Assessment of Knowledge-Based Planning for Prostate Intensity Modulated Proton Therapy

• DOI: 10.14338/ijpt-20-00088.1
• Publication Date: 2021-06-15T18:00:31Z
• Authors: Yihang Xu; Nellie Brovold; Jonathan Cyriac; Elizabeth Bossart; Kyle Padgett; Michael Butkus; Tejan Diwanj; Adam King; Alan Dal Pra; Matt Abramowitz; Alan Pollack; Nesrin Dogan
• Keywords: Medical physics. Medical radiology. Nuclear medicine; 03 medical and health sciences; impt; 0302 clinical medicine; knowledge-based planning; Nuclear and particle physics. Atomic energy. Radioactivity; R895-920; QC770-798; Original Articles; prostate cancer; 3. Good health

To assess the performance of a proton-specific knowledge based planning (KBPP) model in creation robustly optimized intensity-modulated proton therapy (IMPT) plans for treatment patients with prostate cancer.Forty-five localized cancer, who had previously been treated volumetric modulated arc therapy, were selected and replanned IMPT. A KBPP was generated from results 30 patients, remaining 15 patient used validation. The quality accuracy evaluated model-provided organ-at-risk regression plots metrics. also assessed through comparison expert KBPP-generated IMPT target coverage sparing.The resulting R2 (mean ± SD, 0.87 0.07) between dosimetric geometric features, as well χ2 test (1.17 original estimated data, showed good quality. All clinically acceptable. Compared plans, marginally higher dose-volume indices rectum V65Gy (0.8% 2.94%), but delivered lower dose to bladder (-1.06% 2.9% V65Gy). In addition, achieved hotspot (-0.67Gy 2.17Gy) integral (-0.09Gy 0.3Gy) than did. Moreover, better that demonstrated slightly greater clinical volume V95 (0.1% 0.68%) homogeneity index (-1.13 2.34).The created by are high comparable plans. Furthermore, can generate more-robust more-homogenous compared those More studies need be done validation at more-complicated sites.