Room: ePoster Forums
Purpose: To explore the potential for dose-averaged linear energy transfer (LETd) redistribution of LET-guided planning strategies for localized prostate cancer receiving spot scanning proton therapy.
Methods: Five LET-guided plans were created to mimicked the dose distribution of the treated plan using two lateral opposing fields covering the full target (2-field FT): (1) 4-field FT; (2) 6-field FT; (3) 2-field splitting the target (2-field ST); (4) 4-field ST; (5) 6-field ST. All beam parameters were designed in Eclipse treatment planning system. Robustness-incorporated multi-field optimization was applied in FT plans, and in-house developed Monte Carlo- based optimizer was used in ST plans. LETd was obtained by recalculating the plan in fast dose calculator (FDC). FDC calculated dose and LETd were compared.
Results: The LET-guided plans were similar to the treated plans in terms of target coverage and dose to the critical organs. Under the conventional beam arrangement that covers the full target, increasing the number of fields reduced the high dose volume of the critical organs peripheral to the target. Mean LETd of CTV were 2.83 keV/um and 2.76 keV/um for 4-field FT and 6-field FT versus 2.58 keV/um for the treated plan. Using field patching approach that split the target greatly improved the mean LETd of CTV by 42.1%, 62.7%, 63.5% for 2-field ST, 4-field ST and 6-field ST respectively. Maximum decrease in mean LETd of rectum and bladder were observed for 4-field FT (37.8%) and 6-field FT (60.4%) compared with the original planning strategy.
Conclusion: We demonstrate that increasing the number of LET-friendly beams and placing the distal end inside the target have the potential to achieve LET enhancement in the tumor without introducing high LET elements in the critical organs. LET-guided planning strategies could be used as a surrogate of LET optimization.
Funding Support, Disclosures, and Conflict of Interest: This study is partly funded by National Key Research and Development Program of China (Grant 2016YFC0105409)