What’s next in IMRT?What’s next in IMRT?- Optimizing the Optimization - - Optimizing the Optimization -

TT.. Bortfeld Bortfeld11, C. Thieke, C. Thieke1,21,2, K.-H. Küfer, K.-H. Küfer33, H. Trinkaus, H. Trinkaus33

11Department of Radiation Oncology, Department of Radiation Oncology, Massachusetts General Hospital, Boston, USAMassachusetts General Hospital, Boston, USA

22Department of Medical Physics, Department of Medical Physics, Deutsches Krebsforschungszentrum, Heidelberg, Germany,Deutsches Krebsforschungszentrum, Heidelberg, Germany,

33Fraunhofer Institut für Techno- und Wirtschaftsmathematik, Fraunhofer Institut für Techno- und Wirtschaftsmathematik, Kaiserslautern, GermanyKaiserslautern, Germany

Current technical/physical developments in IMRTCurrent technical/physical developments in IMRT

• Make IMRT more efficientMake IMRT more efficient– Streamlined, integrated solutionsStreamlined, integrated solutions– Minimize MLC segmentsMinimize MLC segments– Optimized inverse planningOptimized inverse planning

• Make IMRT more accurateMake IMRT more accurate– Better dose calculation (superposition, MC)Better dose calculation (superposition, MC)– Image guidanceImage guidance– Online verification with portal imagingOnline verification with portal imaging– Gating/Tracking to reduce breathing artifactsGating/Tracking to reduce breathing artifacts– Proton and heavy ion IMRTProton and heavy ion IMRT

Current technical/physical developments in IMRTCurrent technical/physical developments in IMRT

• Make IMRT more efficientMake IMRT more efficient– Streamlined, integrated solutionsStreamlined, integrated solutions– Minimize MLC segmentsMinimize MLC segments– Optimized inverse planningOptimized inverse planning

• Make IMRT more accurateMake IMRT more accurate– Better dose calculation (superposition, MC)Better dose calculation (superposition, MC)– Image guidanceImage guidance– Online verification with portal imagingOnline verification with portal imaging– Gating/Tracking to reduce breathing artifactsGating/Tracking to reduce breathing artifacts– Proton and heavy ion IMRTProton and heavy ion IMRT

Change “penalties” or “weight factors”Change “penalties” or “weight factors”

Weight factor approachWeight factor approach

OptimizeOptimize

FF is a single number! is a single number!

Risk2Risk2Risk1Risk1TargetTarget FwFwFwF

Difficulty 1Difficulty 1

• By how much do you change the weight By how much do you change the weight factors, factors, w w ??– Trial and errorTrial and error

Example: Head&NeckExample: Head&Neck

Brainstem

Spinal Cord

Parotis

0 25 50 75 1000

20

40

60

80

100 Plan 1

Target

Spinal Cord

Vo

lum

e (

%)

Dose (Gy)

Plan 2

w=10000

w=1

Difficulty 2Difficulty 2

• ““Sensitivity” of the solution?Sensitivity” of the solution?

Difficulty 3Difficulty 3

Constraint optimization:Constraint optimization:

Solutions may not be “efficient”!Solutions may not be “efficient”!

Example: Head&NeckExample: Head&Neck

Brainstem

Spinal Cord

Parotis

0 25 50 75 1000

20

40

60

80

100 Plan 1 Plan 2

Target

Brainstem

Spinal Cord

Vo

lum

e (

%)

Dose (Gy)

Optimization of the Optimization: SolutionsOptimization of the Optimization: Solutions

1.1. Use Equivalent Uniform Dose (EUD) to Use Equivalent Uniform Dose (EUD) to characterize the dose in every relevant characterize the dose in every relevant structurestructure

2.2. Find efficient (“Pareto optimal”) solutionsFind efficient (“Pareto optimal”) solutions

3.3. Calculate database with representative Calculate database with representative solutions, use interpolationsolutions, use interpolation

Solutions, part 1Solutions, part 1

• Use Equivalent Uniform Dose (EUD)Use Equivalent Uniform Dose (EUD)– A. Niemierko “A generalized concept of A. Niemierko “A generalized concept of

equivalent uniform dose (EUD)” equivalent uniform dose (EUD)” Med. Phys. 26:1100, 1999Med. Phys. 26:1100, 1999

EUD = uniform dose to the organ that leads EUD = uniform dose to the organ that leads to the same effectto the same effect

EUD exampleEUD example

0

25

50

75

100

0 20 40 60

Vo

lum

e [%

]

Dose [Gy]80 100

Question: What is the homogeneous dose that would give the same effect?

Lung:EUD = 25 Gy

Spinal Cord:EUD = 52 Gy

Power-Law (p-Norm) ModelPower-Law (p-Norm) Model

p

i

pii Dv

/1

EUD

“p-norm”

Mohan et al., Med. Phys. 19(4), 933-944, 1992Kwa et al., Radiother. Oncol. 48(1), 61-69, 1998Niemierko, Med. Phys. 26(6), 1100, 1999

Examples:

:

:1

p

p

maxEUD

EUD

D

D

Solutions, part 2Solutions, part 2

• Find efficient (Pareto optimal) solutionsFind efficient (Pareto optimal) solutions

0 25 50 75 1000

20

40

60

80

100

TargetEUD = 70 Gy

Brainstem

Spinal CordEUD = 34 Gy

Vo

lum

e (

%)

Dose (Gy)

EUD=25 Gy

Efficient (Pareto optimal) Plan

EUD=10 Gy

Solutions, part 3Solutions, part 3

• Fill database with solutions for different Fill database with solutions for different combinations of EUD valuescombinations of EUD values(over night)(over night)

SummarySummary

• New concept in IMRT optimizationNew concept in IMRT optimization

• Multi-criteria EUD optimizationMulti-criteria EUD optimization

• Find better solution fasterFind better solution faster

Power-Law (p-Norm) ModelPower-Law (p-Norm) Model

nvv

)1(TD)(TD

Power-law relationship for tolerance dose (TD):

0 25 50 75 1000

20

40

60

80

100 Plan 1

Target

Spinal Cord

Vo

lum

e (

%)

Dose (Gy)

Plan 2EUD=50.2 Gy

EUD=72.4(a=-8)

EUD=4.0(a=-8)

EUD=18.7 Gy