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An Investigation of Optimizing Proton Energies in IMPT Treatment Planning

W Cao

W Cao1*, G Lim2, X Li3, Y Li4, X Zhang5, (1) UT MD Anderson Cancer Center, Houston, TX, (2) University of Houston, Houston, Texas, (3) UT MD Anderson Cancer Center, Houston, TX, (4) UT MD Anderson Cancer Center, Houston, TX, (5) UT MD Anderson Cancer Center, Houston, TX

TU-A-108-4 Tuesday 8:00AM - 9:55AM Room: 108

In Intensity modulated proton therapy (IMPT), a set of different proton energies of pencil beams are used to create desired dose distributions. The selection of proton energies in the current clinical IMPT treatment planning is determined based on trial and error. In this study, we utilize an optimization approach to find an optimized subset of proton energies out of a given set of candidates. The treatment plan quality of IMPT plans with optimized and non-optimized energy setups will be evaluated.

A mixed integer linear programming based iterative optimization approach was introduced to find optimal proton energies from a given set of energies in IMPT treatment planning. Dosimetric measurements of treatment plans with optimized proton energies were compared with ones with conventional energy setups for four prostate cancer patients retrospectively selected at our institution for this study.

For four prostate cancer cases, no evident difference in dosimetric measurements was found between plans with optimized proton energies and ones with conventional energy setups, in terms of target coverage and critical structure sparing. Importantly, the number of optimized energies was approximately 20% less in average comparing with the number of energies used in conventional IMPT treatment planning. Thus, the IMPT delivery time can be shortened by reducing the energies used IMPT treatment

With a reduction of proton energies that are used in the conventional IMPT treatment planning, we observed that there was no degrading effect in dosimetric performance of prostate IMPT plans in this study. Future studies on larger sized cancer sites may add a higher value to the research on the proton energy optimization problem in improving IMPT treatment delivery efficiency.

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