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Radiotherapy Treatment Planning:Objectives, Formulations and
Clinical Implications
Michael J Zelefsky M.DMemorial Sloan-Kettering Cancer Center
New York, N.Y
New Challenges for RT Treatment Planning
• New treatment delivery systems such as IMRT have compelled physicians and physicists to more carefully consider the dose distribution over the normal tissues.
• 3D-CRT and IMRT have facilitated dose escalation strategies, placing greater demands on treatment planning.
PTV
Conventional Forward Planning and 3D-CRTDefine PTV dose,treatment beams,
and specify parametersof each beam
Dose Calculation
Assess dose distribution and adjust
beam parameters until satisfactory
plan is derived
PTV
Organ at risk
PTV
Organ at risk
PTV
Inverse PlanningSpecify beam directions
and dose distribution
Computes intensity-
modulatedbeams
Computer-aidedoptimization
derives desired treatment plan
PTV
Organ at risk
PTV
Organ at risk
••• •••
a n a..+..n..+..zz
Intensity Modulated Radiation Therapyl Inverse treatment planning
l Delivery of intensity modulated beams
Rectum
ProstatePTV
Bladder
RectumProstate
PTV
Bladder
Comparison of 3DComparison of 3D--CRT and IMRT CRT and IMRT Prostate Cancer Treatment Plans Prostate Cancer Treatment Plans
3D3D--CRTCRT IMRTIMRT
Per
cen
t G
rad
e 2-
3 R
ecta
l To
xici
ty
0 12 24 36 48 60 72 84 96Months
5
10
15
20
81 Gy 3D-CRT (61)
81 Gy IMRT (189)
p = 0.003
Grade 0-1 757/772 (98%)Grade 2 11/772 (1.5%) Grade 3 4/772 (0.5%)
Incidence of Grade 2-3* Rectal Toxicity in Prostate Cancer Patients Treated to 81 Gy by 3D-CRT and IMRT
*One case of grade 3 rectal bleeding in each treatment group
Normal Tissue Considerations
• Dose-volume constraints for each normal organ need to be established to minimize treatment-related toxicities.
• These constraints ultimately need to be incorporated into the treatment plan and balanced with target coverage parameters.
Correlation of Mean DVH With Rectal Bleeding at >30 Months After 3D-CRT
75.6 Gy
Prescription Dose (%)
0 20 40 60 80 100
Rec
tal V
olu
me
(%)
0
20
40
60
80
100
No Rectal Bleeding (82)Rectal Bleeding (36)
p=0.0001
0
20
40
60
80
100
0 2000 4000 6000 8000Dose (cGy)
Vo
lum
e (%
)
PTV Rectal Wall Bladder Wall
47 Gy
53%
Incorporating Rectal Constraints in the Treatment Plan
Target Dose Constraints
• Homogeneity factors considered
• Penalties assigned for overdosage (lower penalty) and underdosage (greater penalty)
• Dose painting reported by the UCSF group to selectively intensify dose to regions of the target
• Inhomogeneity may be more preferable!
P Pul
target
w (D-P )2
uu
w (D-P )2l l
organ at risk
Dc
wc(D-Dc)2
MSKCC OBJECTIVE FUNCTION
“Beamlets”
Greater penalty applied for target underdosage
Dose-Volume Constraint Templates
Prostate Cancer IMRT Planning at MSKCC
l A coplanar, non-collinear, 5-field arrangement is used
Dose constraints and penalties for 81 Gy plan:Dose constraints and penalties for 81 Gy plan:
PTV minus rectum overlap:PTV minus rectum overlap: Prescription dose = 100%Prescription dose = 100%Minimum dose = 98%, penalty = 50Minimum dose = 98%, penalty = 50Maximum dose = 102%, penalty = 50Maximum dose = 102%, penalty = 50
PTV plus rectum overlap: PTV plus rectum overlap: Prescription dose = 95%Prescription dose = 95%Minimum dose = 93%, penalty = 10Minimum dose = 93%, penalty = 10Maximum dose = 96%, penalty = 20Maximum dose = 96%, penalty = 20
Rectal wall:Rectal wall: Maximum dose = 95%, penalty = 20Maximum dose = 95%, penalty = 2070% of rectal volume receives < 40%70% of rectal volume receives < 40%maximum dose, penalty = 20maximum dose, penalty = 20
Bladder wall:Bladder wall: Maximum dose = 98%, penalty = 35Maximum dose = 98%, penalty = 3570% of bladder volume receives < 40%70% of bladder volume receives < 40%maximum dose, penalty = 20maximum dose, penalty = 20
Nasopharynx Cancer - Comparison of Conventional and IMRT Treatment Plans
Prescription:Gross disease: ≥ 70 GyMicro. disease: ≥ 54 GyBID after 36 Gy
Constraints:Min PTV isodose - 100%Max PTV isodose - 120%Max cord dose - 40 GyMax brainstem dose - 45 Gy
Conventional IMRT
e- e-
< 50 Gy 60-65 Gy > 70Gy
Prescription:Gross disease: 70 Gy Micro. disease: 54 Gy
Laterals to 70 Gy
Posterior e- strips
Nasopharynx IMRTNasopharynx IMRTPlan Goals versus ConstraintsPlan Goals versus Constraints
Structure Max/Pen. Min/Pen. Vol. Max. Dose Vol.
PTV 105%/50 95%/50 -- 120% (84 Gy) D95 > 95%
Cord 40%/50 -- -- 57% (40 Gy)
Brain Stem 50%/50 -- -- 65% (45 Gy)
Cochlea 45% 20 77% (54 Gy)
Parotid 70%/50 -- --
Parotid 23% 20 30%
Mean Dose 37% (26 Gy)
Set Constraints
Optimize
NT dose Too high
PTV Too high
No significant Change
↑ NT Constraint
Or ↓ Penalty
Both PTV & NT
acceptable
Both PTV & NT
unacceptable
Change NT Constraint
Change NT penalty
STOP
Strategy for Determining Optimization Parameters
0
20
40
60
80
100
0 20 40 60 80 100 120
Dose (% of Prescription)
% V
olu
me
Five Fields, Parameter Set 1
Bladder Wall Optimization Parameters:Maximum Dose: 95%, Penalty: 50Dose Volume: ≤ 30% Vol. to ≥ 34% of Rx., Penalty: 20
PTVV95: 90%V100: 65%Bladder
V47Gy: 53%
0
20
40
60
80
100
0 20 40 60 80 100 120
Dose (% of Prescription)
% V
olu
me
Bladder Wall Optimization Parameters:Maximum Dose: 95%, Penalty: 50Dose Volume: ≤ 30% Vol. to ≥ 55% of Rx., Penalty: 20
Five Fields, Parameter Set 2
PTVV95: 96%V100: 83%Bladder:
V47Gy: 61%
0
20
40
60
80
100
0 20 40 60 80 100 120
Dose (% of Prescription)
% V
olu
me
Seven Fields, Parameter Set 3
PTVV95: 93%V100: 81%Bladder
V47Gy: 53%
Bladder Wall Optimization Parameters:Maximum Dose: 95%, Penalty: 50Dose Volume: ≤ 30% Vol. to ≥ 38% of Rx., Penalty: 20
Optimization of Treatment Plans
• Current approach balances dose constraints and limitations applied to the normal tissues and target coverage
• Penalties applied for plans where constraints are exceeded
• Not routine for rewards to be applied for discriminating and selecting plans that achieve lower doses to normal tissues.
PTVGR GTV
40 47 55 63 70 Gy
Cochlea
Optimization Parameters and Target-NormalTissue Proximity
0
20
40
60
80
100
0 20 40 60 80
Dose (Gy)
% V
olum
e
PTV
Lt. Cochlea
PTVGR PTVEL
40 47 55 63 70 Gy
Cochlea
Optimization Parameters and Target-NormalTissue Proximity
0
20
40
60
80
100
0 20 40 60 80
Dose (Gy)
% V
olum
e
PTV
Lt. Cochlea
PTVGR PTVEL
40 47 55 63 70 Gy
Cochlea
0
20
40
60
80
100
0 20 40 60 80
Dose (Gy)
% V
olum
e
Optimization Parameters and Target-NormalTissue Proximity
PTV
Lt. Cochlea
• Software captures and stack the axial ultrasound images and the position of the needles.
• Prostate and normal organs are reconstructed in 3-dimensions.
• Genetic algorithm determines the optimal seed coordinates to satisfy dose-volumes constraints for urethra, rectum and target.
Intraoperative Conformal Planning for Prostate Brachytherapy at
MSKCC using a Genetic Algorithm
Genetic Algorithm-I
• Optimization code with operating mechanism that relies on “natural selection”.
• “Member of the population” represents a specific seed-loading pattern
• Each seed represents a “chromosome”
• Algorithm evaluates each seed arrangement according to an objective function using dose constraints and weighting factors for normal tissues and target
Genetic Algorithm-II
• “Members of the population” evaluated to how the seed-loading pattern meet the criteria of the objective function.
• “Best fit” individual preferentially selected to serve as “parents” for next generation.
• Iterative process continues until best fit solution found after 6000 generations
Intraoperative Conformal Planning for Seed Implants at MSKCC
• Inverse planning system which incorporates a genetic algorithm for optimization
• Target Constraints– Minimum dose of 144 Gy
• Urethra <125% of prescription dose• Rectum < 100% of prescription dose
Target Coverage According to Technique
75
80
85
90
95
100
%V100 %V90 D90
CT Pre-PlanUltrasound ManualIntraoperative 3D
%
P < 0.001
(Zelefsky et al IJROBP -2000)
Urethral Dose According to Technique
0
50
100
150
200
250
300
350
ave urethral dose max urethral dose
CT Pre-PlanUltrasound ManualIntraoperative 3D
% o
f p
resc
rip
tio
n
P < 0.001
(Zelefsky et al IJROBP -2000)
Conclusions
• New treatment delivery systems have placed increased challenges for radiotherapy treatment planning
• Optimization strategies currently rely on dose constraints and penalties for exceeding pre-determined dose limitations.
• In the future, new paradigms such as biologic-based variables will need to incorporated into such strategies.
Conclusions
• Because of variations in the proximity of normal tissues to target, the same constraints for each patient will not consistently identify the “best plans”.
• While these dose-volume constraints are not exact and will not lead to the optimal solutions, new optimization strategies which select the most feasible solution will likely impact upon improving conformality and treatment outcome.
