Program Information
LET-Based Adjustment of IMPT Plans Using Prioritized Optimization
J Unkelbach1*, P Botas1,3 , N Qin2 , X Jia2 , D Giantsoudi1 , H Paganetti1 , (1) Massachusetts General Hospital, Boston, MA, (2) The University of Texas Southwestern Medical Ctr, Dallas, TX, (3) Heidelberg University, Heidelberg, Germany
Presentations
TH-CD-209-6 (Thursday, August 4, 2016) 10:00 AM - 12:00 PM Room: 209
Purpose: In-vitro experiments suggest an increase in proton relative biological effectiveness (RBE) towards the end of range. However, proton treatment planning and dose reporting for clinical outcome assessment has been based on physical dose and constant RBE. Therefore, treatment planning for intensity-modulated proton therapy (IMPT) is unlikely to transition radically to pure RBE-based planning. We suggest a hybrid approach where treatment plans are initially created based on physical dose constraints and prescriptions, and are subsequently altered to avoid high linear energy transfer (LET) in critical structures while limiting the degradation of the physical dose distribution.
Methods: To allow fast optimization based on dose and LET we extended a GPU-based Monte-Carlo code towards providing dose-averaged LET in addition to dose for all pencil beams. After optimizing an initial IMPT plan based on physical dose, a prioritized optimization scheme is used to modify the LET distribution while constraining the physical dose objectives to values close to the initial plan. The LET optimization step is performed based on objective functions evaluated for the product of physical dose and LET (LETxD). To first approximation, LETxD represents a measure of the additional biological dose that is caused by high LET. Regarding optimization techniques, LETxD has the advantage of being a linear function of the pencil beam intensities.
Results: The method is applicable to treatments where serial critical structures with maximum dose constraint are located in or near the target. We studied intra-cranial tumors (high-grade meningiomas, base-of-skull chordomas) where the target (CTV) overlaps with the brainstem and optic structures. Often, high LETxD in critical structures can be avoided while minimally compromising physical dose planning objectives.
Conclusion:LET-based re-optimization of IMPT plans represents a pragmatic approach to bridge the gap between purely physical dose-based and RBE-based planning. It can be realized with fast GPU-based Monte-Carlo dose calculation.
Funding Support, Disclosures, and Conflict of Interest: The project was in part supported by NIH grants U19 CA 021239-36 and C06 CA 059267.
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