Combined photon-proton modeling of radiation-induced brain imaging changes supports variability in proton relative biological effectiveness and increased periventricular radiosensitivity

Abstract

Purpose: Recent proton-only investigations of radiation-induced contrast enhancements (RICE) in brain tumor patients indicated variability in proton relative biological effectiveness (RBE) and increased radiosensitivity of the periventricular region (PVR). Because RBE is defined relative to a reference radiation, these studies required assumptions on the photon dose-response relationship. This study aimed to validate proton RBE variability and PVR radiosensitivity using predictive modeling of RICE in a combined photon-proton cohort. Methods and Materials: Predictive models for RICE detected on follow-up magnetic resonance imaging were developed in 152 intracranial tumor patients treated with photons or protons. Logistic regression was applied at the voxel level to model spatial occurrence and at the patient level to model incidence. A clinical RBE model was derived from voxel-wise comparisons of estimated risk between photon and proton irradiation. Results: In total, 128 RICE of various grades occurred in 64 patients. Voxel-level modeling validated absorbed dose (D), D multiplied by dose-averaged linear energy transfer (LETd) for proton therapy, and PVR as independent predictors of RICE. The model implied a variable proton RBE described by RBE=1+m$\cdot$LETd, with m=0.10 $μ$m/keV. At the patient level, the PVR D2ml based on this RBE achieved the highest predictive performance. Conclusions: RICE was spatially associated with dose and PVR proximity across photon and proton therapy, with an additional LET-dependent component after proton therapy. The cross-modality framework validates proton RBE variability against an observed photon reference rather than predefined reference assumptions, and supports PVR radiosensitivity as modality-independent. Accounting for variable proton RBE and the PVR as an organ at risk may improve risk assessment and mitigation of radiation-induced side effects.