Use of commercial MC systems in
routine clinical treatment planning:
pitfalls and triumphs
J. E.Cygler1, E. Heath2, G. X. Ding3, J. Seuntjens2
1The
Ottawa Hospital Regional Cancer Centre
2McGill University, Montreal, Canada
3Vanderbilt University Medical Center, Nashville, USA
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
Part I: Megavoltage Photon Beam
Monte Carlo Treatment Planning
J. Seuntjens, Ph.D.
McGill University, Montreal, Canada
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
Outline
• Rationale for MC as dose calculation engine
for photon beams
• Discussion of commercial MC-based TPS the PEREGRINE system
• Ingredients of commissioning and
verification
• Clinical examples of MC-based TPS
• Conclusions
4x4 cm2 and
10x10 cm2 fields
Cranner - Sargison et al PMB 49: 1557 - 1567 (2004)
Dose in re-buildup regions:
lateral electronic disequilibrium
(Shahine et al, Med. Phys. 26/3, pp350-355, 1999)
1.2
R elative D ose
6 MV
photon
s
CADPLAN:ETAR
1
CADPLAN:
mod. Batho
0.8
2
5x5 cm field
0.6
Measurements
0.4
0
1
2
3
4
Air Gap thickness (cm)
5
6
Do we need MC dose calculations
for conformal 3D photon beam TP?
Critisism:
• target volume - dose differences will just
lead to a change in prescription dose
– heterogeneity corrections deal fairly
adequately with corrections in target dose
• For organs at risk : dose needs to be
minimized anyway - errors in dose will be of
less impact
Assertion: Photon beam MCTP is
needed because:
• Clinical protocols call for dose escalation, hypofractionation, etc. Increased dose to target requires
improved dose accuracy in organs at risk → MC calculations.
• Correlations between hot/cold-spots and complication
probabilities are expected to improve → re-evaluation of
dose-effect relations.
• IMRT dose calculation and optimization requires MC.
• Consistency is needed between dose calculations for
electron and photon beam TP so that mixed beam therapy
can be used more reliably.
• Scrutiny on MC planning systems is more severe because of
expected improved accuracy.
• Optimized MC systems are faster than convolution /
superposition.
Plan 1 in a lung cancer treatment
Dose (Gy)
__ 4-8 __ 8-12 __ 10-20 __ 20-30 __ 30-36 __ 36-38 __ 38-40 __ 41-42 __ 42-
(a)
(b)
EqTAR corrected
Monte Carlo
Difference map
for PTV area
(c)
Outcome?
Status of MCTP for photons:
how available is it?
• “Academic” photon / IMRT treatment planning systems
–
–
–
–
–
–
–
–
–
Stanford U./Fox Chase Cancer Centre (MCDOSE, EGS-based)
University of Michigan (RT_DPM)
Virginia Commonwealth University (EGS4-based)
University of Seville (IMRT planning - EGS-based)
University of California at L.A. (MCNP - based)
Memorial Sloan Kettering Cancer Center (EGS4-based)
University of Tubingen (XVMC based)
McGill University (BEAM/EGSnrc+XVMC)
etc.
–
–
–
–
–
PEREGRINE (NAS Medical, with CORVUS IMRT)
CMS, Elekta (XVMC)
Nucletron (VMC++)
ADAC (DPM)
?
• Commercial photon / IMRT treatment planning systems
Commerical system(s):
PEREGRINE
• First commercially available MC TPS for
photon beams
• Engine developed at Lawrence Livermore
National Laboratory
• Has been available with NOMOS CORVUS
inverse treatment planning system
• Limited number of validation and clinical
studies
PEREGRINE source model
Target
Primary Collimator
Flattening
Filter
Electrons
Scoring plane
Correlated histograms
Rstartφstart
Virtual Source
Plane
Bin
Probability
nth tile
φstart
Bin
Probability
nth tile
Rstar
nth tile
Relative
Fluence
Isocenter
Plane
t
Riso
Riso
Bin
Probability
nth tile
Energy
Sampling source model
φstart
Virtual Source
Plane
(xstart,ystart)
R
Rstart
ui,vi,wi
Wi
Isocenter
Plane
Riso
(xiso,yiso)
R
Ei
Particle transport and dose scoring
source model (particles
start at bottom of monitor
chamber)
Jaws
MLC
Patient
transport mesh
(512x512x128)
Materials for
which crosssection data is
specified
Density interpolated
from CT calibration
curve
Particle transport and dose scoring
source model (particles
start at bottom of monitor
chamber)
Jaws
MLC
Scoring mesh
(dosels)
Patient
transport mesh
(512x512x128)
Clinical instantiation
• Device file:
– Source model
– Beam modifiers
– Monitor backscatter factors
• Tuning:
– Interpolation between device files to match
40x40 diagonal profile at d=10 cm in water
– MU calibration
McGill PEREGRINE cluster
RC
E
RTOG files
CORVUS 5.0
workstation
16 CPUs at 800 MHz
Ingredients of commissioning
and verification
Primary beam
Beam modeling
Absorbed dose to
water calculation
Patient dose
calculation
Beam modifiers
Reference and
relative output in
defined phantoms
Relative output in
patient geometries
with defined materials
PEREGRINE simulations
• Varian CL21EX with Millennium 120 leaf MLC
• mathematical CT phantoms (1-4 mm slice
thickness, 1 mm2 pixels)
• 3 mm dosel radius
• SQ = 0.5%
• Nhist = 1 – 16 billion
• Calculation time = 3 – 30 hrs
Validation in homogeneous
phantoms
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
Depth 1.5 cm in water
Exradin A14P
PEREGRINE
100
EGSnrc
2%
underestimation
Relative Dose (%)
80
60
40
2-3 %
underestimation in
penumbra region
20
0
0
5
10
Inplane (cm)
15
20
Relative output (z=15 cm)
1.3
Output Factor
1.2
1.1
Exradin A14P
PEREGRINE
1.0
`
0.9
0.8
0.7
0
10
20
30
Field size (cm)
40
50
Buildup region – 10x10 cm2
100
EGSnrc
NACP
PEREGRINE
80
Relative Dose (%)
60
13% discrepancy chamber perturbation!!
60
50
40
40
20
0
30
0.0
0.0
0.5
0.1
0.2
1.0
Depth in water (cm)
See: lecture “Measurement Issues in commissioning and validation…” (Seuntjens 2006)
Validation in heterogeneous
phantoms
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
5 cm lung phantom - 10x10 cm2
100
80
PEREGRIN
NACP
EGSnrc
TLD
60
40
20
solid water
lun
solid
t
0
0
5
10
15
Depth (cm)
20
25
3 cm bone phantom - 10x10 cm2
100
80
NACP
EGSnrc
PEREGRIN
TLD
60
40
20
solid water
bone
solid water
0
0
5
10
15
Depth (cm)
20
25
Validation of MLC model
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
MLC leakage at 2 cm offset
2.0%
1.5%
XV2 film
PG v1.6.1
EGSnrc
1.0%
0.5%
0.0%
-6
-4
-2
0
Inplane (cm)
2
4
6
MLC pattern
100
80
PEREGRINE
diode
60
40
20
0
-25
-20
-15
-10
-5
0
Inplane (cm)
5
10
15
20
25
Dynamic IMRT pattern
100
PEREGRINE
CA24
80
60
40
20
0
-10
-5
0
Inplane (cm)
5
10
Patient dose calculations &
clinical issues
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
Lung case (Hodgkin’s lymphoma)
Target
100
80
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
60
40
20
0
0
5
10
Dose (Gy)
15
Target
25
Equivalent pathlength
15
No correction
5
-5
-15
0
20
40
60
80
Differences with EPL
correction are very small
for target regions!!
-25
% Planned Dose
100
120
140
Heart
100
80
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
60
40
20
0
0
2
4
6
Dose (Gy)
8
10
12
Heart
20
differences due to
beam model issues:
implementation
dependent!!
10
Equivalent pathlength
No correction
0
0
20
40
60
80
-10
100
120
46% increase in
mean dose
-20
% Planned Dose
140
Lung case (IMRT)
5
%
10
%
20 %
50 %
100
%
110
%
PEREGRINE
Effective pathlength
Ipsilateral lung
100
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
80
60
40
20
0
0
2
4
6
Dose (Gy)
8
10
12
Ipsilateral lung
Differences are smaller and more
prevalent at lower doses with IMRT
than with 3D-CRT since conformity
and homogeneity is better and less
ipsilateral lung is irradiated.
10
5
Equivalent pathlength
No correction
0
0
20
40
60
80
100
120
7% increase in mean dose
-5
-10
% Planned Dose
140
Contralateral Lung
100
80
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
60
40
20
0
0
1
2
3
Dose (Gy)
4
5
Contralateral Lung
12
Pattern of difference
is very similar for IMRT
as for 3D-CRT!
8
Equivalent pathlength
No correction
4
0
0
20
40
60
80
-4
9% increase in
mean dose
-8
-12
% Planned Dose
100
120
140
Head and Neck case
Target
100
80
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
60
40
20
0
0
10
20
30
40
Dose (Gy)
50
60
70
Target
15
10
Equivalent pathlength
No correction
5
0
0
20
40
60
-5
-10
-15
% Planned Dose
80
100
120
Left Parotid (tumour side)
100
80
CORVUS (EP)
PEREGRINE
CORVUS (no corr)
60
40
20
0
0
10
20
30
Dose (Gy)
40
50
Left Parotid
15
Equivalent pathlength
10
No correction
5
0
0
20
40
60
80
-5
-10
17%
increase in
mean dose
-15
% Planned Dose
100
120
CORVUS w/ EPL corrections
PEREGRINE
Boudreau et al, PMB
50, 879 2005
2 patients
excluded since
targets included
large air cavities
GTV
CTV
120
11 patients
Typical
DVH for
GTV
100
80
60
PEREGRINE
40
CORVUS no corrections
CORVUS EPL corrections
20
PEREGRINE dose to water
0
Ratio :
40
CORVUS (EPL)
PEREGRINE
D5
Dmean
45
50
Dmax
55
Dose (Gy)
60
V95
65
70
V100
GTV
1.004 ± 0.003 1.011 ± 0.002 1.00 ± 1.01 1.007 ± 0.003
1.16 ± 0.04
CTV
1.003± 0.006
1.12 ± 0.02
Organs at risk
Spinal cord (11)
Right & left parotids (22)
Brainstem (8)
Mandible (8)
1.018 ± 0.003 0.98 ± 0.01
D min
D mean
1.10 ± 0.09 0.999 ± 0.003
0.81 ± 0.03
0.96 ± 0.01
0.88 ± 0.06
0.94 ± 0.02
1.10 ± 0.05
1.02 ± 0.01
1.02 ± 0.01
Dmax
1.00 ± 0.01
0.993 ± 0.005
0.99 ± 0.02
1.00 ± 0.01
Vlimit
0.93 ± 0.01
1.27 ± 0.15
1.10 ± 0.10
Conclusions - Discussion
• MC for photon beam planning is not a
luxury and is clinically needed
• MC accuracy is strongly determined by
• beam model implementation - verification is
needed - don’t trust manufacturer
• accuracy in heterogeneous calculations
• Measurement issues are important for
commissioning and accuracy verification
Conclusions/Discussion
•
•
•
•
Clinical impact/issues of photon MCTP
Target doses are in general well predicted
with heterogeneity corrected algorithms
Higher MC dose to sensitive structures in
vicinity of low density tissues (e-scattering)
Higher or lower doses in sensitive structures
tangential to beam path (beam modeling) implementation dependent!
Outlining issues for planning target volumes
Acknowledgements
•
•
•
•
Dr. Francois Deblois, Andrew Alexander, Khalid Al-Yahya,
Jinxian Dai, William Parker, Dr. Gabriela Stroian, Dr. Frank
Verhaegen
NAS Medical (NOMOS Div.)
Natural Sciences and Engineering Research Council for grant
funding (NSERC)
Canadian Institutes of Health Research and the National
Cancer Institute Canada for grant funding and salary
support (CIHR, NCIC)
References
On the use of PEREGRINE (refereed papers, see also abstracts)
• Boudreau, C., E. Heath, J. Seuntjens, O. Ballivy, and W. Parker. (2005).
“IMRT head and neck treatment planning with a commercially available
Monte Carlo based planning system.” Phys Med Biol 50:1–12.
• Hartmann Siantar, C. L., R. S. Walling, T. P. Daly, B. Faddegon, N. Albright, P.
Bergstrom, A.Bielajew, C. Chuang, D. Garrett, R. K. House, D. Knapp, D. J.
Wieczorek, and L. J. Verhey. (2001). “Description and dosimetric
verification of the PEREGRINE Monte Carlo dose calculation system for
photon beams incident on a water phantom.” Med Phys 28:1322–1337.
• Heath, E., J. Seuntjens, and D. Sheikh-Bagheri. (2004). “Dosimetric
evaluation of the clinical implementation of the first commercial IMRT
Monte Carlo treatment planning system at 6 MV.” Med Phys 31:2771–2779.
• Reynaert N., N. Coghe, B. De Smedt, L. Paelinck, B. Vanderstraeten, W. De
Gersem, B. Van Duyse, C. De Wagter,W. De Neve, and H. Thierens. (2005).
“The importance of accurate linear accelerator head modeling for IMRT
Monte Carlo calculations.” Phys Med Biol 50:831–846.
On photon MCTP - See TG-105, literature is constantly updating…
• Chetty, I. J., et al (2006). “Issues associated with clinical implementation of
Monte Carlo-based treatment planning: Report of the AAPM Task Group No.
105.” Med Phys (Submitted April 2006).
Part II: Electron Beam Monte
Carlo Treatment Planning
Joanna E.Cygler, Ph.D., FCCPM
The Ottawa Hospital Regional Cancer Centre
The Ottawa
L’Hopital
Hospital
d’Ottawa
Regional Cancer Centre
McGill University,
Montreal, Canada
Objectives
• To appreciate the need for MC based
treatment planning systems
• To understand how to set user control
parameters in the TPS to achieve optimum
results (minimum statistical noise, accuracy
vs. speed of calculations)
• To appreciate the effect of different
types of inhomogeneities (geometry and
density) on dose distribution
• To learn and appreciate differences
between water tank and real patient
anatomy based monitor unit values
Outline
• Rationale for MC dose calculations for
electron beams
• Effect of different types of
inhomogeneities (geometry and density) on
electron dose distribution
• Discussion of commercial MC-based TPS
• Clinical implementation of MC-based TPS
• Conclusions
Rationale for Monte Carlo based
Treatment Planning Systems
• Traditional dose calculation algorithms fail in
many cases
• MC gives us in general the right answer
• There are no significant approximations
–
–
–
–
no approximate scaling of kernels is needed
electron transport is fully modelled
geometry can be modelled as exactly as we know it
All types of inhomogeneities are properly handled
• There are many experimental benchmarks
showing MC calculations can be very accurate
Rationale for Monte Carlo dose
calculation for electron beams
• Difficulties of commercial pencil
beam based algorithms
– Monitor unit calculations for
arbitrary SSD values
– Dose distribution in inhomogeneous
media has large errors for complex
geometries
Rationale for Monte Carlo dose
calculation for electron beams
6.2 cm
15
Relative Dose
9 MeV
10
Measured
Pencil beam
Monte Carlo
depth = 6.2 cm
depth = 7 cm
5
0
-10
/tex/E TP /abs/X TS K 09S .OR G
-5
0
Horizontal Position /cm
5
10
98-10-21
Ding, G. X., et al, Int. J. Rad. Onc. Biol Phys. (2005) 63:622-633
Unique Features of Monte Carlo
• Calculation time is related to the
required precision
• Isodose lines, DVHs, TCP/NTCP
exhibit some level of statistical noise
• Can transport explicitly on patient
representative media
• Can report doses as either dose-tomedium or dose-to-water
Components of Monte Carlo
based dose calculation system
There are two basic components:
• Particle transport through the
accelerator head
– Explicit transport (e.g. BEAM code)
– Accelerator head model (parameterization of
primary and scattered beam components)
• Dose calculation in the patient
Commercial Implementation
• MDS Nordion (Nucletron) 2001 - First
commercial Monte Carlo treatment
planning for electron beams
– implementation of Kawrakow’s VMC++ Monte
Carlo dose calculation algorithm (2000)1
• Varian Eclipse eMC 2004
– Based on Neuenschwander’s MMC dose
calculation algorithm (1992)2
Description of Nucletron MC Dose
Calculation Module
• Accelator head model provides Exit
Phase Space5
• Dose calculation in the patient based
on VMC++1
Description of Nucletron Electron
Monte Carlo DCM
Fixed applicator
with optional,
arbitrary inserts
Calculates absolute
dose per monitor
unit (Gy/MU)
510(k) clearance (June 2002)
Nucletron system accelerator head
model for electron beam
Source phase space
Exit fluence components:
Five parameters plus
one energy spectrum
1.
Direct electrons
2.
Indirect electrons
3.
Treatment head generated photons
Exit phase space
Courtesy of E.Traneus
User input Nucletron TPS
Treatment unit specifications:
• Position and thickness of jaw collimators and MLC
• For each applicator scraper layer:
Thickness
Position
Shape (perimeter and edge)
Composition
• For inserts:
Thickness
Shape
Composition
User input Nucletron TPS cont
Dosimetric data for beam characterization
• Without applicators:
–
–
X and Y in-air profiles (8x8,
90 cm)
8x20, 8x35, 35x35, SSD = 70 &
Central axis Depth Dose in water for various field
sizes
• With applicators:
–
–
Central axis depth dose and profiles in water
Absolute dose at the calibration point
Dosimetric data for verification
– Central axis depth doses and profiles for various field
sizes
Description of Eclipse eMC system
• Accelator head model provides Initial
Phase Space
• Dose calculation in the patient based on
MMC2
– Local geometry – PDF in spheres (Kugels)
– Global geometry-transport through the
absorber in macroscopic steps based on PDFs
Initial Phase Space (IPS)
Based on Janssen et al4
Four particle contributions:
1.
Electrons and photons from
the main source
2. Electrons scattered from
the edges of the applicator
3. Photons transmitted through
the applicator
4. Virtual source for electrons
and photons
Varian: Electron Algorithm: Electron Monte Carlo (eMC)
User input - Varian eMC
Open field measurements (no applicator)
• Depth-dose curves in water at the sourceto-phantom distance (SPD) = 100 cm
• Absolute dose, expressed in [cGy/MU], at a
specified point on the depth dose curve
• Profile in air at source-detector distance,
SDD = 95 cm for the wide open field
without an applicator, e.g. 40x40 cm2.
User input Varian eMC cont.
For each energy/applicator combination:
• PDD in water at SSD = 100 cm
• Absolute dose, expressed in [cGy/MU], at a
specified point on the depth dose curve
No head geometry details required, since at this time
Eclipse works only for Varian linac configuration
Clinical implementation of
treatment planning software
• Beam data acquisition and fitting
• Software commissioning tests
• Clinical implementation
– procedures for clinical use
– possible restrictions
– staff training
Software commissioning tests: issues
specific to MC based system
• Setting user control parameters in the TPS
to achieve optimum results (acceptable
statistical noise, accuracy vs. speed of
calculations)
– Number of histories
– Voxel size
– Smoothing
• Understand differences between water
tank and real patient anatomy based
monitor unit values
Software commissioning tests
• Homogeneous water phantom
• Inhomogeneous phantoms (Cygler et al, Phys. Med.
Biol., 32, 1073 (1987) and Ding G.X.et al, Med. Phys., 26, 2571-
2580, 1999)
• All scans done with a high (1 mm) resolution
• Criteria for acceptability
(Van Dyk et al, Int. J. Rad.
Oncol. Biol. Phys., 26, 261-273,1993)
Typical Experimental setup
Electron applicator
•RFA300
(Scanditronix)
dosimetry system
Water tank
•p-type electron
diode
Diode
detector
•Scan resolution =
1mm
Homogeneous water phantom tests
• Standard SSD 100 cm and extended SSD
– Open applicators – PDD and profiles
– Square and circular cut-outs
• Oblique incidence
– GA = 150 and 300
• MU tests – SSD 100 and extended SSD
– All open applicators
– Square, rectangular, circular, some irregular
cutouts
Inhomogeneous phantoms
• Low and high density inhomogeneities
– 1 D (slab) geometry
– 2 D (ribs) geometry
– 3 D (small cylindrical) geometry
• Complex (trachea and spine) geometry
Lateral profiles at various depths,
SSD=100cm, Nucletron TPS
20 MeV, 10x10cm2 applicator, SSD=100cm.
Homogeneous water phantom. Cross-plane profiles at
various depths. MC with 10k and 50k/cm2.
110
110
100
100
90
90
80
80
70
meas.@2cm
60
calc.@2cm
50
meas.@3.0cm
calc.@3.0cm
40
meas.@d=3cm
calc.@d=3cm
calc.@d=3cm,50k
meas.@d=7.8cm
calc.@d=7.8cm
70
Dose / cGy
Dose / cGy
9 MeV, 10x10cm2 applicator, SSD=100cm. Homogeneous
water phantom,cross-plane profiles at various depths. MC
with 10k/cm2.
60
50
calc.@d=7.8cm,50k
meas.@d=9cm
calc.@d=9cm
calc.@d=9cm,50k
40
meas.@4.0cm
30
30
calc.@4.0cm
20
20
10
10
0
0
-10
-5
0
Off - axis / cm
5
10
-10
-5
0
Off - axis / cm
5
10
Results Monte Carlo specific tests
Nucletron TPS
100
• Effect of # histories:
80
gives
1-1.5% statistical
20 MeV
GA=30o
60
Dose/cGy
–
50k/cm2
depth=4 cm
uncertainty and
40
depth=6 cm
smooth isodose lines
Voxel size 0.49 cm
20
Measured
2
Calc. 50k/cm
2
Calc. 10k/cm
0
-21
-18
-15
-12
-9
Off axis/cm
-6
-3
0
3
Overall mean and variance of MC/hand
monitor unit deviation, Nucletron TPS
0.45
Theory
fraction
Our data
0.40
0.35
Mean=-0.003
0.30
Variance=0.0129
0.25
0.20
0.15
0.10
0.05
0.00
-0.05
-0.04
-0.03
-0.02
-0.01
0
0.01
0.02
0.03
1- MC/hand
Cygler et al. Med. Phys. 31 (2004) 142-153
0.04
0.05
Results MC tests:voxel size
Air
cylinder
140
0.19 cm
130
120
dose / cGy
0.39 cm
110
100
90
80
Meas 0.1 cm
70
60
-1
-0 .5
0
0 .5
o f f - a x is / c m
Cygler et al. Med. Phys. 31 (2004) 142-153
1
Dose to water vs. dose to medium
Hard bone cylinder
2 cm
1 cm diameter and 1 cm length
110
110
9 MeV
Bone cylinder is replaced
by water-like medium but
with bone density
100
90
90
80
80
70
70
Dose
Dose
100
depth = 2
60
50
40
60
50
20
Bone
cylinder
location
40
Measured
eMC
30
BEAM/dosxyz
simulation
30
20
10
10
0
0
-8
-6
-4
-2
0
2
4
6
8
0
2
3
4
5
Central Axis Depth /cm
Off-axis distance /cm
100
Ding, G X., et al
Phys. Med. Biol. 51
(2006) 2781-2799
1.14
depth = 3
90
9 MeV
80
1.13
depth = 4
70
60
SPR
Dose
1
Measured
eMC
50
40
1.12
30
Water/Bone stopping-power ratios
1.11
20
10
0
1.10
-8
-6
-4
-2
0
2
4
Off-axis distance /cm
6
8
0
1
2
3
depth in water /cm
4
5
Eclipse eMC no smoothing
Voxel size = 2 mm
Air
Air
Bone
Bone
120
110
120
depth = 4.7 cm
18 MeV
110
100
90
90
Relative Dose
100
Relative Dose
4.7 cm
80
depth = 6.7 cm
70
60
50
depth = 7.7 cm
40
18 MeV
depth = 4.7 cm
80
70
60
50
40
30
20
Measured
eMC
30
Measured
eMC
20
10
10
0
0
-6
-4
-2
0
2
Off-axis X position /cm
4
6
-6
-4
-2
0
2
Off-axis Y position /cm
Ding, G X., et al (2006). Phys. Med. Biol. 51 (2006) 2781-2799.
4
6
Effect of smoothing
Air
Air
Bone
Bone
70
no smoothing
9 MeV
Relative Dose
Relative Dose
70
60
50
40
30
4.7 cm
3D smoothing 2D smoothing
20
no smoothing
9 MeV
2D smoothing
60
50
depth = 4.9 cm
5 mm calculation
grid size
40
30
3D smoothing
20
depth = 4.9 cm
5 mm calculation grid size
10
10
0
0
-6
-4
-2
0
2
Off-axis X position /cm
4
6
-6
-4
-2
0
2
4
Off-axis Y position /cm
Ding, G X., et al (2006). Phys. Med. Biol. 51 (2006) 2781-2799.
6
Effect of voxel size and smoothing
Air
Air
Bone
Bone
110
2 mmand no smoothing
18 MeV
110
Relative Dose
100
90
80
70
2 mmand with 3D smoothing
60
5 mm and with 3D smoothing
50
120
Relative Dose
120
4.7 cm
90
80
70
60
50
40
30
30
depth = 4.9 cm
5 mm and with
3D smoothing
100
40
20
2 mm and with 3D smoothing
20
depth = 4.9 cm
10
10
2 mmand no smoothing
18 MeV
0
0
-6
-4
-2
0
Off-axis X position /cm
2
4
6
-6
-4
-2
0
2
Off-axis Y position /cm
Ding, G X., et al (2006). Phys. Med. Biol. 51 (2006) 2781-2799.
4
6
Effect of voxel size and smoothing
CAX PDD Trachea and Spine
120
9 MeV
80
60
2 mm and with
3D smoothing
40
20
2 mm and
no smoothing
18 MeV
100
Relative Dose
100
Relative Dose
120
2 mm and
no smoothing
80
60
2 mm and with
3D smoothing
40
5 mm and with
3D smoothing
20
5 mm and with 3D smoothing
0
0
0
1
2
3
4
5
6
Central axis depth /cm
7
8
0
2
4
6
8
10
Central axis depth /cm
Ding, G X., et al (2006). Phys. Med. Biol. 51 (2006) 2781-2799.
12
Effect of number of histories
Air
Air
Bone
Bone
120
110
120
18 MeV
110
18 MeV
100
Relative Dose
100
Relative Dose
4.7 cm
90
80
70
60
depth = 4.9 cm
50
90
80
70
60
50
depth = 4.9 cm
40
40
30
1 million histories
100 million histories
30
20
10
1 million histories
100 million histories
20
10
0
0
-6
-4
-2
0
2
Off-axis X position /cm
4
6
-6
-4
-2
0
2
Off-axis Y position /cm
Ding, G X., et al (2006). Phys. Med. Biol. 51 (2006) 2781-2799.
4
6
Treatment Planning Procedure
The physician:
• outlines CTV and/or GTV
The dosimetrist / physicist:
• models the beam (energy, custom cutout)
– CTV covered by 90% isodose line
The software calculates :
• absolute dose distribution in cGy
• number of monitor units, MU
Clinical implementation issues
• Bolus fitting (no air gaps)
• Lead markers (wires, shots) used in
simulation
• Monitor unit calculations
– Water tank or real patient anatomy
– Dose to water or dose to medium
• Workload
Example of poorly fitting bolus
How to correct poorly fitting bolus
Good clinical practice
• Murphy’s Law of computer software
“All software contains at least one bug”
• Independent checks
MU MC vs. hand calculations
Monte Carlo
Real physical dose
calculated on a patient
anatomy
Inhomogeneity
correction included
Arbitrary beam angle
Hand Calculations
Rectangular water
tank
No inhomogeneity
correction
Perpendicular beam
incidence only
9 MeV, full scatter phantom
(water tank)
RDR=1 cGy/MU
Lateral
scatter missing
Real contour / Water tank =
=234MU / 200MU=1.17
MU real patient vs.water tank
MC / Water tank= 292 / 256=1.14
MU real patient vs.water tank
Impact on DVH
Target 1,2 MC
based MU
Target 1,2 water
tank based MU
Lt eye water
tank based
Lt eye MC
MU
based MU
Rt eye water
tank based
MU
Rt eye MC
based MU
Internal mammary nodes
MC / Water tank= 210 / 206=1.019
Conclusions
• Commercial MC based TP system are
available
– easy to implement and use
– MC specific testing required
• Fast and accurate 3-D dose calculations
• Single virtual machine for all SSDs
• Large impact on clinical practice
– CT based planning for most sites – workload
increase
– More attention to technical issues needed
– Dose to medium calculated
– MU based on real patient anatomy (including
contour irregularities and tissue
inhomogeneities)
Thank you
Support of Nucletron and Varian
Corporations is gratefully
acknowledged
References
1.
2.
3.
4.
Kawrakow, I. “VMC++ electron and photon Monte Carlo
calculations optimized for radiation treatment planning”,
Proceedings of the Monte Carlo 2000 Meeting, (Springer,
Berlin, 2001) pp229-236
Neuenschwander H and Born E J 1992 A Macro Monte
Carlo method for electron beam dose calculations Phys.
Med. Biol. 37 107 – 125
Neuenschwander H, Mackie T R and Reckwerdt P J 1995
MMC—a high-performance Monte Carlo code for electron
beam treatment planning Phys. Med. Biol. 40 543–74
Janssen, J. J., E. W. Korevaar, L. J. van Battum, P. R.
Storchi, and H. Huizenga. (2001). “A model to determine
the initial phase-space of a clinical electron beam from
measured beam data.” Phys Med Biol 46:269–286.
References cont.
5.
6.
7.
8.
Traneus, E., A. Ahnesjö, M. Åsell.(2001) “Application and
Verification of a Coupled Multi-Source Electron Beam
Model for Monte Carlo Based Treatment Planning,”
Radiotherapy and Oncology, 61, Suppl.1, S102.
Cygler, J. E., G. M. Daskalov, and G. H. Chan, G.X. Ding.
(2004). “Evaluation of the first commercial Monte Carlo
dose calculation engine for electron beam treatment
planning.” Med Phys 31:142-153.
Ding, G. X., D. M. Duggan, C. W. Coffey, P. Shokrani, and J.
E. Cygler. (2006). “First Macro Monte Carlo based
commercial dose calculation module for electron beam
treatment planning-new issues for clinical consideration.”
Phys. Med. Biol. 51 (2006) 2781-2799.
Popple, RA., Weinberg, R., Antolak, J., (2006)
“Comprehensive evaluation of a commercial macro Monte
Carlo electron dose calculation implementation using a
standard verification data set”. Med Phys 33:1540-1551