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What’s next in IMRT? - Optimizing the Optimization - T. Bortfeld 1, C. Thieke 1,2, K.-H. Küfer 3, H. Trinkaus 3 1 Department of Radiation Oncology, Massachusetts.

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Presentation on theme: "What’s next in IMRT? - Optimizing the Optimization - T. Bortfeld 1, C. Thieke 1,2, K.-H. Küfer 3, H. Trinkaus 3 1 Department of Radiation Oncology, Massachusetts."— Presentation transcript:

1 What’s next in IMRT? - Optimizing the Optimization - T. Bortfeld 1, C. Thieke 1,2, K.-H. Küfer 3, H. Trinkaus 3 1 Department of Radiation Oncology, Massachusetts General Hospital, Boston, USA 2 Department of Medical Physics, Deutsches Krebsforschungszentrum, Heidelberg, Germany, 3 Fraunhofer Institut für Techno- und Wirtschaftsmathematik, Kaiserslautern, Germany

2 Current technical/physical developments in IMRT Make IMRT more efficientMake IMRT more efficient –Streamlined, integrated solutions –Minimize MLC segments –Optimized inverse planning Make IMRT more accurateMake IMRT more accurate –Better dose calculation (superposition, MC) –Image guidance –Online verification with portal imaging –Gating/Tracking to reduce breathing artifacts –Proton and heavy ion IMRT

3 Current technical/physical developments in IMRT Make IMRT more efficientMake IMRT more efficient –Streamlined, integrated solutions –Minimize MLC segments –Optimized inverse planning Make IMRT more accurateMake IMRT more accurate –Better dose calculation (superposition, MC) –Image guidance –Online verification with portal imaging –Gating/Tracking to reduce breathing artifacts –Proton and heavy ion IMRT

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10 Change “penalties” or “weight factors”

11 Weight factor approach Optimize F is a single number!

12 Difficulty 1 By how much do you change the weight factors, w ?By how much do you change the weight factors, w ? –Trial and error

13 Example: Head&Neck Brainstem Spinal Cord Parotis

14 0255075100 0 20 40 60 80 100 Plan 1 Target Spinal Cord Volume (%) Dose (Gy) Plan 2 w=10000 w=1

15 Difficulty 2 “Sensitivity” of the solution?“Sensitivity” of the solution?

16 Difficulty 3 Constraint optimization: Solutions may not be “efficient”!

17 Example: Head&Neck Brainstem Spinal Cord Parotis

18 0255075100 0 20 40 60 80 100 Plan 1 Plan 2 Target Brainstem Spinal Cord Volume (%) Dose (Gy)

19 Optimization of the Optimization: Solutions 1.Use Equivalent Uniform Dose (EUD) to characterize the dose in every relevant structure 2.Find efficient (“Pareto optimal”) solutions 3.Calculate database with representative solutions, use interpolation

20 Solutions, part 1 Use Equivalent Uniform Dose (EUD)Use Equivalent Uniform Dose (EUD) –A. Niemierko “A generalized concept of equivalent uniform dose (EUD)” Med. Phys. 26:1100, 1999 EUD = uniform dose to the organ that leads to the same effect

21 EUD example 0 25 50 75 100 0204060 Volume [%] 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

22 Power-Law (p-Norm) Model “p-norm” Mohan et al., Med. Phys. 19(4), 933-944, 1992 Kwa et al., Radiother. Oncol. 48(1), 61-69, 1998 Niemierko, Med. Phys. 26(6), 1100, 1999 Examples:

23 Solutions, part 2 Find efficient (Pareto optimal) solutionsFind efficient (Pareto optimal) solutions

24 0255075100 0 20 40 60 80 100 Target EUD = 70 Gy Brainstem Spinal Cord EUD = 34 Gy Volume (%) Dose (Gy) EUD=25 Gy Efficient (Pareto optimal) Plan EUD=10 Gy

25 Solutions, part 3 Fill database with solutions for different combinations of EUD values (over night)Fill database with solutions for different combinations of EUD values (over night)

26 Summary New concept in IMRT optimizationNew concept in IMRT optimization Multi-criteria EUD optimizationMulti-criteria EUD optimization Find better solution fasterFind better solution faster

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30 Power-Law (p-Norm) Model Power-law relationship for tolerance dose (TD):

31 0255075100 0 20 40 60 80 100 Plan 1 Target Spinal Cord Volume (%) Dose (Gy) Plan 2 EUD=50.2 Gy EUD=72.4 (a=-8) EUD=4.0 (a=-8) EUD=18.7 Gy


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