitochondrial oxidative
phosphorylation to maximize adenosine 5'-triphosphate (ATP) production.
2.5. Hypoxia in Tumors
In the case of most solid tumors, hypoxia develops as a result of the inability of the vascular
system to supply the growing tumor mass with adequate amounts of oxygen. Consequently, both
low oxygen tension and nutrient deprivation contribute to impaired tumor growth, such that
growth beyond 2 mm requires tumor neovascularization.
Several factors may be involved in the development of tumor cell hypoxia: known abnormalities
in the structure and functioning of tumor microvessels, increased diffusion distances between
blood vessels, many of which are not even able to carry oxygenated red blood cells, an expanding
tumor cell mass that competes for oxygen and reduced oxygen carrying capacity of blood due to
disease- or treatment-related anemia. These factors, hence, correspond to three distinct types of
tumor hypoxia 4: (1) Perfusion-related (acute) hypoxia results from inadequate blood flow in
tumors and is generally the consequence of recognized structural and functional abnormalities of
the tumor neovasculature. Such acute hypoxia is often transient, caused by temporary occlusions
and temporary rises in interstitial pressure, and can affect all cells up to the vessel wall; (2)
Diffusion-related (chronic) hypoxia is caused by increased oxygen diffusion distances due to
tumor expansion and affects cells greater than 70-100 pm from the nearest capillary, depending
on where tumor cells lie in relation to the arterial or venous end of a capillary; (3) Anemic
hypoxia relates to a reduced 0 2 -carrying capacity of the blood and may be tumor-associated or
treatment-related.
The presence of hypoxia in human tumors, before the start of treatment, has been observed in a
variety of tumor types including squamous cell carcinomas, gliomas, adenocarcinomas (breast
and pancreas) and sarcomas. Oxygen probes, that is, electrodes implanted directly into tumors to
26
measure oxygen concentration by a polarographic technique
41-43
have shown that (1)
heterogeneity occurs within and between the same tumor types of oxygen concentration and, (2)
hypoxia contributes to poor prognosis; pO2<10 mmHg results in poor local tumor control,
disease-free survival and overall survival.
A large body of clinical evidence suggests that the hypoxia-mediated aggressive behavior of
cancer cells and their resistance to therapy is orchestrated by the heterodimeric transcription
factor, hypoxia inducible factor-1 alpha (HIF-1a), via a number of molecular events required for
the adaptation of tumor cells to hypoxia including unregulated glycolysis, angiogenesis, and
mutant p53
4.
It is also important to realize that in some tumors including uterine lieomyomas,
HIF expression does not always correlate with the presence of hypoxia. This suggests that other
factors including genetic events also contribute to activation of HIF, the most significant of which
is the loss of function of the Von Hippel-Lindau (VHL) tumor suppressor protein, which results
in constitutive activation of the HIF pathway. HIF-1 controls the expression of a variety of genes,
the protein products of which play crucial roles in the acute and chronic adaptation of tumor cells
to oxygen deficiency, including enhanced erythropoiesis and glycolysis, promotion of cell
survival, inhibition of apoptosis, inhibition of cell differentiation, and angiogenesis. Thus,
adaptive changes in the proteome and genome of neoplastic cells result in the emergence of more
aggressive clones made up of cells that are better able to overcome nutrient deprivation or escape
hostile environments. Selection pressures by hypoxia and clonal expansion of the more
aggressive cell types can result in exacerbations of regional hypoxia, further promoting the
development of cell phenotypes that are treatment-resistant. Given the central role of HIF-1 in
hypoxia-mediated aggressive behavior of cancer cells and their resistance to therapy, HIF-1 has
become an important target for the development of anticancer drugs
4i
There is debate about whether there is a critical intratumoral p0 2 level, common across cell types,
below which detrimental changes begin to occur. Experiments performed in cell cultures may not
be applicable to in vivo environments, and some of the variation seen in the literature can be
attributed to the tumor cell type chosen for experiments as well as to the demands of host tissues.
With these caveats in mind, there are critical p0
2
tensions below which cellular functions
progressively cease, or anticancer treatments are impaired 4. The effectiveness of immunotherapy
becomes impaired at 30-35 mmHg; photodynamic therapy effects are attenuated at 15-35
mmHg; on exposure to radiation cell death occurs at 25-30 mmHg; binding of hypoxia
immunohistochemical markers is impaired at 10-20 mmHg; proteome changes are seen at 1-15
27
mmHg, and genome changes occur at 0.2-1 mmHg. Given the differences among these numbers
are fewer than the similarities, from a practical perspective, for solid tissue tumors in vivo, a
value between 5-15 mmHg serves as a good rule of thumb because of its impact on therapy. This
number is in contrast to schemic hypoxia in the myocardium or stroke, where detrimental effects
are experienced at higher 02 levels '". In all these instances the critical oxygen level in tissues
reflects the drive to match delivery with metabolic demand.
The presence of tumor hypoxia appears to impair the effectiveness of radiotherapy, and
radiosensitivity is progressively limited as tumor P 0
2levels
fall. Hypoxia-induced radioresistance
is multifactorial, with the presence of oxygen mediating DNA damage through the formation of
oxygen free radicals, which occurs after the radiation interacts with intracellular water. The ratio
of doses administered under well-oxygenated conditions to hypoxic conditions and needed to
achieve the same biological effect (i.e., cell kill) is called oxygen enhancement ratio (OER). For
sparsely ionizing radiations such as x-rays and gamma rays, the OER at therapeutic doses is
between 2.5 and 3.5
4.
Well-oxygenated cells are about three times more sensitive to x- and
gamma radiation than the same cells when they are hypoxic. Half maximal sensitivity to x- and
gamma rays occurs at oxygen tensions of approximately 2-5 mmHg. At higher P 0
2
values of
approximately 10-15 mmHg near-maximal oxygen effects are seen. However, it should be
recognized that the sensitivity of cells to radiation is dependent on the phase of the cell cycle,
with cells in the G, phase having a lower OER (i.e., greater radiosensitivity) than cells in the Sphase.
28
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Tong, R.T., et al. Vascular normalization by vascular endothelial growth factor receptor 2
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32
Chapter 3
Treatment Philosophies
3.1. Surgery
Surgical resection of tumors is the oldest continuously practiced cancer treatment, and remains a
commonly employed technique. Our knowledge of surgery dates back to The Edwin Smith
Papyrus, the oldest known surgical treatise, written in Egypt in 1600 BC and based on documents
that date back to 3000 BC. The ancient document details evidence that little hope existed for
ancient Egyptian cancer victims, noting that no surgery at all was better for the patient than
surgery on an ulcerated lesion.
In 1884, the first recognized resection of a primary brain tumor was performed at the Hospital for
Epilepsy and Paralysis in London. Surgeons found an encapsulated glioma and removed it.
However, the patient died nearly a month later of meningitis and secondary complications. At the
time, there was no clinical precedent for opening an intact skull and manipulating the brain
(Kirkpatrick 1984).
Dr. Harvey Cushing is considered by many to be the father of modem brain surgery. A
neurosurgeon at the Peter Bent Brigham Hospital in Boston, he performed over two thousand
brain tumor surgeries and pioneered the transsphenoidal approach for removal of pituitary tumors,
while sparing other cranial structures. In 1936, Dr. Cushing's former trainee Dr. Kenneth George
MacKenzie of the Toronto General Hospital performed the first surgical procedure for
glioblastomas, which were previously considered inoperable, terminal lesions. While much has
changed in the operating room, the tumor removal process has remained fundamentally the same
as it was done 5000 years ago.
3.2. Radiotherapy
Cancer radiotherapy developed following the invention of x-rays by Wilhelm Roentgen and the
33
discovery of radium by Marie and Pierre Curie in the 1890s. Roentgen and the Curies discovered
that radiation had the capacity to produce skin damage. Eventually, the theoretical fabric of
modern radiotherapy was built on the clinically critical concepts of dose, dose fractionation, dose
timing, oxygenation, radiosensitizers and cell kinetics. Clinical radiotherapy was born in 1922
when Coutard and Houtant demonstrated the efficacy of radiotherapy in the treatment of
advanced laryngeal cancer.
Radiation therapy is the medical use of ionizing radiation, generally as part of cancer treatment to
control malignant cells. Because of its ability to control cell growth, radiation therapy is
commonly applied to cancerous tumors. Ionizing radiation works by damaging the DNA of
exposed tissue. Furthermore, it is believed that cancerous cells may be more susceptible to death
by this process, as the DNA repair machinery become deactivated in the process of becoming
cancerous. To spare normal tissues, for example skin or other organs, through which radiation
must pass for targeting the tumor, shaped radiation beams are aimed from several angles of
exposure to intersect at the tumor, providing a much larger absorbed dose in the targeted area
than in the surrounding, healthy tissue. Besides the tumor itself, radiation fields may also include
the draining lymph nodes if they are clinically or radiologically linked with the tumor, or if there
is a risk of subclinical malignant spread. It is necessary to include a margin of normal tissue
around the tumor to allow for uncertainties in daily instrument set-up and internal tumor motion.
These uncertainties are likely to result from internal movement (i.e., respiration and bladder
filling) and movement of external skin marks relative to tumor position.
Radiation oncology is the medical specialty concerned with prescribing radiation; it is distinct
from the specialty of radiology, which uses radiation in medical imaging and disease diagnosis. A
radiation oncologist with intent to cure or provide adjuvant therapy prescribes radiation. It is also
used as palliative treatment where cure is not possible; the aim is for local disease control or
symptomatic relief or as therapeutic treatment where the therapy has survival benefit and can be
curative. It is also common to combine radiation therapy with surgery, chemotherapy, hormone
therapy, immunotherapy, or a combination of these approaches. To an extent, most common
cancer types can be treated with radiation therapy. The precise treatment intent will depend on the
tumor type, location, and stage, as well as on the general health of the patient. Total body
irradiation (TBI) is a radiation therapy technique used to prepare the body to receive a bone
marrow transplant. Brachytherapy, in which a radiation source is placed inside or next to the area
requiring treatment, is another form of radiation therapy that minimizes exposure to healthy tissue
34
during procedures to treat cancers of the breast, prostate, and other organs.
Radiation therapy also has several applications in the treatment of nonmalignant conditions such
as trigeminal neuralgia, severe thyroid eye disease, pterygium, pigmented villonodular synovitis,
and in the prevention of keloid scar growth and heterotopic ossification. However, it is important
to note that the use of radiation therapy in nonmalignant conditions is limited partly by the risk of
radiation-induced cancers.
Radiation therapy works by damaging the DNA of cancerous cells. This DNA damage is caused
by one of two types of energy: photon or charged particle. The damage is a result of either direct
or indirect ionizing of the atoms, which make up the DNA chain. Indirect ionization occurs as a
result of water ionization or formation of free radicals (notably, hydroxyl radicals), which then
damage the DNA. In the older and most common form of radiation therapy, intensity-modulated
radiation therapy (IMRT) (photons), the greatest radiation effect is through free radicals. Because
cells have mechanisms for repairing single-stranded DNA damage, double-stranded DNA breaks
prove to be the most significant technique to cause cell death. Cancer cells generally are
undifferentiated and stem cell-like. They reproduce more, and exhibit a diminished ability to
repair sub-lethal damage compared to most healthy differentiated cells. This single-stranded DNA
damage is then passed on through cell division, causing an accumulation of damage to the cancer
cells' DNA, causing them to die or reproduce more slowly.
One of the major limitations of photon radiation therapy is that the cells of solid tumors become
deficient in oxygen. Solid tumors can outgrow their blood supply, generating a low oxygen state
known as hypoxia. Oxygen is a potent radiosensitizer, increasing the effectiveness of a given dose
of radiation by forming DNA-damaging free radicals. Tumor cells in a hypoxic environment may
be more resistant to radiation damage than those in a normal oxygen environment
4.
Much
research has been devoted to overcoming hypoxia, including the use of high-pressure oxygen
tanks, blood substitutes that carry increased oxygen, hypoxic cell radiosensitizer drugs such as
misonidazole and metronidazole, and hypoxic cytotoxins (tissue poisons), such as tirapazamine.
3.3. Chemotherapy
35
Chemotherapy is the treatment of cancer with an antineoplastic drug or a combination of such
drugs into a standardized treatment regimen. Most commonly, chemotherapy acts by killing cells
that divide rapidly, one of the key properties of most cancer cells. This implies that chemotherapy
also harms cells that divide rapidly under normal circumstances, such as cells in the bone marrow,
digestive tract, and hair follicles, resulting in the most common side effects of chemotherapy:
myelosuppression or decreased production of blood cells, and hence also immunosuppression;
mucositis or inflammation of the lining of the digestive tract; and alopecia, or hair loss.
Cancer is the uncontrolled growth of cells coupled with malignant behavior: invasion and
metastasis. It is believed that cancer is caused by the interaction between genetic susceptibility
and environmental toxins. Most chemotherapeutic drugs widely work by impairing mitosis (cell
division), effectively targeting fast-dividing cells. These cytotoxic drugs damage the cells and the
latter undergo apoptosis. Scientists have yet to identify specific features of malignant and immune
cells that would make them uniquely targetable. Thus, other fast-dividing cells, such as those
responsible for hair growth and for the replacement of the intestinal epithelium (lining), are also
often affected. However, some drugs have better side effect profiles than others, allowing doctors
to adjust treatment regimens to the advantage of patients in certain situations.
As chemotherapy affects cell division, tumors with high growth fractions such as acute
myelogenous leukemia and aggressive lymphomas, including Hodgkin's disease are more
sensitive to chemotherapy, as a larger proportion of the targeted cells undergo cell division at any
time. Malignancies with slower growth rates, such as indolent lymphomas, tend to respond to
chemotherapy more modestly.
Drugs affect differentiated tumors more effectively, because mechanisms regulating cell growth
are usually still preserved
5.
With succeeding generations of tumor cells, differentiation is
typically lost, growth becomes less regulated, and tumors become less responsive to most
chemotherapeutic agents. Near the center of some solid tumors, cell division is effectively ceased,
which makes them insensitive to chemotherapy. Another problem with solid tumors is the fact
that the chemotherapeutic agent often does not reach the core of the tumor. Moreover, cancer
cells become more resistant to chemotherapy treatments over time.
Although chemotherapy has been used clinically through most of the twentieth century, drug
treatment of cancer has largely been a disappointment. Cytotoxic therapy often damages the
36
patient's healthy cells as much as the cancerous ones, and the period of survival based solely on
chemotherapy is poor, such that it is almost always used in conjunction with surgery or
radiotherapy, or both. However, a new class of drugs holds promise as a novel and potentially
powerful approach to cancer treatment, restricting tumor growth by targeting primarily required
blood vessels, including recent trends in antiangiogenic therapeutic targets.
3.4. Antiangiogenic Therapy
The dependence of tumor growth and metastasis on angiogenesis provides a powerful rationale
for antiangiogenic approaches to cancer therapy
52.3.
Targeting blood vessels in brain tumors has
been a particularly attractive strategy, given the characteristic high degree of endothelial
proliferation, vascular permeability, and pro-angiogenic growth-factor expression (i.e., VEGF).
However, so far no antiangiogenic agent has been approved for the treatment of brain tumors.
Two classes of agents have been approved for non-central nervous system (CNS) tumors. One is
the anti-VEGF antibody bevacizumab, which neutralizes VEGF, and VEGF-receptor tyrosine
kinase inhibitors (TKIs) (sorafinib and sunitinib). Bevacizumab is effective only when combined
with standard chemotherapeutic agents. These approaches raise an interesting question about how
a drug designed to destroy blood vessels is able to augment the outcome of drugs that require
blood vessels. This paradox may be resolved by introducing a novel hypothesis: when used
judiciously, these agents can transiently normalize the tumor vessels and enhance the delivery and
efficacy of concurrently administered cytotoxic agents 54-55. Compelling evidence in support of
this hypothesis was obtained through a number of precinical models
"5,
including a mouse
model of breast cancer metastasis in the brain and an orthotopic glioblastoma model
. Moreover,
data consistent with the preclinical findings are beginning to emerge from the clinic, with
important implications for cancer and other pathologies.
Using serial, non-invasive MRI techniques, Batchelor et al.v have shown that cediranib
(AZD2171, an oral, pan-VEGF receptor TKI with activity against PDGFRa,
P
and c.kit),
temporarily induces a normalization time window in tumor vessels in patients with recurrent
glioblastoma. This normalization had a rapid onset, was prolonged but reversible, and had
significant clinical and functional consequences. Cediranib monotherapy led to an objective
radiographic response (that is, reduction in contrast-enhanced tumor volume on MRI by 250 per
37
cent) in more than half the patients examined in the study, and reduced tumor-associated
vasogenic edema in most. In addition, this study was the first to identify the onset and duration of
a vascular normalization time window induced by an antiangiogenic agent. Other studies showing
evidence of the beneficial effect of anti-VEGF therapy in malignant glioma have dealt with
bevacizumab in combination with chemotherapy
5*.
Besides vascular normalization, several other mechanisms of action of anti-VEGF agents have
been posited 60. When used in combination with cytotoxic therapies, anti-VEGF agents might
sensitize endothelial cells cytotoxic agents such as radiation. Moreover, these agents may also
counteract the surge in VEGF that occurs after tumor irradiation. This mechanism of action of
antiangiogenic therapy is particularly relevant for characteristically non-metastatic brain tumors
ss. Finally, antiangiogenic therapy may disrupt the perivascular cancer stem-cell niche, and
thereby potentially eradicate brain cancer stem cells
61.
Although clinical data in support of these
mechanisms are not yet available, a better understanding of the mechanism of action of antiVEGF therapy will allow optimization of current combinations in terms of dose and schedule as
well as potential reduction in side effects of the combined treatment.
Cediranib demonstrates clear potential to reduce vasogenic edema and has a steroid-sparing effect
2.
The antiedema effect may also result from other anti-VEGF therapies
5.
The benefits of anti-
VEGF strategies might include endothelial injury and increased permeability as well.
Bevacizumab has shown some efficacy in a small study of patients with cerebral radiation
necrosis
62.
These observations suggest that deciphering how anti-VEGF agents work might not
only increase the efficacy of anti-VEGF treatment, but might also improve the quality of life of
patients with brain tumors. Larger, prospective studies with clearly defined endpoints will be
necessary to validate anti-VEGF therapy in patients with vasogenic cerebral edema and cerebral
radiation necrosis.
38
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13.
Pope, W.B., Lai, A., Nghiemphu, P., Mischel, P. & Cloughesy, T.F. MRI in patients with
high-grade gliomas treated with bevacizumab and chemotherapy. Neurology 66, 12581260 (2006).
39
14.
Vredenburgh, J.J., et al. Phase II trial of bevacizumab and irinotecan in recurrent
malignant glioma. Clin Cancer Res 13, 1253-1259 (2007).
15.
Carmeliet, P. Angiogenesis in life, disease and medicine. Nature 438, 932-936 (2005).
16.
Calabrese, C., et al. A perivascular niche for brain tumor stem cells. Cancer Cell 11, 6982 (2007).
17.
Gonzalez, J., Kumar, A.J., Conrad, C.A. & Levin, V.A. Effect of bevacizumab on
radiation necrosis of the brain. Int J Radiat Oncol Biol Phys 67, 323-326 (2007).
40
Chapter 4
Basics of Advanced Imaging Techniques
4.1. Magnetic Resonance Imaging Techniques
Magnetic Resonance Imaging (MRI) is a non-invasive method that uses the nuclear magnetic
resonance phenomenon to render internal images of an object. Used primarily in medical imaging
to demonstrate pathological
or other physiological
alterations of living
tissues, most
"conventional" medical MRI techniques rely on the relaxation properties of excited hydrogen
nuclei in water and lipids. When the object of interest is placed in a powerful, uniform magnetic
field, the spins of atomic nuclei with a resulting non-zero spin must arrange in a particular
manner with the applied magnetic field, according to quantum mechanics principles. Nuclei of
hydrogen atoms (protons) have a simple spin
, and therefore align either parallel or antiparallel
to the magnetic field.
The spin polarization determines the basic MRI signal strength. The spin polarization of protons
denotes the population difference of the two energy states that are associated with the parallel and
antiparallel alignment of the proton spins in the magnetic field, and is governed by Boltzmann
statistics. The vast quantity of nuclei in a small volume is summed to produce a detectable change
in the field. The magnetic dipole moment of the nuclei then precesses around the axial field; the
frequency with which the dipole moments precess is called the Larmor frequency. The tissue is
then briefly exposed to pulses of electromagnetic energy (RF pulses) in a plane perpendicular to
the magnetic field, causing some of the magnetically aligned hydrogen nuclei to assume a
temporary non-aligned high-energy state. In other words, the steady-state equilibrium established
in the static magnetic field becomes perturbed, and the population difference of the two energy
levels is altered. The frequency of the pulses is governed by the Larmor equation to match the
required energy difference between the two spin states.
To reconstruct the image of the object, the voxels of the subject are selected using orthogonal
magnetic field gradients. Although it is relatively common to apply gradients in the principal axes
of a patient, MRI allows completely flexible orientations of images. All spatial encoding is
41
obtained by applying magnetic field gradients, which encode positions within the phase of the
signal. Images can be created from the matrix using the discrete Fourier transform (DFT). Typical
medical resolution is about 1 mm3, while the research model has reached a resolution from tens
down to one order of p1 '.
Simultaneous Blood Oxygenation Level Dependent andArterial Spin Labeling Imaging
Information related to the oxygenation status of brain tumors can be obtained using functional
MRI techniques such as Blood Oxygenation Level Dependent (BOLD)
2
and Arterial Spin
3
Labeling (ASL) MR Imaging.
BOLD MRI has been extensively used in brain activation studies. The primary source of contrast
in BOLD MR images is the endogenous paramagnetic deoxyhemoglobin, which increases the
MR transverse relaxation rate (R 2 *) of water in blood and surrounding tissues, making the
technique sensitive to pO2 within perfased vessels and adjacent tissues. Although BOLD contrast
does not measure PO2 directly, it provides indirect information about the oxygenation level, and
hence brain activity. BOLD signal results from complex interactions between cerebral blood flow
(CBF), blood volume, and oxygenation consumption. Neuronal activation in response to external
stimuli causes a local increase in cerebral blood flow, such that more oxygen and metabolites
(glucose) are delivered to the activated neurons 4. As oxygen delivery exceeds the demand, or, in
other words, when the concentration of diamagnetic oxyhemoglobin increases and that of
paramagnetic deoxyhemoglobin decreases at the venous level, there is an increase in the MRI
signal-the BOLD signal. Although tumors do not respond to external stimuli, a similar paradigm
can be used to obtain information about the oxygenation level using BOLD MRI. Specifically, the
BOLD signal can be obtained by comparing the tumor response as the patient breathes room air
and pure oxygen. The hypothesis is that the changes in blood flow in response to hyperoxia will
alter the tumor oxygenation status, and the effects will be more pronounced in hypoxic regions.
Additional information about the hemodynamic changes can be obtained using a perfusion
imaging technique such as ASL. Whereas BOLD contrast primarily detects microscopic
susceptibility changes (T 2 *) that indirectly reflect changes in CBF, ASL perfusion contrast
imaging uses magnetically labeled water in the blood as an endogenous tracer to measure the
changes in T, directly induced by changes in regional blood flow. With the pulsed ASL pulse
sequences, it is possible to measure perfusion and BOLD signals simultaneously by applying inplane saturation pulses in the imaging slice immediately before the inversion pulse s. The
42
magnetization of tagged blood undergoes inversion recovery during the tag state and is fully
relaxed during the control state, while the magnetization of static tissues undergoes saturation
recovery during both states. The subtraction of tag-state signal from control-state signal results in
a perfusion-weighted signal, and the addition of signal of both states results in the BOLDweighted signal. Compared to to separate acquisition of perfusion and BOLD data separately, this
acquisition scheme shortens the scanning time by half and eliminates spatial misregistration
errors. Therefore, simultaneous detection of BOLD and ASL signals minimizes the temporal and
spatial variations in the two functional signals. Furthermore, cerebral metabolic rate of oxygen
consumption (CMRO2) can be obtained quantitatively from a combination of BOLD and
perfusion experiments -.
The feasibility and efficacy of simultaneous BOLD-ASL imaging has been demonstrated in brain
activation experiments '"'. Although its application to tumor hypoxia imaging has not been
discussed, it is expected that CBF and BOLD images, together with CBV images, are useful for
the determination of CMRO 2 in tumors "-", indicate regional oxygen consumption and
metabolism independent of vascular dynamics. The application and optimization of simultaneous
BOLD-ASL imaging techniques for hypoxia imaging in tumors will be important for efficiently
distinguishing between blood flow and oxygen consumption effects, as well as for achieving
improved BOLD contrast. Simultaneous acquisition of complementary functional indices that
reflect different aspects of the oxygenation status of brain tumors would be a valuable tool for
functional imaging studies, offering enhanced detection power and improved data interpretation.
We have investigated an imaging technique that can simultaneously acquire BOLD and ASL
perfusion images. Hyperoxia (100 percent oxygen supply) experiments in healthy human subjects
have demonstrated that this combined technique can measure signal changes related to blood flow
and blood oxygenation equally well in a single scan compared to separately acquired scans "'".
Furthermore, image acquisition time with this new technique is only one-third that of
conventional techniques. This advantage is especially important, as shorter scan sessions are less
taxing for patients. The use of the simultaneous sequence may also allow for a more accurate
comparison of ASL and BOLD response due to the lower sensitivity to the variations in the
respective time courses, compared to separate scans. In addition, since the clinical scans most
used for patients typically require a long data acquisition time, the time saved by using the
simultaneous scanning method could greatly facilitate clinical studies, providing greater
43
convenience to patients as well as expediting the acquisition of valuable data from vulnerable
patient groups.
ProtonMagnetic Resonance Spectroscopy (H MRS) Imaging
'H MRS can provide information about the biochemical profile of tissue
'6, and
is increasingly
being used as a non-invasive method to classify brain lesions '7-1. The earliest MRS studies
showed clear differences between the 1H spectra of brain tumors and normal brain tissue. 19,20 1H
MRS abnormalities are observed in normal-appearing tissue outside the Gd-enhancing region that
is conventionally used to delineate a tumor
2122,
which suggests a molecular imaging method
using 'H MRS may improve the demarcation of cancerous brain tissue and tumor localization for
treatment. To date, 'H MRS studies have mostly been performed in a research context, but
clinical applications are increasing as in vivo MRS techniques and hardware have become more
reliable and user-friendly, along with improved data analysis and confidence of interpretation.
Accurate classification of brain tumors by in vivo 'H MRS requires determination of the
relationship between metabolite profile and tumor type, but several factors can hinder this
important step 3. Tumors are often very heterogeneous, and their spectra are likely to have
contributions from multiple tissue compartments. As well as viable tumor cells, there may be
necrotic and cystic tissue; in the case of highly infiltrative tumors such as gliomas, there may also
be contributions from normal brain tissue. In addition, tumor growth is not well regulated,
variations in cellular metabolism and cell density occur, and as a tumor progresses it may become
composed of cells of different grades. Nevertheless, consistent 'H spectra patterns have been
found in a variety of tumor types
',
and statistical techniques such as pattern recognition have
been used to determine the spectral features that correlate with tumor type despite variations due
to tumor heterogeneity 2-27. Biochemical interpretation of in vivo 'H MRS data has been aided by
comparison with high-resolution MR studies of cell cultures or biopsy samples. 28.29
For routine clinical studies single voxel spectroscopy (SVS) with short echo time (TE) provides
the advantages of speed and robustness
3-32.
It is often possible to acquire reasonable quality
spectra in locations close to scalp lipid, or in regions of field inhomogeneity, for instance, in
tissues close to the sinuses. However, as tumors are often heterogeneous, chemical shift imaging
(CSI) can provide more information about tumor heterogeneity and infiltration.
44
Several primary metabolites have been observed in the brain to discriminate between normal and
abnormal tissues
N-acetyl aspartate (NAA; singlet at 2.05 ppm) is regarded as a neuronal
20,3.
marker specific to neurons, and since most brain tumors are of non-neuronal origin, NAA is
reduced or absent. In MRS of tumors, the presence of NAA within a spectrum is generally
believed to indicate the presence of viable neurons within an infiltrative tumor such as a glioma.
Total Choline (tCho; single peak at ~3.22 ppm, comprising signals from choline, phosphocholine
and glycerophosphocholine) is elevated in tumors compared to normal brain tissue, and is a
general marker for cancers in the brain "* as well as in other tissues
3536.
The elevation of tCho
is thought to be due to accelerated membrane synthesis of rapidly dividing cancer cells.
Compared to the levels seen in normal brain, total Creatine (tCr; singlets at 3.04 and 3.9 ppm,
each comprising signals from both phosphocreatine and creatine) is reduced in astrocytomas, and
almost absent in some benign tumors. However, it is generally assumed that tCr is not
significantly changed in terms of tumor metabolism.
Lactate (doublet at 1.33 ppm) is frequently observed in tumors, due in part to their preference for
aerobic glycolysis ", and is often most prominent in the highest-grade tumors. However, as PET
data demonstrate lactate levels do not correlate well with either grade or metabolic rate
3".
Lactate is present in both intra and extracellular spaces, and its overall level is a function of
metabolic rate and clearance.
Lipids (1.3 and 0.9 ppm) are also characteristic of high-grade tumors at short TE 2",
observed only in 41 percent of high-grade tumors at long TE
41.
but are
To some extent, lipid signals
have been considered a nuisance as they can obscure lactate and alanine, and hence, long TE
studies are sometimes preferred. Biopsy studies indicate that lipids correlate with necrosis, which
is a histological characteristic of high-grade tumors. Lipid signals, therefore, could be membrane
phospholipids released during cell breakdown, and may thus relate to the necrotic fraction.
The ratio of choline to NAA index (CNI) is a standard measure for differentiating normal and
abnormal tissues in the brain from the spectrum in each voxel; a CNI >2.5 defining tumor
42.
For
patients with untreated gliomas, measured CNI values exhibited 90 percent sensitivity and 86
percent specificity for separating tumor tissue from non-tumor tissue including normal, edema,
gliosis and necrosis
42
45
4.2. Positron Emission Tomography (PET) Imaging Technique
Positron emission tomography (PET) uses ionizing radiation to produce a three-dimensional
image of functional processes in the body. A positron-emitting radionuclide tracer injected into
the body on a biologically active molecule is taken up by tissues, allowing the PET camera to
detects pairs of gamma rays emitted indirectly by the tracer. The three-dimensional maps of tracer
concentration within the body are then reconstructed by computer analysis.
As the radioisotope undergoes positron emission decay, it emits a positron, an antiparticle of the
electron with opposite charge. The emitted positron travels in tissue for a short distance, during
which time it loses kinetic energy, until it decelerates to a point where it can interact with an
electron 4. The encounter annihilates both electron and positron, producing a pair of annihilation
photons moving in approximately opposite directions, which are detected when they reach a
scintillator in the scanning device, creating a burst of light that is detected by photomultiplier
tubes or silicon avalanche photodiodes (Si APD). The technique depends on simultaneous or
coincident detection of the pair of photons moving in approximately opposite direction. Photons
that do not arrive within a timing-window of a few nanoseconds are ignored.
A technique commonly used for PET image reconstruction is similar to the reconstruction of
computed tomography (CT) and single-photon emission computed tomography (SPECT) data.
Using statistics collected from tens of thousands of coincidence events, a set of simultaneous
equations for the total activity of each parcel of tissue along many lines of responses can be
solved by a number of techniques ".
Thus, a map of radioactivity is constructed and plotted as
a function of location for voxels, showing the tissues in which the molecular tracer has become
concentrated.
Radionuclides used in PET scanning are typically isotopes with short half-lives, such as carbon11 (~20 min), nitrogen-13 (-10 min), oxygen-15 (-2 min), and fluorine-18 (-110 min). These
radionuclides known as radiotracers are incorporated either into compounds normally used by the
body, or into molecules that bind to receptors or other sites of drug action. Such labeled
compounds are known as radiotracers. PET technology can be used to trace the biologic pathway
46
of any compound in a living specimen, provided it can be radiolabeled with a PET isotope; hence,
the processes that can be probed by PET are virtually limitless, and radiotracers for new target
molecules and processes continue to be synthesized. At present, however, by far the most
commonly used radiotracer in clinical PET scanning is fluorodeoxyglucose (FDG), an analogue
of glucose that is labeled with fluorine-18. Due to the short half-lives of most radioisotopes, the
radiotracers must be produced using a cyclotron in close proximity to the PET imaging facility.
The high costs of the cyclotrons needed to produce the short-lived radionuclides for PET
scanning, as well as the need for specially adapted on-site chemical synthesis apparatuses to
produce radiopharmaceuticals has somewhat limited the availability of PET; at present, the use of
PET is not as widespread as other imaging technologies such as MRI. The short half-lives of
radionuclides also contributes to the relatively limited use of PET. Although the minimized
radiation dose of these short-lived radionuclides is advantageous to the patient, their use is
restricted to an abbreviated window of administration. For instance, the half-life of fluorine-18 is
about two hours, and the prepared dose of a radiopharmaceutical bearing this radionuclide will
undergo multiple half-lives of decay during the working day. As such, frequent recalibration of
the remaining dose is necessary, and careful planning of patient scheduling is essential.
18
F-MISO PET Imaging
**F-MISO enters cells by passive diffusion when nitroreductase enzymes become trapped in cells
where tissue oxygen partial pressure is reduced. When oxygen is abundant in normally
oxygenated cells, the parent compound is quickly regenerated by reoxidation, and metabolites do
not accumulate. However, in hypoxic cells, the low oxygen partial pressure prevents reoxidation
of 1"F-MISO metabolites, resulting in tracer accumulation in hypoxic cells, as shown in Figure 3.
Because '8F-MISO only accumulates in hypoxic cells with functional nitroreductase enzymes,
18
F-MISO collects in viable cells but not in dead necrotic cells.
47
a. Chemical structure of FMISO and radiolabeled with fluorine-18
01HP
N
N,
NO2
1.Wpra222/=tF
222NK COJF
.OTs
C
n
N
N
NO2
(A)
b. Mechanism of FMISO cell trapping
Ml
F18-WOSO
-
RNH1
F-18--M11SC
"Wasne
Figure 3 a. Chemical structure of 18F-MISO; b. mechanism of '8F-MISO cell trapping
Time-activity curves have shown that the activity of '8F-MISO in a typical normal muscle region
of interest (ROI) achieves equilibrium with plasma levels within 30 minutes, but selective
retention of '8 F-MISO is observed in hypoxic tissue within an hour after injection, and persists for
two and a half hours.
48
Quantification of the 8' F-MISO tumor/plasma ratio can be optimally
performed two hours after injection, when normal tissues have equilibrated with plasma, and
hypoxic tissue continues to have selective retention of '8F-MISO, leading to favorable
information about the hypoxic volume being assessed. A complete histogram of in vivo "'F-MISO
tissue/plasma ratios constructed from animal studies has defined the normal tissue/plasma ratio as
<13. Therefore, a conservative selected threshold of '8F-MISO tumor/plasma ratio of >1.4 two
hours after injection is an indicator of significant hypoxia.
4-.
Tumor hypoxia has been confirmed by direct measurements with the oxygen-sensing electrode in
a variety of cancers
5
54, and multiple studies correlating direct oxygen measurements with '8F-
MISO uptake have also been performed 3-*. These studies have shown that the degree of '8FMISO uptake correlates with low tissue oxygen tension, and the retention of
18
F-MISO is
significantly greater in hypoxic tumors than in normoxic tumors, and further, that there is strong
correlation between '8 F-MISO uptake and
P0 2 readings
of 5 mmHg". An important consideration
in the analysis of these studies is that direct measurement of hypoxia by a hypoximeter does not
provide an overall picture of the hypoxic, necrotic and aerobic regions within a particular tumor,
all of which can be assessed with an '8F-MISO PET scan.
48
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53
54
Chapter 5
Angiogenesis Biomarker:
Serial MR Spectroscopy Revealing an Antitumor Effect of Cediranib
in Glioblastoma
5.1. Introduction
Glioblastoma multiforme (GBM) is a severe and generally fatal brain tumor, with an annual
incidence of approximately 9,000 in the United States. Despite aggressive treatment strategies
involving surgery, radiation and cytotoxic chemotherapy, the average survival time for a patient
with GBM is less than 1 year, and fewer than 5% of patients survive 5 years or more ".
Innovative therapeutic approaches are desperately needed for this patient population. GBM is
typically characterized by marked angiogenesis and paradoxically severe hypoxia and necrosis
16,70,104,1s.
Angiogenesis in GBM is mediated by vascular endothelial growth factor (VEGF)
which leads to dysfunctional and highly permeable microvessels, characterized by abnormalities
in pericyte coverage and basement membrane thickness 15''6'108-109.
Bevacizumab (Avastin, Genentech/Roche), a humanized monoclonal antibody that targets VEGFA ligand, was approved by the US Food and Drug Administration in May 2009 for use as a
monotherapy for recurrent GBM, based on phase II evaluations "0. However, the mechanisms by
which antiangiogenic therapies benefit these patients are not well understood. Jain and colleagues
have demonstrated that anti-VEGF therapies "normalize" the tumor vasculature. Their findings in
both pre-clinical models and a clinical trial of rectal cancer have indicated that anti-VEGF
therapy leads to reductions in microvessel density and mean blood vessel diameter, basement
membrane thickness, tumor interstitial pressure and vasculature permeability as well as enhanced
pericyte coverage
108,111,112
A phase II clinical trial of cediranib (AZD2171, AstraZeneca Pharmaceuticals, UK), a potent oral
pan-VEGF receptor TK inhibitor, demonstrated that vascular normalization was induced at 24
hours and lasted to 28 days in recurrent GBM patients, as determined by structural and functional
MRI metrics
27,113.
However, these functional and structural improvements were reversed, and the
55
tumor reverted to an abnormal state with further continuation of cediranib therapy. These findings
thus suggest there may be a "normalization window" during which delivery of chemotherapeutics
may be optimized.
A preclinical study of GBMs in mice demonstrated that use of cediranib can lead to a decrease in
edema, by vascular normalization, as well as prolonged survival even as tumor growth persists "4.
The study suggested that the benefits of antiangiogenic therapies might be partially due to
antiedema effects rather than direct antitumor effects. However, other investigators have noted
direct antitumor effects of VEGF blockade "5, as well as tumoristatic activities-i.e., tumor
growth inhibition and tumor cell apoptosis-in a broad range of human tumors
possible inhibitory effect on stem-cell-like glioma cells
1".
1"118,
and a
Thus, although the extent of vascular
normalization after one dose of cediranib correlates with both progression-free survival (PFS) and
overall survival (OS) in recurrent GBM patients 120, underscoring the clinical importance of
vascular normalization, the degree of antitumor effect, if any, beyond vascular normalization in
this class of therapies remains uncertain in humans.
Early magnetic resonance spectroscopy (MRS) studies showed clear differences between the
spectral profiles of tumor and normal brain tissues. For example, choline (Cho) is typically
elevated in brain tumors and metastases, potentially because of increased cellular turnover and the
accelerated membrane synthesis that occur in rapidly dividing cancer cells
.21.Levels of N-
acetylaspartate (NAA), regarded as a neuronal marker, decrease in any disease that adversely
affects neuronal integrity
122.
Hence, relative to normal healthy brain tissue, neoplastic tissue
generally exhibits elevated Cho concomitant with decreased NAA 8, a hallmark widely used in
clinical practice. Given these metabolic characteristics of tumors, 'H-MRS may be able to
improve demarcation of cancerous brain tissue when used in combination with the high-quality
anatomical data provided by conventional MRI techniques.
In this study, we compared 'H-MRS data and conventional MRI data in a group of patients
undergoing cediranib monotherapy for rGBM. Our results suggest that 'H-MRS confirms the
findings from MRI, and provides additional information to improve understanding of cancer
responses to antiangiogenic agents in rGBM patients.
56
5.2. Methods
PatientRecruitment
Thirty-one patients (mean age 53.7, range 20-77) with recurrent GBM (rGBM) were recruited for
this study. Every patient underwent surgical resection and radiochemotherapy after initial
diagnosis and pathologic confirmation of GBM. At the time of enrollment into the study, all
patients had tumor recurrence, as determined by MRI and/or neurological deterioration.
All patients received an oral dose of cediranib (45 mg) daily, which was reduced as necessary
27,113 until there was radiographic or clinical evidence of disease progression. Neurological and
physical examinations and MRI studies were performed throughout the course of treatment.
MR Imaging and Spectroscopy
MR studies were performed using a 3T MRI scanner (Tim Trio, Siemens, Malvern, PA) at a
series of time points: -5, -1, 1, 26-28, 54-56, and 110-112 days from the start of cediranib
treatment.
We performed serial 2D Chemical Shift Imaging (CSI)
'23
using Point Resolved Spectroscopy
(PRESS) 124 for signal pre-localization and Outer Volume Saturation (OVS)
'
to minimize
contamination from subcutaneous fat. Water suppression was achieved with a modified Chemical
Selective Saturation (CHESS)
effects
(WET)
'27.
126
method known as water suppression enhanced through T1
Acquisition
parameters
included
weighted
k-space
sampling
3
TR/TE-1700/135(144) ins, NA=3, nominal resolution lxlxl.4 cm . First- and second-order
shimming was performed automatically, followed by manual adjustment. Data selected for
analysis had a typical Full Width at Half Maximum (FWHM) in the range of 20Hz for the water
line.
The MRI protocols used conventional sequences (Ti, T2, FLAIR, post-Gd TI, volumetric postGd image) and dynamic sequences (DCE, DSC, DTI), as reported in Batchelor et al.
27,113
(see the
details in Appendix A).
DataAnalysis
57
For 11 out of 31 patients, MRS quality was inadequate to reliably detect distinct signals from the
metabolites in the tumor. In some of these patients, MRS quality was compromised by tumor
location near the skull; because in these cases shimming could not be adequately performed, the
signal was considerably contaminated by fat (5 of 11 patients). Additionally, in some patients,
marked necrosis in the lesion caused indistinguishable peaks in the spectra (8 of 11 patients).
Those spectra were objectively excluded from the data before further processing to ensure
reliable analysis. The spectra obtained from 20 of the total group of 31 subjects were included in
quantitative measurements.
We analyzed the spectroscopic raw data using LC Model 6.1 software (Provencher, Ontario, CA
'2),
with a manual script written in Matlab. The spectra were grouped in three regions of interest
(ROIs), defined by the corresponding Ti-weighted post-contrast images at baseline for:
(1)
enhancing tumor (ET), (2) non-enhancing surrounding tumor (peritumoral tissue) (FI'), and (3)
normal tissue on the contralateral side of tumor (cNT). The location and numbers of the voxels in
each ROI were serially consistent across all time points, although there were changes in the
intensity of enhancement as a consequence of treatment. To accurately assess tumor metabolism,
the voxels in the enhancing tumor were selected so as to avoid areas of necrosis, hemorrhage,
calcification, cysts, or ventricles. Only fitted spectra with standard deviation (%SD) lower than
25%, per Crame'r-Rao lower bounds automatically provided by the LC model, were accepted.
There was no subjective spectral apodization. The concentrations of all metabolites were
normalized to the normal side creatine concentration (norCre).
We examined the changes in metabolite concentrations during treatment by analyzing the ratio of
NAA to Cho and the ratios of NAA and Cho to normal side Cre (norCre). Typical spectra (as
shown in Figure 4) demonstrate that the NAA peak is higher than the Cho peak in normal tissue,
whereas the ratio is reversed in tumor, i.e. Cho peaks above NAA.
Changes in the MRI parameters were additionally analyzed (see the details in Appendix B), and
are displayed in the supplementary data. We assessed the vascular indexes by analyzing changes
in the contrast-enhanced Ti-weighted tumor volume (CE-Ti), vessel size (VS), and K.(in this
non-flow-limited state, assumed to mainly represent permeability, P) within regions of
enhancement. We quantified the water-related indexes, the functional consequences of vascular
normalization, using three different techniques that indicate hydration level. We measured: 1) T2weighted abnormality fluid-attenuated inversion recovery (FLAIR), 2) trace apparent diffusion
58
coefficient of water (ADC), and 3) extracellular extravascular space fraction (Ve), within regions
of enhancement. We also derived the absolute TI relaxation time constant values from variable
flip angle TI mapping sequences.
We analyzed the MRS/MRI data in relation to overall survival (OS), and based on the six-month
survival threshold, categorized all patients as 'high overall survival' or 'low overall survival'
responders. Metabolite ratios on days 1, 28, and 56 were compared with baseline ratios.
We computed Student's t-test p-values against the null hypothesis, which assumes no change in
metabolite ratios during treatment. The changes in MRI parameters (i.e., CE-Ti, VS, P, FLAIR,
ADC, and V) were analyzed in a similar way. Statistical significance determined by Student's
paired t-test was accepted at a confidence level of 0.95 (* p<0.05). We performed an ROC
statistical analysis to determine how predictive the MRS measurements were of 6-month survival.
Numerical data were presented as average ± one SD. The number of subjects included in the
analysis at each time point is given in Table S1 (Supplemental Data).
No corrections were made for Ti or T2 , or for possible variations in water concentration between
normal and tumor tissues. Our data analyses are strictly semi-quantitative, as routine clinical
studies do not allow for data acquisition to correct for metabolite and water relaxation. In addition,
we have assumed tissue water concentration in the tumor is similar to that in normal brain tissue;
hence, we calculated only the apparent metabolite concentrations.
59
o
NAA
4
3
2
1[ppm
4
3
2
1 [ppm]
Figure 4 Three regions of interest (ROIs) were defined on the corresponding T1-weighted postcontrast images: (1) enhancing tumor (red voxels), (2) non-enhancing surrounding tumor - i.e.
peritumoral tissue (blue voxels), and (3) normal tissue on the contralateral side of tumor (green
voxles). To obtain an accurate assessment of tumor metabolism, the voxels in enhancing tumor
were selected by avoiding areas of necrosis, hemorrhage, calcification, or cysts.
Typical MRS spectra were obtained from contralateral normal tissue (left) and enhancing tumor
(right). These demonstrate an NAA peak higher than the Cho peak in normal tissue, while the
ratio is reversed in the tumor.
60
5.3. Results
Table 2 shows the averaged values of three metabolite ratios (i.e., NAA/norCre, Cho/norCre, and
NAA/Cho) with standard deviations, the coefficients of variation, and p values tested by student
t-statistics between two pre-treatment visits in three ROIs. Relatively small mean differences
were observed between two baselines, with moderate but acceptable coefficients of variation (<
30%).
Figure 5 demonstrates a representative example of serial T1 post-contrast MR images and raw
spectra in one representative voxel (denoted by the blue-lined box) of the enhancing tumor region
during the time-course of treatment. The spectra display dynamic changes of each metabolite's
peak in the range of 0.5-4 ppm.
Figure 6 shows the changes in the NAA/norCre, Cho/norCre, NAA/Cho ratios relative to
pretreatment values, as well as lipid and lactate levels normalized by norCre, averaging across all
eligible patients.
The primary metabolic index in Figure 5.3a, NAA/Cho, provides a combined picture of the most
commonly used diagnostic criterion of metabolic changes for some types of tumors
83,129.130.
Many
studies have reported lower NAA/Cho ratio in tumors (compared to normal tissue) due to
decreased levels of NAA and/or increased levels of Cho
such findings are frequently
"131"133;
interpreted as resulting from the replacement of normal brain tissue by cancerous tissue. Though
averaged, NAA/Cho in both enhancing tumor and peritumor regions showed no significant
change until 28 days; there was significant increase between days 28 and 56 (p-0.01), then a
subsequent decrease. In the contralateral normal tissue, NAA/Cho was relatively constant.
As illustrated in Figure 3b, the ratio of lipids and lactate (including all lipid peaks in the range of
0.5-2 ppm) in enhancing tumor versus Cre on the contalateral normal side (norCre) decreased
significantly on day 56. Like the other metabolites, (lipids and lactate)/norCre was relatively
stable in the contralateral normal tissue.
Figures 5.3c and 5.3d show the individual behavior of the metabolites normalized by Cre in the
contralateral tissue (norCre). Figure 5.3c illustrates a sharp increase in NAA/norCre in the
enhancing tumor after a single dose of cediranib. The increase until day 56 (p=0.02), at which
61
time point the value began to decrease until the end of the study (p=0.04). In the peritumoral
region, NAA/norCre increased until day 28, and remained relatively constant close to the normal
value (i.e., 1.5) until day 112 (p=0.04).
In contrast, Cho/norCre (Figure 5.3d) in the enhancing tumor showed a different pattern: an
increase up to day 28 (p=0.03), a decrease from 28-56 days, then no change until the end of the
study (day 112). The decrease in Cho reached statistical significance (p=0.047) between days 28
and 56. A similar trend was found in the peritumoral region. In the contralateral normal tissue,
both NAA/norCre and Cho/norCre remained relatively constant.
We also analyzed the changes in the MR parameters relative to baseline for the same subset of 20
patients; for reference, results are shown in Figure S1 (Supplementary Data).
The MRI data from the subset of patients from whom we also acquired analyzable MRS data
were similar to the MRI findings of others in the whole 31-patient sample
3.
In both the larger
data set of 31 patients and the subset of 20 patients from whom we acquired MRS data, the
volume of contrast-enhanced tumor (CE-Ti) decreased until day 28 and thereafter began to
increase. An abrupt and substantial decrease in K''
(mean - -70%) was noted immediately after
the first dose of cedirinib (day 1). The relative tumor vessel size also decreased until day 28, and
began to increase after day 28. We observed sustained decrease in vasogenic edema,
demonstrated by reduced FLAIR lesion volumes, ADC, and V, for the duration of the therapy.
These findings suggested a high probability of antipermeability effects of cedranib until day 28.
We analyzed MRS/MRI findings in relation to patients' overall survival times, based on the sixmonth survival threshold. Early post-treatment time points (i.e., days 1, 28, 56) may be the most
important for treatment management because early indications of therapeutic outcome provide
better opportunity to optimize therapeutic intervention and improve survival ".
As shown in Figure S2 (Supplementary Data), the MRS data indicated no significant difference
in the ratios of the metabolites, including NAA/norCre, Cho/norCre, NAA in tumor/NAA in the
contralateral normal tissue (tumNAA/norNAA), and Cho in tumor/Cho in the contralateral
normal tissue (tumCho/norCho); similarly, the group differences in MRI measurements of 'high
overall survival' and 'low overall survival' responders were considered as having no significant
effect. (Figure S3 in Supplementary Data). However, NAA/Cho (Figure 7), the most
62
commonly used clinical MRS measure for discriminating normal and abnormal tissues 8, notably
showed an increase in the 'high overall survival' group (15%, 9%, 40% with p<0.05 on days 1,
28, and 56, respectively), while showing a decrease in the 'low overall survival' group (- 12%, 10%, -20% on days 1, 28, and 56, respectively). Based on this finding, we performed ROC
analysis to determine the probability that NAA/Cho predicts 6-month survival. In Table 3, the
values of an area under the ROC curve (AUC) and p-values at early time points, particularly days
28 and 56, demonstrated the high possibilities (74% and 95%) and the significances (0.02 and
0.01).
We compared the relative changes in the ratios of the three metabolites before and after one dose
of cediranib to the changes in the absolute values of norCre and the TI relaxation time constant in
Figure S4 (Supplementary Data). The comparison showed subtle changes in norCre and TI
time constant after one dose, confirming that changes in NAA/norCre are independent of norCre
and T1 changes.
63
Table 2 Mean and standard deviation of NAA/norCre, Cho/norCre, and NAA/Cho on day -5 and
day -1 for all the patients; their coefficients of variance and p values between two baselines; in
three ROIs
Standard
Day -5
Deviation
Day -1
Standard
Coefficients
p values
Deviation
of Variance
(T-test)
NAAlnorCre
Tumor
0.77
0.33
0.77
0.23
0.27
0.66
Periphery
1.17
0.29
1.22
0.45
0.22
0.51
Normal
1.65
0.21
1.62
0.19
0.10
0.99
Tumor
0.33
0.11
0.36
0.11
0.32
0.50
Periphery
0.33
0.09
0.35
0.11
0.25
0.57
Normal
0.35
0.06
0.35
0.08
0.08
0.38
0.84
2.40
0.75
0.21
0.75
CholnorCre
NAAICho
Tumor
Periphery
3.78
0.94
3.62
1.07
0.09
0.98
Normal
4.98
1.00
4.99
1.10
0.09
0.51
64
Ti-weighted
Post -Contrast
Images
MR Spectra
in Tumor
3
2
1
[ppm]
3
2
1
[ppm]
3
2
1
[ppm]
3
2
1
[ppm]
Figure 5 Serial T1 post-contrast MR images and raw spectra in one representative voxel (bluelined box) of enhancing tumor region in the time course of treatment. The spectra exhibit the
dynamic changes of each metabolite's peak in the range of 0.5 - 4 ppm at every time point of
treatment.
65
b) (Lipids + Lac)/norCre
a) NAA/Cho
-+
180 -Periphery
Tumor
Normal
-*--Tmor
riphery
g4;W-rmal
3.53
et
Anl
60,
4-
140-
act
An
2.5
2
1.5
1120
1
100
80
Fre
n=9
n=2
n 20 n=20
56
28
1
112
0.5
n 20 n=20
Pre
1
Study Days
Tumor
a- Periphery
*- Normal
'ect
*-
ZI180 160
E
9140-
140-
9120-
120
~100
100
An
I
n::21
Pre
112
d) Cho/norCre
-- Tumor
"-Periphery
Normal
160 .
80 -
n=9
28
Study days
c) NAA/norCre
d180 -
n=20
!0
1
n=20'
r6,3
28
56
n=-9
112
n 20 n=20
80
Pre
Study Days * Student's paired t-test p< 0.05
1
n=20
28
112
Study Days
Figure 6 Averaged MRS changes over all eligible patients relative to pretreatment values (%).
a) NAA/Cho; b) (Lipids and Lactate)/norCre; c) NAA/norCre; d) Cho/norCre;
The number of the eligible patients at each time point is provided under each data point.
Numerical data are presented as average ± one SD. An asterisk (*) on the data point designate
statistical significance at a confidence level of 0.95 (* p<0.05) with Student's paired t-test.
66
NAA/Cho in tumor
Dayl
Day28
Day56
o-O80S60-
4020!o
0-
>-20-
-40 J
High-OS (n=13)
M Low-OS (n=7)
Figure 7 the relative changes (%) in NAA/Cho separately grouped by the patients' overall
survival (OS) periods based on six-month survival threshold at the early time points posttreatment (i.e days 1, 28, 56) in the enhancing tumor region.
Table 3 Area Under the ROC curve on early time points (i.e. 1 day, 28 day, 56 day) to determine
the prediction of NAA/Cho to 6-month survival
NAA/Cho
Iday
28day
56day
AUC
0.68
0.74
0.95
(95% CI)
(0.65-0.72)
(0.71-0.78)
(0.91-1.00)
P value
0.15
0.02
0.01
67
5.4. Discussion
In this clinical study we sought to identify metabolic changes in rGBM, using MRS to distinguish
the changes induced by cediranib treatment. We observed elevated choline, lactate, and lipid
peaks, with very low NAA peak, in enhancing lesions as well as a reverse metabolite profile in
contralateral normal tissue at baseline. The mean values of NAA/Cho were 2.4 in the enhancing
tumor and 5.0 in normal tissue. These results mirror the classic patterns of metabolite peaks seen
in high-grade gliomas and the mean values that have been measured in other published reports
so03,13s5,136. Our results also confirm the ability of MRS to evaluate tumor response to treatment
83,3,141.
Our results both extend earlier studies to track metabolic changes induced by an
antiangiogenic agent in tumor tissue, and report several new findings.
The first new observation is the consistency of the NAA/Cho ratio with increased concentration
of both Cho and NAA in tumoral as well as peritumoral regions during the vascular normalization
window of 28 days ". One interpretation of these findings is that tumor cells are not directly
killed during the initial normalization window, and the marked changes in tumor enhancement
observed in conventional MRI reflect antivascular effects of the antiangiogenic drug. This
interpretation is compatible with preclinical results reported
114.
The decrease in tumor size and
the consequential shift in brain seen until one month after treatment initiation might reasonably
prompt one to conclude that NAA/norCre and Cho/norCre increases are attributable to partial
volume effects. A statistically significant decrease in hydration level (i.e., vasogenic edema, as
seen by ADC) during one month may also account for these changes.
The second observation is a significant increase in NAA/Cho with a significant reduction in Cho
and an increase in NAA after 28 days. This finding suggests that cediranib has a direct effect on
cellular metabolism in rGBM patients-an effect that is temporally separated from its
antivascular effects and distinct from preclinical models of cediranib-possibly due to the longer
survival times seen in humans compared to animal models of GBM. Further evidence of this
direct metabolic effect is supported by a significant decrease in observed lipids and lactate after
day 28; it has been previously shown that the spectra from active glioblastoma contain elevated
peaks of lipids
80".
Snuderal et al. observed reduced cellular density in the central area of the
tumor in the autopsies of five cediranib-treated patients included in our study population. This
morphological finding is consistent with the metabolic changes we detected. Also of note is that
68
the delayed antitumor effect associated with antiangiogenic treatment has also been reported in
other tumor types
142143 .
Interestingly, ADC in MRI showed a decrease, primarily
because of the significant
antipermeability effect of cediranib, overwhelming its cytotoxic effect, as an increase in ADC has
been shown to correlate with cell-killing mechanism for cytotoxic therapies. At baseline the
value of ADC was already high, and after edema greatly reduced, ADC dropped to a normal level
especially within 28 days, indicating a window of vascular normalization. However, between 28
and 56 days, there was no significant decrease in ADC; in fact, we observed a slight increase in
the responding group, which was likely related to the cytotoxic mechanism of cediranib.
Therefore, considering the different mechanisms of antiangiogenic and cytotoxic therapies, there
would not be a complete discrepancy between ADC and 1H-MRS.
The trend we observed in the MRS data was reversed after day 56, consistent with the general
clinical course of tumor recurrence and the eventual death of the patients. These findings might
imply that while cediranib does have direct effects on metabolism in some tumor cells, those cells
that survive despite blocked angiogenesis are eventually able to continue to grow.
A third observation in our study is the high probability of NAA/Cho to predict 6-month survival
of rGBM patients treated by cediranib, as determined by ROC analysis. The changes in NAA/Cho
illustrated in Figure 7 showed positive values in 'high overall survival' responders compared to
negative values in the 'low overall survival' group. An ROC analysis of NAA/Cho showed high
significances on day 28 (p=0.02, AUC=0.74) and day 56 (p=0.01, AUC=0.95). Together these
data might imply that it is the critical time frame between 28 and 56 days that discriminates the
tumor response to this antiangiogenic agent. This finding suggests that NAA/Cho has good
correlation with tumor responses for predicting six-month survival on the antiangiogenic
treatment, reflecting a combined picture for the opposite changes of two primary metabolites.
We acknowledge that this study is limited by its small sample size, and more importantly, by our
still-incomplete understanding of the correlations between MRS findings and tissue morphology.
The conventional interpretations of the MRS findings in glioblastoma were generated primarily in
the pre-antiangiogenic era. Although a direct antitumor effect is the interpretation most consistent
with our MRS findings in this study, we cannot at this stage rule out other possible interpretations,
and additional, larger sample-size studies are warranted.
69
This prospective study provides preliminary evidence that cediranib elicits direct metabolic
effects in rGBM; traditionally such findings have been interpreted as antitumor effects resulting
from vascular normalization based on the dynamics of the predominant brain metabolites. Our
data also suggest that with further technical advances; early changes in metabolites detectable by
'H-MRS might be able to serve as imaging biomarkers, to predict treatment response in patients
with recurrent malignant glioblastomas. NAA/Cho changes in enhancing tumor tissues suggest
that anti-VEGF therapy not only has an antivascular effect, but that such effect modulates tumor
and brain tissue both early and late in the disease process. These findings, if confirmed in larger
studies, could shed further light on the mechanism of action of this new class of antiangiogenic
agents, and potentially even be used to make treatment management decisions.
70
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74
5.5. Appendix A. MR image acquisition
Each scanning session in MRI protocol consisted of the following sequences:
1. Scout: The AutoAlign method of producing scout images was used to improve scan-to-scan
reproducibility. Briefly, this method acquires two low-resolution whole-head scans (2.5 mm
isotropic voxels) at different flip angles within 46sec, and uses a computer algorithm to compare
the current location of the head with a predefined atlas. This localization is then used to ensure
that the slice prescriptions are identical between scan sessions, even across many months.
Imaging time: 46sec.
2. T2-weighted images: A single-slab, three-dimensional, T2-weighted turbo-spin-echo sequence
with high sampling efficiency (SPACE) was used at high resolution. Specific imaging
parameters: 0.9 mm isotropic, 192 slices, 256x256 matrix, 24cm FOV, TR 3200ms, effective TE
494ms. Imaging time: 4min 30sec.
3. Fluid Attenuated Inversion Recovery (FLAIR) images: Axial fluid-attenuated inversion
recovery images were acquired with TR 10,000ms, TE 70ms, and 5mm slice thickness, 1mm
interslice gap; 23 slices, 384x3x512 matrix. Imaging time: 3min 2sec
4. Ti images: Axial images were obtained prior to the injection of contrast. TR 600ms, TE 12ms,
5mm slice thickness, 1mm inter-slice gap, 0.45mm in-plane resolution; 23 slices, 384x3x512
matrix. Imaging time: 1min 59sec.
5. Dynamic contrast-enhanced(DCE) images: This is a series of acquisitions of a 50.6mm thick
slab consisting of 20 slices. 2.1mm slice thickness, 0.4mm inter-slice gap, using a fast gradient
echo technique (TR 5.7ms, TE 2.73ms). Data to allow computation of a T1 map of the tissue of
interest are initially created using five different flip angles (2, 5, 10, 15, 30). Then, the same slab
of tissue is sampled with a 10 flip angle every 5.04s for 252s (50 time points), and 0.1 mMol/kg
of Gd-DTPA was injected 52s after the beginning of the acquisition at 5cc/s. Imaging time: 4min
l2sec.
75
6. Diffusion-weighted imaging (DTI): 60 slices of twice-refocused echo-planar diffusionweighted images were acquired with TR 7500ms, TE 84ms, and a b-value of 700s/mm2 in 42
directions as well as 7 low b-value images (b=Os/mm2) to allow reconstruction of the diffusion
tensor at each voxel. Resolution was 2mm isotropic, with a 128x3x128 matrix. Imaging time:
6min 30sec.
7. Dynamic susceptibility contrast imaging (DSC): A 75mm slab of tissue was imaged using a
dual-echo, combined gradient-echo, and spin-echo echo planar sequence to enable relative vessel
size mapping. This sequence acquires two images after each 90 RF excitation: a gradient echo
image (TE 34ms) and a spin echo image (TE 103ms); each image had 1.7mm in-plane resolution
and 5mm through-plane resolution (128x3x128 matrix). There was a 2.5mm inter-slice gap and
10 slices. 120 blocks of images were acquired, with a block acquired every 1.33s. 0.2 mmol/kg of
Gd-DTPA was injected at 5cc/s after 85s of imaging. Imaging time: 2min 45sec.
8. Post-contrast Ti-weighted imaging: Axial Ti-weighted images were acquired exactly as
precontrast, as described above. In addition, a 3D magnetization prepared rapid gradient echo
(MP-RAGE) volumetric acquisition was performed, with 1 mm isotropic voxels, TR 2530ms, TE
3.5ms, 256x3x256 matrix, 176 slices. Imaging time: 6min 6sec.
76
5.5._Appendix B. MR image analysis
1. Volumetrics
Enhancing lesions and areas of T2 abnormality on FLAIR images were quantitatively analyzed
by an experienced neuroradiologist blinded to the order of the scans and treatment status of the
patients. The lesions were outlined using a volumetric approach described previously that
includes outlining each enhancing voxel on post-contrast scans and then summing the voxels to
calculate an overall lesion volume.
2. Map Synthesis: Blood Volume, Blood Flow, and Relative Vessel Size Maps
Relative cerebral blood volume of larger vessels (gradient echo images) and smaller vessels (spin
echo images) as well as cerebral blood flow were calculated using a standard deconvolution
technique, with blood volume corrected for leakage of the contrast agent across the blood-brain
barrier. These maps are relative and therefore unitless.
Relative vessel size maps were created using the ratio of delta-R2* to delta-R2, according to
published approaches. This provides a voxel byvoxel estimate of the relative radius of the
microvasculature, with larger vessel diameter corresponding to brighter signal.
3. Apparent Diffusion Coefficient Maps
Maps of apparent diffusion coefficient (ADC) were created from the low and high b-value images
using
custom-written
software
implementing
the
standard
Steskjal-Tanner
diffusion
approximation. This provides an estimate of the relative water self-diffusion or water mobility on
a voxel-by-voxel basis; higher values represent a greater degree of water mobility, and the units
of these maps are in area/time, typically mm2/s.
4. PermeabilityMaps
Dynamic contrast-enhanced MRI data were processed using custommade software written in
Matlab (MathWorks, Natick, MA), following standard published approaches, including maps of
K"
(corresponding roughly to wash-in rates of the contrast agent) and v (extracellular-
extravascular volume fraction). These references provide highly detailed descriptions of these
parameters and their biophysical meaning. K'
does not fully correspond to permeability in each
regime, but it is related to the permeability-surface area product of the capillary bed in non-flowlimited situations.
77
5. Synthetic Map Analysis
The outlines generated in the volumetric analysis of the second baseline (day-1)
coregistered to the synthesized maps (CBV, CBF, vessel size, K',
were
ADC) and median values
across the entire enhancing lesion (for CBV, CBF, vessel size, and K'") or entire FLAIR lesion
abnormality (for ADC) were computed. As all of the values other than ADC were considered
relative rather than absolute, maps were normalized to each other using an unaffected area of gray
and white matter typically located distantly, such as in the contralateral hemisphere.
78
Supplementary Data
Table S 1 Number of subjects included in the analysis at each time point
Day -5
Day -1
Day I
Day 28
Day 56
Day 112
Total Patient Number
20
20
20
20
13
9
High Overall Survival Size
13
13
13
13
11
9
Low Overall Survival Size
7
7
7
7
2
0
79
MRI changes relative to pretreatment values
(%)
a) Vascular Indexes
CE-T1
-
P -*-
VS
100
80-
40
20n=20
n=20
n=13
n=9
Pre 1
28
56
Study Days
112
0n
0
b) Water-related indexes
I
-100
---
edema ---
ADC --
Ve
-
8060> 40200i
n=20
n=20
n=13
n=9
28
56
Study Days
112
0
Pre 1
Figure S 1 Mean MRI changes over the same subjects as those of MRS relative to pretreatment
values (%). a) Top: the changes of the MRI indexes demonstrating the vascular effects; b)
Bottom: the changes of the MRI indexes demonstrating the water-related effects
80
MRS
a. High Overall Survivors
Dayl (n=13)
0
100
-
80
-
Day28 (n=13)
* Student's paired t-test p< 0.05
60Cz
E
2
40
-
20
-
Day56 (n=11)
TT
*
T
T
*
11
0-
CD
C
CU
-n
-20
-
-40
-
tumNAA/norCre U tumCho/norCre
E tumNAA/norNAA E tumCho/norCho
0
E tumNAA/tumCho
b. Low Overall Survivors
Dayl (n=7)
Day56 (n=2)
Day28 (n=7)
100 80-
-
T60
TT
Cu
o 40E
T
~200-
o -20
-40
E tumNAA/norCre
* tumNAA/norNAA
* tumCho/norCre
0 tumCho/norCho
E tumNAA/tumCho
Figure S 2 Averaged MRS findings separately grouped by the patients' overall survival (OS)
times based on six-month survival threshold at the early time points post-treatment (i.e days 1, 28,
56) in the enhancing tumor region.
The relative changes (%) of NAA in tumor /norCre (tumNAA/norCre), Cho in tumor /norCre
(tumCho/norCre), NAA in tumor /Cho in tumor (tumNAA/tumCho), NAA in tumor /NAA in the
contralateral normal tissue (tumNAA/norNAA), and Cho in tumor /Cho in the contralateral
normal tissue (tumCho/norCho) in MRS with respect to pre-treatment (day -1) are presented
separately for the high and low overall survival populations.
a) the changes of the predominant metabolites' ratios in high-OS;
b) the changes of the predominant metabolites' ratios in low-OS;
An asterisk (*) on the data point designate statistical significance at a confidence level of 0.95 (*
p<0.05) with Student's paired t-test.
81
Low Overall Survivors
b) MRI (Vascular Indexes)
High Overall Survivors
a) MRI (Vascular Indexes)
Days
28
1
Days
56
28
0-
0 0
-20O-40-
E
E
0
0
-60 -
'
1
Cu
C
-80-
0
-100 -*CE-T
1
28
EO-40-
-100-
-
-60
-
-80
-
E
0
*
ADC
N Ve
-20-
.
U edema
,**
C-L
Days
56
0
**
e
-60c -80-
-40
0
0
C
-
-_
---I
*
P MVSI
*
d) MRI (Water-related indexes)
00__O -20-
-20
-100 - 0 CE-T1
*
c) MRI (Water-related indexes)
Days
,
56
-40-
1
28
56
B!'!p'LI
**
-60-
C
-80-100-
* edema
ADC
0 Ve
* Student's paired
t-test p< 0.05
Figure S 3 Averaged MRI findings separately grouped by the patients' overall survival (OS)
times based on six-month survival threshold at the early time points post-treatment (i.e days 1, 28,
56) in the enhancing tumor region.
The relative changes (%) of MRI parameters with respect to pre-treatment (day -1) are presented
separately for the high and low overall survival populations.
a) the changes of the MRI indexes demonstrating the vascular effects in high-OS;
b) the changes of the MRI indexes demonstrating the vascular effects in low-OS;
c) the changes of the MRI indexes demonstrating the water-related effects in high-OS;
d) the changes of the MRI indexes demonstrating the water-related effects in low-OS;
An asterisk (*) on the data point designate statistical significance at a confidence level of 0.95 (*
p<0.05) with Student's paired t-test.
82
a) High-OS (n=13) in ET
" Cho/norCre
U NAA/norCre
0 NAA/Cho
50
40 -
b) Low-OS (n=7) in ET
T1
30
20
*-
r T
* NAA/norCre * Cho/norCre
* NAA/Cho
" norCre
40
MT1
I
0-
30
20
I
0
50
" norCre
E 10
E 10
0C-
I
C
T
111111F
C-10
C-10
-20
*
-30
Student's paired t-test p< 0.05
Day 1
-30
a) All Patients (n=20) in ET
50
-
M NAA/norCre
NAA/Cho
TI
40-
Day 1
b) All Patients (n=20) in cNT
* Cho/norCre
* norCre
5040
-
* norNAA/norCre U norCho/norCre
* norNAA/norCho M norCre
MT1
30 -
30-
LIT
20E 100-
g20 -
0
E 10
0
0
2-10 -
I
T
-I-
Tr
2-0
-20-30
I
-20
-20-
Day 1
-30
-
Day 1
Figure S 4 The relative changes in the ratios of three metabolites before and after one dose of
cediranib, compared to the changes in the absolute value of norCre and the TI relaxation time
constant estimated from various filp angle TI mapping sequences.
a) the changes in enhancing tumor in high-OS (n= 13);
b) the changes in enhancing tumor in low-OS (n=7);
c) the changes in enhancing tumor in all eligible patients (n=20);
d) the changes in contralateral normal tissue in all eligible patients (n=20);
Notably, the absolute norCre and T 1 changed very slightly.
83
84
Chapter 6
Oxidative Metabolism Biomarker:
A Significant Increase in Oxygen Consumption Rate in Hyperoxia
in Glioblastoma
6.1. Introduction
Adenosine 5'-triphosphate (ATP) is generated in normal cells through one of two critical
pathways: oxidative phosphorylation in the mitochondria and glycolysis in the cytoplasm. All
cells use both pathways, but rely overwhelmingly on oxidative phosphorylation, switching to
glycolysis at times of oxygen deprivation. However, in 1930, Otto Warburg observed a curious
but common property of invasive cancers: that cancer cells metabolize glucose into lactate even
in the presence of oxygen-a process referred to as "aerobic glycolysis" or "the Warburg effect"
39
Warburg originally hypothesized that cancer cells develop a defect in the mitochondria that leads
to impaired aerobic respiration, and a subsequent reliance on glycolytic metabolism; and that this
glycolytic shift causes such cells to become cancerous. Although evidence for the Warburg
hypothesis has been scant, the experimental observations of increased glycolysis in cancer cells,
even when oxygen is present, have been repeatedly verified.
In the 20* century, many biochemists, including Craig Thompson 36, reconsidered the Warburg
effect. Thompson agreed that the Warburg effect is a fundamental property of cancer cells, not
simply a byproduct of the cells' transformation into cancer. He developed a new model that links
the Warburg effect to mutations in the signaling pathways that govern glucose uptake into cells
with intact mitochondria. Thompson's model, therefore, raises the question of whether glycolytic
shift occurs independent of hypoxia, such that the oxidative pathway is preserved in cancer cells.
Measurement of the cerebral metabolic rate of oxygen (CMRO2) can be used to investigate
oxidative changes in cells under different baseline conditions. Davis et al.
6
introduced a
formalism to calculate CMRO 2 based on the deoxyhemoglobin (dHb) dilution model; this model
85
used CO 2 breathing to calibrate the BOLD signal by inducing a global increase in cerebral blood
flow (CBF)
'".
Wu et al. have also proposed a modified CMRO2 model; this one, taking into
account the contributions of arterial-venous blood volume and involving a non-steady state
determination of CMRO 2
'45.
Subsequently, Hoge et al., Mandeville et al., and others
'46,147 have
reproduced and extended Davis's findings. Though the hypercapnia-calibrated technique has been
widely adopted for investigating CMRO 2, the use of CO 2 has various drawbacks including a
potential influence on CMRO 2 "4, a definite correlation with the onset of breathlessness 149
potential intolerability in distressed subjects, and a large potential variability in the calculated
calibration parameter (i.e., M - the maximum theoretical BOLD signal change) (Hoge 1999). The
recent Chiarelli's study 36 has introduced the hyperoxia-calibrated model (breathing of 02enriched air) as an alternative technique for calibration of the BOLD-CBF relationship, requiring
BOLD and CBF signal and end-tidal 02 measurements.
Although several CMRO 2 measurement approaches have been well established for investigating
the neuronal activity in healthy brain, no studies have been conducted to apply these CMRO
2
models to brain diseases such as tumor under physiologically perturbed states. Some have
proposed that moderate and transient perturbations in arterial oxygen partial pressures (PaO 2) do
not change CMRO 2 in normal tissue
15s;
however, it is not clear if the same is true in the case of
tumors. Approaches such as needle oxygen electrodes, optical reflectance, MRI, and nuclear
medicine techniques
1521
have been proposed as a means to derive relative CMRO 2. Among
these techniques, MRI is unique in its ability to non-invasively quantify physiologically relevant
hemodynamic parameters (i.e., BOLD, CBF), providing excellent structural resolution for
evaluating CMRO 2. Functional MRI (fMRI) studies based on BOLD contrast have great potential
for assessing the changes in deoxyhemoglobin in tumors, particularly for assessing interventions
designed to alter tumor oxidative metabolism
'5.
Arterial spin labeling (ASL) offers great
efficiency as an MRI tool for imaging CBF at reasonably high spatial and temporal resolution 155
Moreover, the use of different MRI techniques in concert-for example, simultaneous BOLD and
ASL measurements -facilitates
simultaneous detection of BOLD and perfusion
6356,157.
This
approach also provides relatively high CBF contrast, minimizes intra-trial variation in CBF and
BOLD responses associated with sequential measurements of these parameters, and enables
quantitative calculation of CMRO 2.
In this study, we employed the novel simultaneous BOLD-ASL MR technique to capitalize on
previous observations of BOLD and CBF responses to hyperoxia in healthy volunteers and,
86
furthermore, extend these investigations to newly diagnosed glioblastoma (nGBM) patients. At
present, no other comprehensive investigation of oxidative metabolism and cerebrovascular
activity in nGBM patients under gas modulation has used a multi-parametric MRI technique. The
specific goal of this study was to evaluate CMRO 2 changes in nGBM patients in response to
hyperoxia. Our results suggest that the simultaneous BOLD-ASL technique produces results
consistent with previous findings in healthy volunteers, and provides valuable information to
improve understanding of oxidative metabolic responses to hyperoxia in nGBM.
87
6.2. Methods
Subjects Recruitment
Ten patients (age 53.1±9.05) with newly diagnosed glioblastoma (nGBM) were recruited. Every
patient underwent surgical resection before enrolling in the imaging study. Ten healthy volunteers
(age 42.2±12.1) were also examined using the same protocol. Informed consent was obtained
from all healthy subjects and nGBM patients participating in the protocol, which was approved
by the Institutional Review Board (IRB) of the Massachusetts General Hospital.
Data Acquisition
MRI studies were performed using a 3T MRI scanner (TimTrio, Siemens, Malvern, PA) equipped
with a 32-channel head coil. The simultaneous BOLD-ASL sequence was developed based on a
pulsed ASL sequence, applying the QUIPSS II technique for pre-saturation and PICORE tagging
method followed by single-shot, gradient echo (GE) echo planar imaging (EPI) acquisition with a
64x64 matrix. 300 paired images were acquired, alternately with and without tagging, using
TI1/TI2 =700/1400ms. 11-slice images, 8mm in thickness, were acquired using the optimized TE
and TR for both BOLD and flow (TR/TE=2000/19ms, FOV = 220x220 mm 2 , 6/8 partial Fourier).
Ti-weighted images in healthy volunteers and the same images with Gadolinium-DTPA contrast
agent in nGBM patients were acquired to provide anatomical details. The MRI acquisitions
followed standard protocol described in Batchelor et al. (2007)
27.
23-slice axial pre- and post-
contrast Ti-weighted images were acquired with TR/TE-600/12ms, 5 mm slice thickness, 1mm
interslice gap, 0.45mm in plane resolution, and 384x512 matrix. In addition, a 3D magnetization
prepared rapid gradient echo (MP-RAGE) volumetric acquisition was performed, with 1mm
isotropic voxels, TR/TE = 2530/5ms, 256x256 matrix, 176 slices.
Gas was administered via a specifically designed respiratory mask, according to the following
breathing paradigm: baseline room air for 2 minutes followed by 100%
02
for 4 minutes, then
washout room air for 4 minutes with 40-45L/min flow rate. Heart rate (HR) and the peripheral
oxygen saturation level (SP 0 2 ) were continuously monitored using a pulse oximeter (Invivo,
Orlando, FL).
88
DataAnalysis
Preprocessing of the raw data involved motion correction, subtraction (CBF), and addition
(BOLD) of the paired images, spatial smoothing using a 6mm kernel Gaussian filter, and general
linear modeling (GLM) using Neurolens software (MGH/Universit6 de Montr6al et CRIUGM).
The GLM analysis was performed on the time course of BOLD and CBF data sets to create
percent change maps of signals as well as student T-statistic activation maps. Output values
determined to be significant by Student's t-test (p < 0.05) were further analyzed.
To avoid bias to a particular type of activation map in healthy subjects, and to explore specific
lesions in patients, region of interest (ROI) analysis was performed to determine the average
changes in BOLD and CBF. For healthy volunteers, the whole gray matter was defined using the
segmentation in SPM (Statistical Parametric Mapping, Functional Imaging Laboratory, UK). For
nGBM patients, the data were analyzed in two ROIs: the enhanced tumor defined by the
radiologists' outlines, and normal-appearing gray matter defined by SPM-derived segmentation.
To obtain an accurate assessment of tumor metabolism, the enhanced tumor voxels were selected
to avoid areas of necrosis, hemorrhage, calcification, or cysts.
The BOLD and CBF signal change maps generated after the preprocessing step were analyzed
using in-house developed code (Matlab, Mathworks Inc, Natick, MA) to estimate the relative
cerebral metabolic rate of 02 (CMRO 2) (i.e., relative oxygen consumption rate). According to
Chiarelli et al. 65, the relationship between CBF and BOLD signals in hyperoxia, assuming
CMRO 2 / CMRO 2 lo at the unity, as neither brief nor mild hyperoxia significantly alters CMRO 2,
was derived by the following formula:
from
ABOLD
BOLDO
from Metabolism
02
CBF
[dHb]v
"+
)(
CBF [dHb]v0
=M(1(
where M=TE-ACBV0 -[dHb],
CBF
CBF
-1 )P)
[Eq. 6.1]
and where the proportionality constant and parameters with
subscript zero indicate baseline values, consistent with the definition of M in the hypercapniacalibrated model derived by Davis et al.
65
Grubb's factor (c) is 0.38 147,1ss.
P is either
1.0, in the
simplest case of extravascular signal changes around larger veins, or 1.25, when two other
effects-diffusion of the water molecules and the signal changes of the blood itself
65 1 59
,
_are
89
considered. These constants represent the effects of blood volume and deoxyhemoglobin
concentration on BOLD signal, respectively.
M values were calibrated at 0.038 from the data of healthy subjects. This M value was
comparable to the those measured by Chiarelli's hyperoxia model and Davis's hypercapnia model
in several studies, when considering the different conditions such as echo time and the magnetic
field (i.e., 0.075 in Chiarelli et al. [TE=32ms]; 0.067 in A. Lin et al. [TE=28ms]; 0.080 in Davis
et al. [TE=45ms]; 0.15/0.22 in Hoge et al. [TE=50ms]).
Using the defined M values, we re-formulized the model to calculate CMRO 2 in hyperoxia. In the
model, there are two terms that contribute to deoxyhemoglobin concentration [dHb] changes: one,
resulting from direct oxygen, and the other from metabolic changes such as CBF. The [dHb]
change triggered by metabolic change was considered in relation to CMRO 2 changes.
from Metabolism
A[dHb],
[dHb], 0
from 02
[dHb],
[dHb], 0
CMRO2
CMRO2
where,
|O
m
(1-
f
db],
M)
[dHb] o
fa
CBF
CBF
[Eq. 6.2]
ABOLD
BOLDO
The final equation was derived to calculate the relative CMRO2, by measuring the changes
in BOLD and CBF signal with the direct oxygen-induced changes in deoxyhemoglobin
concentration, as derived from the end-tidal oxygen values.
from 02
CMRO2
CMRO
2
|o
[dHb]
[dHb],o
[Eq. 6.3]
Finally, we calculated the relative CMRO 2 using this final equation, averaging the values in each
ROI.
90
6.3. Results
Physiological parameters are summarized in Table 4 for healthy subjects, and in Table 5 for
nGBM patients. During oxygen breathing, we observed a general decrease in heart rate and an
increase in oxygen saturation level, up to the maximum of 99%.
BOLD and CBF changes in healthy subjects
In healthy subjects, BOLD and CBF responses were detected primarily in the gray matter;
whereas BOLD increased, CBF decreased, as illustrated in Figure 8, which shows a T 1-weighted
anatomical image and BOLD and CBF signal change maps for a representative healthy subject.
The graphs of percent change (AS) of the BOLD and CBF signals, averaged for all ten healthy
volunteers in each ROI (Figure 9), reveal a 2% increase of BOLD signal and 2% decrease of
CBF signal in the gray matter. These results agree well with previously published data
1s6.16o-162
and are consistent with the observation of only minimal changes in oxygen consumption rate in
the face of these modest changes in input oxygen.
BOLD and CBF changes in nGBM patients
In nGBM patients, as noted above, we acquired Tl-weighted anatomical image data after
injection of Gd-DTPA contrast agent. The contrast-enhanced lesion exhibited a heterogeneous
pattern of BOLD signal changes, as demonstrated in Figure 10, which shows BOLD and CBF
signal change maps for a representative patient. Figure 11 shows the average percent change
(A S) of the BOLD and CBF signals in tumor and normal-appearing gray matter in all ten patients
compared to the same signals in healthy gray matter. Compared to the mild changes (0.8% in
BOLD and 3.6% in CBF) seen in both normal-appearing gray matter in patients gray matter in
healthy subjects, enhanced tumor exhibited a subtle increase (0.1%) in BOLD signal and a
significant increase (49%) in CBF signal. These results are comparable with those from the
preclinical study by Winter et al.
6.
One interesting observation was the reverse responses of
CBF in tumor and normal tissue; i.e., we observed that if CBF increased in tumor, it decreased in
normal tissue, and conversely, if CBF decreased in tumor, it increased in normal tissue.
These values in normal-appearing gray matter correspond well to the hyperoxia-calibrated model
in Eq. 6.1, yielding relative CMRO 2 (i.e., CMRO 2 at oxygen/ CMRO 2 at baseline) measures that
were consistent in normal tissue of nGBM patients as well as in healthy volunteers. These data
also agree with findings from previous studies
14s,1sois1
91
Table 4 Heart rate (HR) and oxygen saturation level (i.e., saturation of peripheral oxygen, SP0 2)
at baseline and at oxygen for all healthy volunteers
Subject
ID
01
02
03
04
05
06
07
08
09
10
Average
SD
HR at baseline
(beat/min)
72
62
85
90
62
67
77
52
66
88
72.1
12.63
HR at oxygen
(beat/min)
65
60
83
71
62
63
71
53
62
86
67.6
10.33
SP 0 2 at baseline
SP 0 2 at oxygen
(%)
(%)
97
96
98
97
93
95
97
96
95
96
96
1.41
99
98
99
99
98
99
98
99
99
98
98.6
0.52
Table 5 Heart rate (HR) and oxygen saturation level (i.e. saturation of peripheral oxygen, SP 0 2) at
baseline and at oxygen for all nGBM patients
Patient
ID
01
02
03
04
05
06
07
08
09
10
Average
SD
HR at baseline
(beat/min)
55
66
80
65
69
68
89
59
39
68
65.8
13.51
HR at oxygen
(beat/min)
51
64
68
62
65
63
85
55
39
57
60.9
11.98
SPo2 at baseline
SP0 2 at oxygen
(%)
(%)
96
94
97
93
95
97
95
99
98
99
98
98
99
98
96
94
95
95.2
1.32
99
98
98
98.4
0.52
92
Figure 8 Ti-weighted anatomical image [a], BOLD signal change map in hyperoxia, signal
changes (%) [b], and CBF signal change map in hyperoxia, signal changes (%) [c] for a
representative healthy subject.
6
U BOLD
MCBF
3
-3
-6-
-
I
Figure 9 Percent changes (AS) in BOLD signal and in CBF signal, averaged across all ten
healthy volunteers, in gray matter
93
Figure 10 post-contrast Ti-weighted anatomical image [a], BOLD signal change map in
hyperoxia, signal changes (%) [b], and CBF signal change map in hyperoxia, signal changes (%)
[c] for a representative newly diagnosed glioblastoma patient. Red circles indicate the tumor
region.
b.
a.
100
2.0
Fr
80
1.5
~60
9
T
1.0
I
240
20.5
S20
0.0
T-~
Patient
Tumor
-- '
Patient Health
y
GM
GM
0
-20
Pater
rumc r
Patient Healthy
GM
GM
Figure 11 [a] Percent changes (AS) in BOLD signal, averaged across all ten glioblastoma
patients, in enhanced tumor (ET) and normal-appearing gray matter, compared to the average in
all ten healthy subjects. [b] Percent changes (AS) in CBF signal, averaged across all ten
glioblastoma patients, in enhanced tumor (ET) and normal-appearing gray matter, compared to
the average in all ten healthy subjects.
94
Relative CMRO 2 in nGBM patients
After calibrating M in the model for the data we acquired using our simultaneous BOLD-ASL
MRI sequence in tumor patients and healthy subjects, we calculated relative CMRO 2 using the
36.65
conventional constants (i.e., M, a, and P) validated both by our data and by previous studies
Figure 12 shows a post-contrast Ti-weighted image and the relative CMRO 2 map (i.e., CMRO 2
at oxygen / CMRO 2 at baseline) for a representative patient. Notably, relative CMRO 2 was
significantly increased in the enhanced tumor, but remained mostly constant in the normalappearing tissues. Averaged across all ten nGBM patients, CMRO 2 increased 46% in response to
oxygen in the enhanced tumor, compared to subtle changes (2%) in normal-appearing gray matter
(Figure 13). Although responses varied depending on tumor size and location across patients, the
tumor lesions in all patients showed considerable increases in CMRO 2 in hyperoxia compared to
the gray matter of patients and healthy subjects.
Model Sensitivity
The variability in the model parameters was considered to reflect the possible modification of
these factors by the different physiological properties of a given tumor; for instance, baseline
CBV, baseline deoxyhemoglobin concentration, the relationship between CBV and CBF, and the
dynamic change in deoxyhemoglobin concentration mediated by oxygen.
We tested the sensitivity of the calculated relative CMRO 2 value to the model parameters by
from
[dHb],o directly from oxygen (i.e., [dHbl
a, P, M, and [dHb], //[dI~bljO
independently varyingindepndenty
varing
oxygen
d
,
The values assumed for each of these parameters in our standard analysis were.a=0.38, P=1.5,
from
M=0.038, and [dHb
oxygen
dHb], =0.85. The ranges of variation for a and
P (0.2
to 0.7 and 1.0 to
2.0, respectively) were chosen to adjust the sensitivity ranges employed in the previous analyses
146,163 and to reflect the findings of the earlier preclinical study by Parkard et al'
. The range of
variation for M was chosen based on physiologically plausible resting values in tumor, by
measuring CBV at baseline and [dHb] at baseline in tumor using techniques such as dynamic
from
oxygen
d ],
susceptibility contrast (DSC). The range of [dHb l[dHb]l
was defined between the value
a
eindbten
h
au
95
acquired from healthy subjects who exhibited feasible physiological responses, and the value in
the maximum, assuming no change by oxygen.
Figure 14 shows the very low sensitivity of the relative CMRO 2 to a, P, and M. The sensitivity to
from
[dHb]
oxygen
/
/[dHb],
was the modest source of model-based variation in the estimate of relative
CMRO 2. However, even in the extreme case, there was a 25% increase of CMRO 2-
96
Figure 12 Post-contrast T 1-weighted image [a] and relative CMRO 2 map in hyperoxia [b] for a
representative newly diagnosed glioblastoma patient. The red circles indicate the tumor region.
*
50
40
N 30
0
u20
10
0
Healthy GM
Patient GM
Patient Tumor
CMRO2
Figure 13 Averaged relative CMRO 2 (i.e.,
/
MRO210 ) in newly diagnosed glioblastoma
(nGBM) patients. In nGBM patients, the CMRO 2 response at oxygen increased 46% in enhanced
tumor and subtle changes in the normal-appearing gray matter compared to relative CMRO
2
measured in the gray matter in healthy volunteers. An asterisk (*) on the data point designate
statistical significance at a confidence level of 0.95 (* p<0.05) with Student's paired t-test.
97
2
1.8
81.6
Minimum
25%
31.4
1.2
1
0.5
0.6
0.7
1.6
1.8
2.0
0.05
0.06
0.07
0.95
0.85
0.75
[dHbJJ[dHb]v from 02
1.0
0.2
0.3
0.4
1.0
1.2
1.4
alpha
beta
0.02
0.03
0.04
M
0.55
0.65
Figure 14 Model Sensitivity of relative CMRO 2 in tumor to variations in a,
s,
M, and
from oxygen
[dHb]
[dHb], 0
from oxygen
[dHb]
The range were 0.2<ca<0.7, 1.O<3<2.0, 0.02<M<0.07, and 0.55<
from
/[dHb]vo
<1.0. The
oxygen
[dHb]
initial default values were c=0.38, P=1.5, M=0.038, and
/[dHb]VO
=0.85.
98
6.4. Discussion
In this study, we sought to measure cerebral hemodynamic parameters (i.e., BOLD and CBF
changes) under an important physiologically perturbed condition (i.e., hyperoxic challenge), and
to apply these data to quantitatively assess changes in oxidative metabolism in both healthy
subjects and newly diagnosed glioblastoma (nGBM) patients.
BOLD and CBF changes in healthy subjects
We observed elevated BOLD signal and slightly reduced CBF signal changes in the brains of
healthy volunteers. Our results agree with previously reported measurements
of these
physiological responses in the normal brain 36.
Although the effect of hyperoxia on the hemodynamic response is not yet completely understood,
it is generally accepted that hyperoxia slightly decreases CBF in gray matter "6. Initially, the
effect of high PaO 2 was assumed to be vasoconstrictive, as studies in both animals and humans
have shown that the cerebral blood vessels constrict during inhalation of 100% 02. Kolbitsch et al.
reported decreased relative CBF in all human brain regions except the parietal and left
hemispheric frontal gray matter during hyperoxia 165. Although some discrepant observations of
CBF responses to pure oxygen remain due to differences among species, in measurement
techniques, and in regional/mechanistic variations in baseline physiology, our study, like most
others, demonstrates a mild reduction in CBF primarily in the gray matter.
Intrinsically, BOLD signal depends on multiple hemodynamic parameters such as CBF, CBV,
baseline blood oxygenation, and cerebral metabolic rate of oxygen consumption (CMRO 2)
65,154,161.166 It has been suggested that changes in overall BOLD signal in hyperoxia are derived
both directly from the inhaled oxygen and from changes in oxidative metabolism including CBF
and the rate of 02 uptake (i.e., CMRO 2) 167. In response to hyperoxic challenge, our study showed
that BOLD signal was substantially enhanced, revealing increased blood oxygenation throughout
the healthy brain.
As a result, our measurements of BOLD and CBF in the hyperoxia-calibrated model support the
conventional assumption that hyperoxia does not change CMRO 2 in healthy gray matter.
99
Our study extends earlier studies to track hemodymamic responses to hyperoxia in nGBM
patients, and yields several new findings.
BOLD and CBF changes in nGBM patients
The first new observation was the subtle BOLD response in contrast-enhanced lesion in nGBM
patients compared to the signal responses in the gray matter of health subjects. Several preclinical
and clinical studies have employed gradient echo (GRE) imaging to monitor the hemodynamic
response to hyperoxia in tumors
'6.
In general, increases in the intensity of T2*-weighted GRE
images of tumors during 100% 02 breathing have been attributed to changes in both blood flow
and blood oxygenation. However, the preliminary studies that yielded these observations were
somewhat contradictory with respect to their divergent degree of changes, heterogeneous
distribution of MR signals, and variation in type of tumor. In contrast, the BOLD response to
inspired oxygen that we observed in tumor was much more moderate than that seen in gray matter,
indicating that more deoxyhemoglobin is produced as a result of the oxygenation metabolic
changes in tumor.
The second intriguing finding of our study was an unexpected increase in CBF in enhanced tumor.
Furthermore, we discovered the inverse relationship of CBF measured in the tumor and normal
hemisphere; i.e., we found that if CBF was increased in the tumor, it was decreased in normal
tissue (in 8 out of 10 patients), or if decreased in the tumor, it was increased in the normal tissue
(in 2 out of 10 patients). This inverse relationship implies a "stealing effect" that is accounted for
by the different resistances of abnormal versus normal vascular structure in diseased brain.
The BOLD and CBF responses we measured are comparable to those from Winter's preclinical
study ", which revealed an R, increase and R 2* decrease with elevated p0 2 in tumors when
subjects breathed 100% oxygen. We also demonstrated that the changes in BOLD signal are
consistent with CBF changes, per Chialleri's formalism, in normal-appearing tissue in nGBM
patients. This finding may, therefore, confirm that BOLD and CBF coupling remains in the
hyperoxia model, even in normal-appearing tissues in glioblastoma patients.
Relative CMRO 2 in nGBM patients and Model Sensitivity
The most remarkable finding in our study is the significant increase in relative CMRO 2 in the
enhanced tumor region. Although no previous MRI studies have been performed to derive
relative CMRO 2 under hyperoxia in glioblastoma, Xia et al. estimated CMRO 2 changes in rat
100
tumors (i.e., tumor ACMRO 2 ) under hyperoxia using near infrared spectroscopy (NIRS) in a
preclinical study
70.
Concordant with our human results, Xia's group found a consistent increase
in directly measured oxy- and deoxyhemoglobin
concentration
(A[HbO2 ] and A[Hb],
respectively) in tumor, followed by a significant increase in tumor blood flow and tumor CMRO 2
in hyperoxia.
However, we acknowledged that our CMRO2 modeling approach might not be optimized for
tumors, which have different physiological properties. Our initial approach made the simplified
assumption that the model parameters employed in normal tissue were consistent in tumor. We
then measured baseline CBV and CBF in tumor using the DSC technique with contrast,
validating that the averaged CBV in tumor was 1.14 times as high as that in gray matter, and that
the averaged change in CBV relative to CBF was mildly higher in tumor than in gray matter.
Based on these findings as well as those from the previous studies, we simulated the model
sensitivity of CMRO2 to the physiologically plausible range of each parameter.
While any
perturbations in these parameters will certainly influence the quantitative values for the
magnitude of CMRO2 changes we observed, the likelihood that such differences will modify our
fundamental observations is small, as illustrated in Figure 14.
One interpretation of our findings and the similar findings of Xia is that cancer cells appear to
increase oxygen consumption under conditions of high oxygen pressure in the blood. There have
been the diverse hypotheses on the preserved integrity of oxidative pathways in glycolytically
active tumors. Our data directly address this important controversy. By documenting the ability of
tumors to upregulate their oxidative metabolism, our results support the view of Thompson and
others who have hypothesized that mitochondrial function is fundamentally preserved even in
aggressive tumors such as GBM. Furthermore, we can relate the increased delivery of oxygen to
the tumor to the changes in its oxidative metabolism. When breathing 100%
02,
oxygen delivery
is increased by ~ 42% (this increase is attributed almost entirely to the increases in dissolved
oxygen and CBF). It is interesting to compare this figure to the changes in oxygen metabolism
revealed by our data, which showed an increase of approximately 46% in the main tumor body.
The similarity of these two values introduces the possibility that oxygen consumption in GBM is
delivery-limited; in other words, as oxygen delivery is increased, the tumor responds
proportionally in its utilization of the available oxygen. Given that these tumors are highly
vascularized, with increased CBF and, hence, oxygen delivery-as demonstrated by our DSC and
ASL data-this might seem paradoxical. Yet the distortions observed in the vascular micro-
101
architecture in these lesions " may limit absorption of oxygen at the cellular level in a way that is
distinct from overall flow-based oxygen delivery.
If this is true, it suggests that at least this type of tumor may increase glycolysis directly to
support metabolic activity stimulated by oxygen starvation, a functional hypoxia. Awash with
inflowing oxygenated blood, the tumor remains thirsty for oxygen. Evidence supporting GBM
hypoxia in actively growing regions, independent from tumor perfusion, is found in PET
FMISO data
'72.
18
F-
Alternatively, it may be that tumors have lost the ability to regulate oxygen
utilization, and/or to sense the level of oxygen pressure in the cell in order to activate the
mitochondria; that is, presented with more oxygen or higher oxygen pressure, the cells burn it
regardless of metabolic load. In this view, Thompson's concept of mutagenic changes in
glycolytic control would be extended to include the respiratory system. Both of these
interpretations may, in fact, be true.
Our results suggest that administration of pure oxygen manipulates oxygen metabolism in tumor
cells, which prompts a re-consideration of the Warburg effect and its meaning in relation to the
cascade of mutagenic effects that leads to GBM malignant degeneration.
However, we also concede that our study has some important limitations that, at this stage,
preclude a definitive interpretation of the results. First is its modest sample size. Replication of
these experiments on a broader range of patients, including patients with lower-grade lesions,
would be illuminating, and might indicate how the mutagenic changes that lead to glioma
malignant dedifferentiation alter oxidative metabolism and its response to oxygen. Second,
because the SNR of the ASL technique used in this clinical investigation was limited, we were
not able to make reliable measurements of CBF signal in white matter, and thus, we can make no
determinations on the effects seen in this tissue. Finally, and perhaps most significantly, our study
was focused on changes in oxidative metabolism, and did not directly measure baseline CMRO .
2
Understanding the denominator in our maps of changing oxygen utilization is clearly a key
parameter in understanding the broader implications of our observations. An important question
is which region was oxygen-starved to begin with? Peritumoral hypoxia would be expected to
induce angiogenic changes in the surrounding tissue, which may in turn provide both the means
and support for infiltrative extension-the hallmark of these aggressive lesions. However, it may
be that the infiltrative components of the lesions themselves account for the increased oxygen
metabolism observed, independent of any baseline drop in flow and oxidative metabolism.
102
Determining both baseline CMRO 2
73
and tissue hypoxia
172
would thus be important for better
understanding and interpreting our results. These important studies are currently ongoing.
This prospective study provides preliminary evidence of the subtle changes in BOLD signal and
increase in CBF signal in glioblastoma, as determined by a simultaneous BOLD-ASL MRI
measurement technique, under the physiological perturbation of oxygen modulation. Our data
suggest that with further careful exploration and additional model validation, the interpretation of
combined BOLD and CBF measurements using a quantitative CMRO 2 model remains applicable
for evaluation of glioblastoma patients. Importantly, a significant increase in oxygen-induced
relative CMRO 2 within and around the tumor indicate that hyperoxia can manipulate oxygen
metabolism in cancer cells, supporting the idea that tumors retain their respiratory potential even
under conditions of increased glycolysis. These findings, if confirmed in future studies, could
shed further light on the mechanism of tumor oxygenation and respiratory control, and potentially,
may be used to delineate potential therapeutic options such as normobaric (NBO) and hyperbaric
(HBO) oxygen treatments.
103
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106
Chapter 7
Hypoxia Biomarker:
A Simultaneous Measurement of Relative CMRO2 with MRI and
"F-MISO Uptake with PET in Glioblastoma
7.1. Introduction
Glioblastoma (GBM) is a fatal tumor afflicting approximately 13,000 persons each year in the
United States 2. Despite aggressive therapies including surgery, radiation and cytotoxic
chemotherapy, the average survival rate among GBM patients is less than 1 year, and less than
4% of patients survive 5 years or more. The standard initial therapy for this tumor is maximal
resection, daily temozolomide, followed by radiation (chemoradiation) and 6 monthly cycles of
postradiation temozolomide. Although the prognosis for newly diagnosed GBM patients has
74
improved slightly with the emrgence of chemoradiation' , the general outlook remains grim in
this patient population, with only 26% of patients alive 2 years after diagnosis. Pathologic
features of GBM include marked angiogenesis with microvascular proliferation as well as severe
hypoxia with tumor necrosis5.
GBM vessels are dilated, tortuous, disorganized, highly
permeable, and characterized by abnormalities in their pericyte coverage and basement
membranes 19
The presence of hypoxia within tumors has been observed in patients with glioma before the start
of treatment. Eppendorf pO2 histography studies9- have shown evidence of heterogeneity within
and between the same types of tumor, and demonstrated that hypoxia contributes to poor
prognosis. The decrease in intracellular 02 tension (hypoxia) has long been considered one of the
reasons for the suboptimal treatment response in GBM patients. As hypoxia is an important
biological characteristic and its presence is difficult to predict, a number of preclinical and
clinical studies have been performed to understand the patterns of hypoxia in gliomas and to
monitor the changes that occur during therapy'75'76. Imaging is an important tool for identifying
cancer patients who may benefit from treatment or take advantage of the absence of hypoxia. Any
method to evaluate tumor hypoxia must be noninvasive, and allow continuous monitoring of the
changes that occur during treatment and evaluation of heterogeneity between and within tumors.
107
There are a number of ways in which tissue oxygenation status can be assessed in vivo (both
invasively and noninvasively) or in vitro, using tissue acquired by surgical biopsy.
The challenge for hypoxia imaging is to acquire images showing low levels of tissue P 0
2, which
is a phenomenon that occurs at a much smaller scale than can be assessed with the human
imaging techniques currently available (1-5mm resolution). The various techniques used to assess
hypoxia are sensitive to different properties, and the information provided by the individual
modalities is often complementary. Among the imaging techniques currently available for human
use, magnetic resonance imaging (MRI) and positron emission tomography (PET) allow in vivo
assessment, particularly for repeated, sequential measurements. The general availability, ease of
use, robustness, validity, and noninvasive nature of ['8F] Fluoromisonidazole (18F-MISO) PET
and blood oxygen level dependent (BOLD) MRI, and their ability to measure hypoxia status and
detect heterogeneity, make them ideal for montoring hypoxia in humans.
BOLD MRI is sensitive to pO 2 within and in tissues adjacent to perfused vessels. BOLD MRI
contrast is also dependent on tissue perfusion, levels of oxygenation, as well as on static tissue
components
72.
The primary advantage of BOLD MRI techniques is that there is no need to
administer exogenous radioactive contrast material and images at high temporal and spatial
resolution can be obtained and repeated as needed. Major limitations of BOLD MRI include the
fact that they do not measure tissue pO 2 directly; the images obtained have low contrast to noise
ratio and clinical studies with carbogen vasomodulation are technically challenging.
'8F-MISO is the prototype hypoxia imaging agent whose uptake is homogeneous in most normal
tissues. Having the advantage of being directly related to intracellular p0 2 in viable cells, imaging
with
18
F-MISO has yielded the promising results", providing a quantitative measure of tumor
hypoxia. This method enables hypoxia imaging in a procedure that is well tolerated by patients.
' 8F-MISO is sensitive to the presence of hypoxia in viable cells, but not in necrotic cells, making
' 8F-MISO PET a useful method for monitoring the changing hypoxia status of tumors during
radiotherapy. The limitations of this method include its intermediate signal-to-noise ratio and the
need to obtain venous blood.
Combined BOLD-CBF MRI (to measure CMRO 2) and '8F-MISO PET (to monitor hypoxia) can
provide valuable measurements
of tumor physiology, with excellent structural resolution.
Simultaneous acquisition of MR and PET data could provide such metrics while detecting the
108
delivery of a radiolabeled therapeutic agent to the tumor, or characterizing its biochemistry. Such
data could provide very important answers to the phenomenon of hypoxia.
The goal of this study was to apply combined MR-PET technology (Figure 15) to examine
hypoxia in human brain cancers such as GBM. Although other brain cancers, primary as well as
metastatic tumors, could potentially benefit from this methodology, we have focused on the most
common type of primary brain tumor. The insight we gain into hypoxia by applying the
sophisticated quantitative MR-PET tools in GBM could be relevant to many other types of cancer.
We investigated the hemodynamic response to oxygen and
1
F-MISO uptake by applying novel
simultaneous MR-PET technology in newly diagnosed glioblastoma (nGBM) patients before and
after treatment. The specific goal of this study was to characterize relative CMRO 2 changes in
relation to hypoxia level, based on "F-MISO uptake, in nGBM patients who undergo a multitherapy treatment protocol.
Combined Brain MR and PET
Brain PET Inserter
Figure 15 Combined Brain MR and PET scanner: a BrainPET inserter installed inside the 3T
TimTrio MRI scanner (Left); a BrainPET inserter withdrawn from the MR scanner for separate
MR operation (Right)
109
7.2. Methods
Subjects Recruitment
Three patients (aged 50.3±5.4 years) with nGBM were recruited for the study. Each patient
underwent surgical resection before enrolling in the imaging study. Informed consent was
obtained from all patients participating in the protocol, which was approved by the Institutional
Review Board (IRB) of the Massachusetts General Hospital. All patients were scanned with an 8channel head coil in the integrated MR-PET scanner (3T TimTrio and BrainPET, Siemens,
Malvern, PA) at two specific time points (i.e., days 1 and 24) during treatment.
Data Acquisition
Shortly after installation of the combined system we demonstrated its feasibility for performing
simultaneous MR-PET data acquisition in brain tumor patients. In our tests, the data acquisition
was synchronized (i.e., the frame duration was adjusted based on the MR sequence acquisition
time). No obvious artifacts were observed in the PET data acquired in these conditions. Fusion
software allowed the simultaneous visualization of both the MR and PET datasets. The overall
individual performance of the two scanners seems to be maintained on integration with the MR
scanner. Given these favorable initial data, we applied our simultaneous human brain MR-PET
system for the acquisition of all data.
MRI Data Acquisition
The simultaneous BOLD-ASL sequence was developed based on a pulsed ASL sequence by
applying the QUIPSS II technique for presaturation and a PICORE tagging method followed by
single-shot, gradient echo (GE) echo planar imaging (EPI) acquisition with a 64 x 64 matrix.
Using this technique, we acquired 210 paired images, alternately with and without tagging, using
TIl/TI2 =700/1400ms. Further, 11-slice images, 6mm in thickness, were acquired using the
optimized TE and TR for both BOLD and flow (TR/TE=2000/19 ms, FOV = 220x220 mm 2, 6/8
partial Fourier).
Ti-weighted images after injection of gadolinium-DTPA were acquired to provide anatomical
details. 23-slice axial post-contrast Ti-weighted images were acquired with TR/TE=600/12ms, 5
mm slice thickness, 1mm interslice gap, 0.45mm in plane resolution, and 384x512 matrix.
110
Air and oxygen were administered via a specifically designed respiratory mask, according to the
following breathing paradigm: baseline room air (1min), followed by two blocks of 100% 02 (1.5
min) and room air (1.5 min) with 10-15L/min flow rate (the total scan time: 7 min). Heart rate
(HR) and the peripheral oxygen saturation level (SP 0 2) were continuously monitored using a
pulse oximeter (Invivo, Orlando, FL).
PET DataAcquisition
The BrainPET scanner is a 3D dedicated brain scanner that can either be operated as a standalone PET scanner or inserted into the bore of a 3T MR scanner. A dose of
1
F-MISO (3.7
MBqlkg or 0.1 mCi/kg) was injected at the start of the MR image acquisition, and PET data were
collected simultaneously with MRI. The exact time of the dose calibration was recorded. Single
1
field-of-view emission imaging began 100-120 min after 'F-MISO injection. During 20-min
emission tomography, three venous blood samples were obtained at 5 min intervals. Based on
blood samples counted in a multichannel gamma counter, blood activity was expressed as
pCi/mL decay, corrected to the time of injection.
MRI DataAnalysis
The preprocessing of the raw data included motion correction, subtraction (CBF), and addition
(BOLD) of the paired images, spatial smoothing using a 6mm kernel Gaussian filter, and general
linear modeling (GLM) using Neurolens software. BOLD and CBF signal change maps in
hyperoxia were analyzed using the code developed in-house to estimate relative CMRO 2
according to Chialli's formula [ref]. More details are provided in Section 6.2.
PET DataAnalysis
' 8F-MISO is not actively transported from the blood vessels inside the cells, but diffuses freely in
the interstitial tissue and becomes trapped in viable cells, depending upon the intracellular 02
tension. The kinetic model proposed by Thorwarth et al '77was used to analyze these data. Briefly,
there are two tissue compartments in this model: "diffusive" and "accumulative," the former
corresponding to the unbound (free to diffusive) tracer and the latter corresponding to the
8
irreversibly bound tracer. Three rate constants determine the' F-MISO accumulation: two rate
constants (kI* and k2*) that characterize the diffusion between blood and the diffusive
compartment, and a third rate constant (k3*) that links the diffusive and accumulative
compartments and is directly related to the local
particular voxel
(CT)
02
tension. The total signal measured in a
is a weighted linear combination of these functions (Figure 16, where wo,
111
wA and wB are the relative weights of the compartments). The arterial input function (AIF) of the
tracer was estimated using the MR-based AIF.
PET data were corrected for dead time, scatter, randomness, and attenuation using standard
algorithms provided by the scanner manufacturer. Image reconstruction was performed and
coregistered with high-resolution anatomical MR images that were matched to the BOLD images.
The data were analyzed using the kinetic model to determine parameters related to hypoxia.
All of the MR and PET data were analyzed in region of interests (ROIs) defined on the tumor and
contralateral normal tissue.
Figure 16 Compartment model used to analyze FMISO uptake in tumor
112
7.3. Results
In all of the nGBM patients we examined, the contrast-enhanced lesion exhibited a heterogeneous
pattern of BOLD and CBF signal changes in hypoxia before treatment. As demonstrated in
Figure 17a-c, which shows BOLD (Figure 17b) and CBF (Figure 17c) signal change maps 1 day
before and 24 days after treatment for a representative patient, we generally found the expected
decreased response of BOLD and increased CBF in the residual enhanced tumor and peritumoral
regions at pretreatment. On the other hand, the images after the treatment show more
homogeneously increased response of BOLD and mild changes in CBF compared to the baseline.
The graphs of the average percent change (AS) of the BOLD and CBF signals, for all patients, in
each ROI pre- and post-treatment are shown in Figure 18a-b. The enhanced tumor at baseline
exhibited a subtle increase (0.5%) in the BOLD signal and a dramatic increase (47%) in the CBF
signal. After the treatment, following the reduced enhancement of tumor, we observed a greater
increase (0.9%) in BOLD and a slight increase (8.5%). In normal appearing gray matter, there
was no unexpected changes in BOLD and CBF before and after the treatment.
Figure 19 shows the relative CMRO 2 map evaluated from the above BOLD and CBF changes
(Figure 19b), as well as the'"F-MISO uptake map in PET (Figure 19c) with the post-contrast
anatomical image (Figure 19a) 1 day before and 24 days after treatment. Compared to baseline,
1
the images showed a significant increase in relative CMRO 2 and "F-MISO uptake around the
enhancing tumor, whereas mostly subtle changes were seen in contralateral normal tissue.
However, with tumor regression following treatment, we observed that the relative CMRO 2 and
F-MISO uptake decreased significantly around the tumor compared pretreatment levels.
18
8
Figure 20 shows the graphs of the averaged relative CMRO 2 (Figure 20a) and ' F-MISO uptake
(Figure 20b), for all patients, at two time points (i.e., 1 day before and 24 days after treatment) in
each ROI. These data showed a significant increase in relative CMRO 2 (42%) and
18
F-MISO
uptake (2.45 SUV) around the enhancing tumor compared to mostly subtle changes in the same
8
ROI after treatment (5% in relative CMRO 2 and 1.55 SUV in ' F-MISO uptake).
113
Figure 17 post-contrast Ti-weighted anatomical image [a], BOLD signal change map in
hyperoxia, signal changes (%) [b], CBF signal change map in hyperoxia, signal changes (%) [c]
on 1 day before and 24 days after the treatment for a representative newly diagnosed glioblastoma
patient. The red circles indicate the tumor region.
a-
ii.
1.2
60
140
0.4
20
0.0
0
pre-trestment
posttretment
pre-trefamnt
post-treatmt
Figure 18 [a] percent changes (AS) in BOLD signal, averaged across all three glioblastoma
patients, in enhanced tumor, before and after the treatment, [b] Percent changes (AS) in CBF
signal, averaged across all three glioblastoma patients, in enhanced tumor, before and after the
treatment
114
Figure 19 post-contrast Ti -weighted anatomical image [a], relative CMRO 2 map in hyperoxia [b],
8
1 F-MISO uptake (SUV) [c] on 1 day before and 24 days after the treatment for a representative
newly diagnosed glioblastoma patient. The red rounds indicate the tumor region.
a.
b.
so
T
4030
T
20
10
0
Sm
pre-treatment
0
pre-treatment
post-treatment_
pre-treatment
post-treatment
post-treatment
CMROI
Figure 20 [a] averaged relative CMRO 2 (i.e.,
C o 2 0), and [b] averaged 1 F-MISO
uptake [SUV] in three newly diagnosed glioblastoma (nGBM) patients, before and after the
treatment
115
7.4. Discussion
In this clinical study, we sought to expend our previous findings (as described in Chapter 6) in
relation to hypoxia level in nGBM patients, using the new combined MR-PET scanner (Figure
15). We had previously observed oxidative metabolic changes in nGBM patients in an important
physiologically perturbed condition (i.e., hyperoxic challenge). However, further understanding
of what caused this change in gliomas eluded us. We therefore applied our novel combined MRPET technique to achieve quantitative assessment of the changes in oxidative metabolism and
hypoxia in nGBM patients.
Our results agree with the previous patterns of metabolic changes and
high-grade gliomas (i.e., increased relative CMRO 2 and
1
F-MISO uptake seen in
18
F-MISO uptake) and the mean values
measured in our previous study (in Section 6.3.) and described in other published reports' 99'17 8 .
We confirmed the ability of our combined scanner to evaluate the physiological responses of
tumor in comparison with "conventional" separate MR and/or PET measurements. Our results
extend earlier findings to track the correlation between oxidative metabolic and hypoxia level
changes in nGBM patients induced by multi-therapy treatment, and also augment several new
findings.
The first remarkable observation is that the relative CMRO 2 increased in the region that exhibited
high "'F-MISO uptake in pretreated tumor. One interpretation of this observation is that the
hypoxic cells in the tumor began to consume the full amount of oxygen delivered to accelerate
oxidative metabolism. This interpretation is consistent with our previous assumption in Chapter 6.
Distortions observed in the vascular microarchitecture in the lesion produce the oxygen-starved
space at the cellular level, which may directly lead to glycolysis to support the metabolic activity
induced by oxygen starvation. When sufficient oxygen is delivered directly to oxygen-starved
cells, they are able to consume it via aerobic metabolism, which suggests that hyperoxia
manipulates oxygen metabolism in hypoxic cancer cells.
However, the MR and PET data revealed distinct patterns in different parts of the tumor (i.e.,
increased
1
F-MISO uptake with no CMRO 2 changes, and vice versa). Furthermore, the increase
in CMRO 2 was more widely distributed than that of 18F-MISO uptake although overlap was seen
in some regions. This might indicate that hyperoxia changes not only the oxygen metabolism in
116
hypoxic cancer cells, but also in normal-appearing tissues that may be affected by infiltrating
cancer cells.
8
The second finding is that both the relative CMRO 2 and ' F-MISO uptake were clearly reduced
with tumor regression following multi-therapy treatment. It indicates that the cytotoxic effect of
the treatment reduced the number of hypoxic cells in GBM, resulting in regular CMRO 2 behavior,
as observed in normal gray matter. This decreased hypoxic cellular density in the area of the
tumor, as detected in the PET images, is consistent with the diminished oxidative metabolic
changes detected in MRI during a short treatment window, i.e., within 1 month. Therefore, the
therapeutic effect on GBM is likely to be predicted by the matrix of these simultaneous
measurements in the early stages of treatment, which provides great benefit for the wellorganized design of potential therapies. Overall, our results suggest strong correlation between
oxygen metabolism and hypoxia level in tumor cells. However, we concede that our study does
have some important limitations that preclude definitive interpretation of our results.
We acknowledge that our study is limited by its small sample size. Given our methods offer very
complementary data, there is high potential to integrate and improve them. Our study also
presented unique challenges for clinical translation of the new MR-PET methodology. For precise
clinical translation of the new system, we had to use great care in the standardization of imaging
procedures and analysis methods to more fully validate our technique. Coregistration and
quantification of different instruments and imaging protocols were challenging from the point of
view of minimizing errors. Our semi-quantitative techniques were derived from parameters based
on established measures of tumor biology and physiology, but some missing links remain in our
interpretation. Variation between measurements and time points of the same quantity, from the
same individual, caused either by measurement error or by physiological changes between
measurements should also be known. Further improvement of our new technique will thus be
important, and studies are currently ongoing in that direction.
This prospective study provides preliminary evidence of the effects of multi-therapy treatment on
tumor oxidative metabolism and hypoxia, as evaluated by combining advanced MR imaging and
PET with a novel contrast agent. Our data suggest a strong correlation between CMRO 2 changes
and
F-MISO uptake, which will serve as an effective biomarker for detection of oxidative
18
changes and therapeutic effects in gliomas. Tumor hypoxia is common, and its effects represent a
significant challenge to the curability of human tumors, leading to treatment resistance and
117
enhanced tumor progression. Tumor hypoxia can be detected by both noninvasive and invasive
techniques, but the interrelationship between these techniques must be better defined; at present,
human validation of the utility of hypoxia imaging is sparse at best. Antihypoxia therapies do
exist currently in the clinic, and more are on their way. However, the benefits of such therapies
are limited, either because they do not work very well or we do not know how to use them
optimally. Our integrated hypoxia imaging technique, applied in a subpopulation of cancer
patients, has potential to aid the design of novel antihypoxia therapies.
118
References
1.
CBTRUS. Primary Brain Tumors in the United States Statistical Report. (2005).
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Stupp, R., et al. Radiotherapy plus concomitant and adjuvant temozolomide for
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Plate, K.H. & Mennel, H.D. Vascular morphology and angiogenesis in glial tumors. Exp
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Rampling, R., Cruickshank, G., Lewis, A.D., Fitzsimmons, S.A. & Workman, P. Direct
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Valk, P.E., Mathis, C.A., Prados, M.D., Gilbert, J.C. & Budinger, T.F. Hypoxia in human
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Guo, P., et al. Platelet-derived growth factor-B enhances glioma angiogenesis by
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Hockel, M., Schlenger, K., Knoop, C. & Vaupel, P. Oxygenation of carcinomas of the
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Vaupel, P., Kelleher, D.K. & Hockel, M. Oxygen status of malignant tumors:
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Bernsen, H.J., et al. Hypoxia in a human intracerebral glioma model. J Neurosurg 93,
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Rijken, P.F., et al. Spatial relationship between hypoxia and the (perfused) vascular
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Howe, F.A., Robinson, S.P., McIntyre, D.J., Stubbs, M. & Griffiths, J.R. Issues in flow
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Koh, W.J., et al. Imaging of hypoxia in human tumors with [F-18]fluoromisonidazole. Int
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Thorwarth, D., Eschmann, S.M., Paulsen, F. & Alber, M. A kinetic model for dynamic
[18F]-Fmiso PET data to analyse tumour hypoxia. Phys Med Biol 50, 2209-2224 (2005).
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Lawrentschuk, N., et al. Assessing regional hypoxia in human renal tumours using 18Ffluoromisonidazole positron emission tomography. BJU Int 96, 540-546 (2005).
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Swanson,
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120
Chapter 8
Conclusion
8.1. Current State of Integrated Imaging Techniques for Biomarker Identification
The goal of this thesis was to investigate biomarkers for aggressive, infiltrating brain tumors (i.e.,
gliobalstoma) using integrated advanced imaging techniques. With a focus on cancer physiology
including angiogenesis, oxidative metabolism, and hypoxia in glioblastoma, this study has
succeeded in harnessing the unprecedented spatio-temporal resolution of MRI and PET
techniques to investigating biomarkers that may help predict the responses of antiangiogenic
treatment, most notably, to observe the unpredicted shifts in oxidative metabolism in oxygen
perturbation and its link to hypoxia in glioblastoma.
The first biomarker, detected by 1H-MRS in our prospective study, provides preliminary evidence
that the antiangiogenic of the new drug cediranib elicits direct metabolic changes in recurrent
glioblastoma. Traditionally, such findings have been interpreted as antitumor effects resulting
from vascular normalization, based on the dynamics of the predominant brain metabolites. Our
data also suggest that with further technical advances, early metabolic changes detectable by 'HMRS will serve as imaging biomarkers, to predict treatment response in patients with recurrent
malignant glioblastomas. The metabolic changes in an enhancing tumor suggest that anti-VEGF
therapy not only has an antivascular effect, but that such effects modulate tumor and brain tissue
both early and late in the disease process. This biomarker, if confirmed in future studies, could
delineate the mechanism of action of this new class of antiangiogenic agents, and could
potentially be used to make treatment management decisions.
Another biomarker, determined by simultaneous functional MRI measurement, exhibits the
changes in oxygen consumption rate following changes in BOLD and CBF signals in
glioblastoma, under physiological perturbation of oxygen modulation. This study suggests that
with further careful exploration and additional model validation, the CMRO 2 biomarker,
determined by combined BOLD and CBF measurements using a quantitative model, will become
valuable for evaluation of glioblastoma patients. Remarkably, a significant increase in oxygen-
121
induced relative CMRO 2 within and around the tumor indicated for the first time that hyperoxia
can manipulate oxygen metabolism in cancer cells, supporting the notion that tumors retain their
respiratory potential even under conditions of increased glycolysis. Therefore, these findings
could serve in a key capacity to inform potential therapeutic designs.
The final biomarker assessed by simultaneous MR and PET, linked with CMRO 2, provides useful
information about the changes in tumor hypoxia. This incorporated biomarker suggests a strong
correlation between the oxygen consumption rates in hyperoxia and hypoxia, and can serve as a
feasible biomarker for detecting oxidative changes in early stages of treatment. In addition, this
biomarker has important implications for the role oxygen plays in supporting tumor metabolism
and angiogenesis, and can help us better understand the mechanisms of new drugs in cancerous
tissues.
MRI is a modality with wide-ranging applications. Although its anatomic depictions are widely
used for traditional cancer imaging needs such as volumetric assessment, its true power for
identifying cancer imaging biomarkers will come from the more physiologic and functional
abilities it contains. Since all of our methods offer complementary data, there is high potential to
integrate and improve them. Further effort is required to advance our most promising techniques
from the preliminary biomarker stage to advanced stages with more clearly established utility. If
this is done, the potential of these imaging tools could more fully realized to help reduce
morbidity and mortality in cancer.
8.2. Novel Methodologies
Numerous challenges were surmounted during the process of carrying out this dissertation
research.
Theoretical achievements included the development and application of appropriate hemodynamic
and oxygen transport models, development of a CMRO 2 model applicable to tumor under unusual
physiological perturbations, sensitization of the innovate sequences and imaging technology to
physiology, analytical methods, visualization techniques for functional experiments, and clinical
collaboration involving the requirement and participation of ill patients.
122
Methodological achievements included mathematical calculation of the metabolites by MRS,
advanced modeling of CMRO 2 in hyperoxia, adjustment of the modified CMRO2 model to
parameters representative of the different physiological properties of tumor, computed integration
8
of coupled MRI and PET parameters, and estimation of the new tracer 1 F-MISO uptake.
The chief experimental developments were: 1) experimental methods to apply MRS to clinically
estimate the metabolic changes in tumor; 2) simultaneous acquisition of CBF and BOLD with
minimal artifact, including pulse sequence development; 3) modeling for CMRO 2 changes under
different physiological conditions, with development of MRI gas inhalation methods; 4)
simultaneous acquisition of MRI (i.e., BOLD and CBF) and PET to optimize the spatial and
temporal resolution and to develop advanced analysis with robust co-registration; and 5) methods
8
to establish the correlation between CMRO 2 changes and ' F-MISO uptake.
8.3. Future Work and Potential Applications
Our biomarkers herein represent a promising toolkit for development of new drugs and potential
therapeutic strategies at a time when scientists and clinicians are struggling with the application
of new treatments such as antiangiogenesis agents, especially with regard to meaningful
endpoints. However, before these biomarkers can be used in an application setting, additional
validation steps should be undertaken.
First, we acknowledge that our study was limited by a modest sample size. At this stage, and
given this limitation, it is hard to rule out other possible interpretations of our biomarkers.
Replication of these experiments in a broader range of patients, including patients with lowergrade lesions, would be illuminating, and might indicate how the functional changes in imaging
alter the metabolic changes that lead to glioma malignant dedifferentiation. Second, due to our
currently incomplete understanding of tissue physiology and morphology, our conventional
interpretations of these findings in glioblastoma were generated primarily from the framework
established for traditional treatments, such as those in the so-called pre-antiangiogenic era. Third,
because the SNR of the ASL technique used in this clinical investigation was limited, we were
not able to make reliable measurements of CBF signal in white matter, and thus, we can not make
determinations of the effects seen in this tissue. Finally, and perhaps most significantly, our study
focused on changes in oxidative metabolism, and did not directly measure baseline CMRO 2.
123
Understanding the denominator in our maps of changing oxygen utilization is clearly key to
understanding the broader implications of our observations. Determining both baseline CMRO
2
and tissue hypoxia 172 would thus be important to both better understand and more accurately
interpret our biomarkers. These important studies should be ongoing.
After completing key validation steps, our imaging biomarkers will help us to develop clearer
understanding of the characteristics of tumor physiology including angiogenesis, oxidative
metabolism, and hypoxia. These biomarkers also have potential as useful surrogate end points,
applicable to the various stages of the pharmaceutical industry's drug product development
paradigm. Thoughtful use of our biomarkers may allow early safety and proof-of-concept
determinations. Perhaps more importantly, in the clinical setting our biomarkers may allow
researchers and clinicians to identify promising new therapies more quickly, and to convincingly
demonstrate the lesser promise of other products, which, together can greatly improve the
efficient evolution of the vast number of drugs and devices in initial stages of evaluation.
Additionally, these techniques will be available to streamline drug development, enable
longitudinal examination of tumor development, and track tumor response to treatment.
It is easy to see how everyday radiologic findings may be effectively used as imaging biomarkers.
Perhaps just as important, our integrated techniques evaluated by imaging modalities that are
widely available nationwide, can provide important infrastructure on which to build biomarkersrelated trials. With both versatility and practicality, our imaging biomarkers have great potential
to aid a wide variety of preclinical and clinical trials.
124
125