Eric E. Klein, M.S., Washington
University, St. Louis, MO
Craig Stevens, M.D., Ph.D., MD Anderson
Cancer Center, Houston, TX
AAPM 2005 Annual Meeting
• Effectiveness of radiation therapy depends on maximum TCP and minimum NTCP. Both of these quantities are very sensitive to absorbed dose
• We learn how to prescribe from clinical trials and controlled studies. Their outcome depends on the accuracy of reporting data
• TG-43 changes to S k
Calibration updates. based on NIST
• Gamma Knife (Elekta) found a 8% discrepancy in 4 mm output. End result, Direct
Prescription change of 8%.
• Change from LDR to HDR GYN
Brachytherapy. Depends on institution.
• IMRT – Too early to advise if excessive hot spots (EUD concept) matters
• Orton et al (1998)
– Developed benchmark test case
– Reviewed 322 patients in RTOG 88-08
• Results
– Benchmark lung corrections
• Measured: 1.14 (Co-60)-1.05 (24 MV)
• Calculated: 1.17 (Co-60)-1.05 (24 MV)
– Patients: 0.95-1.28, mean=1.05, SD=0.05
• For lateral fields: mean=1.11, SD=0.08
• Conclusion
– Lung corrections lead to significant variations
– Density corrections will help reduce these variations
1

• Mah & Van Dyk (1991)
– reviewed 100 thoracic patients
• Conclusions
– Within lung, corrections are significant (0.95-1.24)
– Target dose corrections are significant (0.95-1.21)
– Substantial variation over patients (-5% to +21%)
– Dose uniformity reduced in corrected distributions
– In
∼∼∼∼
80% patients, probability of lung damage underestimated by >5% (up to 19%) if corrections not applied
Density
Determination
CT Based
Van Dyk IJORBP 1983
Assumed
Density
Dose Correction
Factor
“real” 1.40
% Difference from
“real density calculation
0
CT Measured
(total lung)
CT Measured
(average lung)
Age Related Best
Fit
Age Related Best
Fit (+ 1 SD)
Age Related Best
Fit (-1 SD)
Emphysema
Metastases
0.26
0.35
0.31
0.38
0.24
0.06
0.60
1.45
1.39
1.42
1.37
1.47
1.59
1.23
Dose Correction Factors Based on
Different Lung Density Assumptions
+4
-1
+2
-2
+5
+14
-12
TISSUE INHOMOGENEITY CORRECTIONS
FOR MEGAVOLTAGE PHOTON BEAMS
Report of Task Group 65 of the Radiation Therapy Committee of the American Association of Physicists in Medicine
Nikos Papanikolaou
Jerry J. Battista
Arthur L. Boyer
Constantin Kappas
Eric Klein
T. Rock Mackie
Jeff V. Siebers
Michael Sharpe
Jake Van Dyk
University of Arkansas, Little Rock, Arkansas, USA
London Regional Cancer Centre, London, Ont., Canada
Stanford University, Stanford, California, USA
University of Thessaly, Medical School, Larissa, Hellas
Mallinckrodt Institute of Radiology, St Louis, MO, USA
University of Wisconsin, Madison, Wisconsin, USA
Virginia Commonwealth University, Richmond, Virginia
Princess Margaret Hospital, Toronto, Canada
London Regional Cancer Centre, London, Ont., Canada
Physics of Photon Dose Calculation Problem
• Incident photons
(spectrum)
• Scattered photons
• Scattered electrons
2

Photon scatter
Depth Field size
(cm) (cm)
Scatter (% of total dose)
Co-60 6 MV 18 MV
5
10
20
5 x 5
10 x 10
25 x 25
12
24
48
8
18
38
7
14
27
Range of scattered electrons
Range
Forward (cm)
Lateral (cm)
Co-60 6 MV 18 MV
0.5
0.2
Energy
1.5
0.4
3.0
0.8
Measurement based
Algorithms
Model based
Algorithms
Rely on measured data in water, coupled with empirically derived correction factors to account for patient contour, internal anatomy and beam modifiers (Clarkson,
ETAR)
Use measured data to derive the model parameters. Once initialized, the model can very accurately predict the dose based on the physical laws of radiation transport
(convolution, MC)
• Dose at A = Dose at B
• d x
ρ and w x
ρ are equal
Local Energy Deposition - No Electron Transport
ICF
=
T ( d ' ,
T ( d , r )
)
• Uses O’Connor’s scaling theorem d & r are depth & radius of equivalent d ' &
= r are scaled versions of d & r
ρ ijk w ijk
= i j k w ijk i j k field
3

• Mackie et al
(1985)
• Effects of electron transport
– High energy
• Predicted by convolution
Non Local Energy Deposition - Electron Transport
D
= dxdydz
Φ
3 D
( , , ) K pt
( , , )
muscle ρρρρ =1 gr/cm 3 lung ρρρρ =0.25 gr/cm 3
4

Convolution/Superposition Homogeneous Scatter Homogeneous Primary and Scatter
12 patients
• Homogenous plan
• Heterogeneous plan calculated using CMS
XiO Superposition/Convolution with same:
– MU
– Block margin
• Review of Doses to Isocenter (ICRU Ref.
Point), minimum PTV coverage, and
Critical Organs
15
18
19
20
21
10
12
13
14
Depth
(cm)
2
3
5
6
7
9
One Validation Test for Algorithm
Meas.Dose
(cGy)
100.4
95.9
88.5
84.6
81.9
76.9
74.5
70.1
68.0
66.2
64.4
58.8
55.8
53.4
51.1
80.5
77.0
75.2
73.5
71.7
65.7
62.6
59.4
56.2
Conv
-Xio
99.1
95.5
89.1
87.4
85.8
82.3
XiO conv / dose
0.988
0.996
1.007
1.033
1.047
1.070
1.080
1.099
1.106
1.110
1.113
1.118
1.122
1.111
1.101
74.2
69.8
67.7
65.8
63.9
58.5
56.3
53.8
51.3
Superp-
Xio
98.7
95.2
87.5
84.6
81.9
76.7
XiO sup
/dose
1.017
1.007
1.011
1.000
1.001
1.003
1.004
1.004
1.004
1.006
1.008
1.005
0.991
0.993
0.995
Tissue density
Lung density
Tissue density
Normal Tissue % dose Increased
Cord Max dose
Esophagus Max dose
Global Hot Spot
2.0
5.5
8.9
5

• Heterogeneous plan used for up-front MU
• Great care is taken to have weight points in tissue media (even of not isocenter)
• Dose prescribed to 95% isodose
• i.e., 7095cGy @ 95%, 7468cGy @
Isocenter
Limited to 6 MV, Thorax only
Continue running Homogeneous Plans, but now using Hetero. MUs
Homogeneous Heterogeneous
Homogeneous Heterogeneous
6

• Kenneth Forster, Ph.D.
• Steven Frank, M.D.
• Paul Keall, Ph.D.
• Radhe Mohan, Ph.D.
• Michael Gillin, Ph.D.
• The most radioresistant tumor cell is the one that is not irradiated.
– Or not in the high dose region
• Would you choose a less accurate dose calc today?
• We're going to use Monte Carlo calculations in a few years, let's wait
• It's too hard to change.
• We've never used them before.
• Monte Carlo is very similar to convolutionsuperposition with heterogeneity
• Implementing hetero corrections is not hard.
• And they're more accurate!
• But block margin, weighting, and energy will be chosen more accurately
7

• 5 years ago
– transferred CT info to simulator films by hand.
• CT not in Rx position
– "at least" 1cm from tumor edge to block edge
– dose calculated to midplane in a homogeneous patient
• GTV contoured on Rx planning CT, with
FDG PET to identify LN
• CTV based on the literature (8mm).
• PTV
– tumor motion measured in ALL patients (ITV).
– Set up uncertainty measured (2SD=7mm)
• then block edge (~7mm)
• GTV to block edge 8+7+7=22mm
• Rx 95% of PTV gets Rx dose.
8

• Able to do this on a service with
– 8 attendings
– 2 physicists
– 6 dosimetrists (that rotate)
– 12 Rx machines
• About 100 therapists
– All while implementing IMRT and other new technologies
• But the changes to the isocenter are small, while coverage of the PTV becomes MUCH better.
• GTV -> CTV 8 mm (Giraud et al., 2000)
• CTV -> PTV 10 mm
• PTV -> Block edge 10 mm
• Beam geometries and prescription (60-66
Gy) were those used for initial treatment.
• All beams 6MV x-rays
• Plan 1: calculate dose to iso, homogeneous
• Plan 1H: monitor units from 1, heterogeneous
• Plan 3: adjust beam weights so that 95% of
PTV treated to target dose.
9

• T1
• Goal 66Gy
1
1H
1H
3
AP
PA total
123
178
301
Plan 1 Plan 1H Plan 3
123
178
301
160
135
295
10

• Tumor more anterior
• Lung posterior
• Therefore, weighting should be more AP
1
1H
1
1H
• 29 patients with 30 tumors
• Stage I or Stage II
• CTV range: 15-359 cm 3
• PTV range: 73-760 cm 3
11

• GTV -> CTV 8 mm (Giraud et al., 2000)
• CTV -> PTV 10 mm
• PTV -> Block edge 10 mm
• Beam geometries and prescription (60-66
Gy) were those used for initial treatment.
• Plan 1: calculate dose to iso, homogeneous
• Plan 2: monitor units from 1, heterogeneous
• Plan 3: adjust beam weights so that 95% of
PTV treated to target dose.
• Monte Carlo is very similar to convolutionsuperposition with heterogeneity
• Hetero plans are close to Monte Carlo
– On average PTV coverage is better.
– Case-by-case can be quite different
• And it's not hard.
• But block margin, weighting, and energy will be chosen more accurately
• The physicist needs to understand the algorithm(s) within the TPS and MU calculation programs.
• The physicist is strongly advised to test the planning system to ascertain if the system can predict common trends.
• The physicist is advised to measure benchmark data for their own beam and compare with the calculated (planning system or hand calculations) data. If possible, the physicist may also use Monte Carlo calculations to support measured data.
12

• The physicist should maintain an open dialogue with clinicians and be clear on limitations of the TPS. For each clinical site
(eg. left breast, right lung, larynx etc), there should be 5-10 treatment plans generated, with & without inhomogeneity corrections.
The dose prescription should be the same for both cases.
• TG-65 recommends energies of 12 MV or less for lung radiotherapy.
• The physicist should understand the dose calculation resolution grid, due to volumetric averaging.
Smith et al.
MedPhys, 17: 135
1990:
The Influence of
Grid Size on
Accuracy in
Radiotherapy Dose
Plotting
• The physicist should keep abreast of new algorithms. The vendors should provide clear documentation of the inhomogeneity correction methods implemented.
• When physicists teach residents, tissue inhomogeneity effects on doses should be discussed.
• The physicist should finally confirm that the method to calculate treatment time or monitor units, whether it is derived by the treatment planning software, or with an alternative method, is accurate to deliver the planned absolute dose to the point of interest.
• In addition, planning volume margins may be affected according the algorithms’ ability to calculate penumbra in the presence of inhomogeneous media, particularly lung.
• Classic beam arrangements may need to be scrutinized due to the impact of increased exit dosing observed with corrections applied .
13