A Monte Carlo based radiation response model to assess variability of clinical RBE in proton therapy

The clinical implementation of a variable relative biological effectiveness (RBE) in proton therapy is currently controversially discussed. First clinical evidence indicates a variable proton RBE, which needs to be verified. In this study, a radiation response model for assessing clinical RBE variability is established. The model was applied to four selected glioma patients (grade III) treated with adjuvant radio(chemo)therapy and who developed late morphological image changes on T1-weighted contrast-enhanced (T1w-CE) magnetic resonance (MR) images within approximately two years of recurrence-free follow-up. The image changes were correlated voxelwise with dose and linear energy transfer (LET) values using univariable and multivariable logit functions. The model performance was assessed by the area-under-the-curve (AUC) performing a leave-one-out cross validation. The tolerance dose TD50 at which 50% of patient voxel experienced toxicity was interpolated from the model. A Monte Carlo (MC) framework was developed to simulate dose and LET distributions, which includes variance reduction (VR) techniques to decrease computation time. Its reliability and accuracy was evaluated based on dose calculations of the clinical treatment planning system (TPS) as well as absolute dose measurements performed in the patient specific quality assurance.
Morphological image changes were related to a combination of dose and LET. The multivariable model revealed a cross-validated AUC of 0.88 (95% confidence interval 0.80 – 0.95). The TD50 decreased linearly with increasing LET indicating an increase in biological effectiveness. The MC framework reliably predicted average TPS dose within the clinical target volume as well as absolute water phantom dose measurements within 2% accuracy using dedicated VR settings.
The observed correlation of dose and LET with late brain tissue damage suggests considering RBE variability for predicting chronic radiation-induced brain toxicities. The MC framework simulates precisely and time-efficiently radiation fields in patients. Hence, this study encourages and enables in-depth patient evaluation to assess the variability of clinical proton RBE.