Predicting online plan adaptation strategy using radiomics in MR-guided radiotherapy of localized prostate cancer

Motivation: MRI-guided radiotherapy (MRgRT) offers the advantage of superior soft-tissue image contrasts, particularly beneficial for daily online treatment plan adaptation in prostate cancer (PC). However, the decision between “adapt-to-position” (ATP) or “adapt-to-shape” (ATS) is subjective and complicated. Goal(s): This study aims to use radiomics to predict the ATP or ATS adaptation for localized PC. Approach: Daily MRI images from 210 fractions were included. 1023 radiomics features were extracted and used to build a logistic regression model for predicting ATP or ATS adaptations. Results: The MRI radiomics model built was relatively good in objectively predicting ATP and ATS adaptations for MRgRT in localized PC. Impact: Our study showed that MRI radiomics have promising predictive capabilities for determining online adaptation strategies for MRgRT in localized PC. This could enhance workflow efficiency and personalize care by providing quantitative and objective criteria for adaptation strategy determination in MRgRT.