A Mechanistic Model of Brain Necrosis Progression Based on Vascular Heterogeneity.

purposeBrain radionecrosis (RN) is a significant late toxicity of radiation therapy, yet its progression remains challenging to predict because of patient-specific factors. This study develops a mechanistic model to simulate RN expansion focusing on vascular heterogeneity. METHODS AND MATERIALS: A 3-dimensional cellular automaton (CA) model was developed to simulate RN progression, based on the assumption that vascular heterogeneity drives its spatial dynamics. Patient-specific vasculature maps were generated by registering a synthetic brain phantom to magnetic resonance imaging-derived segmentations. Microvessel length density (L

resultsThe model successfully predicted RN expansion patterns, achieving area under the curve values of 0.87 to 0.95 in validation cases. Simulated necrotic regions exhibited anisotropic expansion influenced by local vascular density, supporting the vascular hypothesis. Patient-specific posterior distributions for progression rate reflected wide interpatient variability, whereas the necrotic neighboring effect had a narrower range. The model consistently identified high-risk voxels, with predicted necrotic regions overlapping observed RN in FU imaging.

conclusionsThis study presents a mechanistic model that integrates vascular heterogeneity to predict RN progression, providing interpretable, patient-specific risk maps. It extends RN evolution modeling beyond dose-based metrics, potentially aiding in refining treatment planning and adaptive FU strategies to minimize radiation-induced toxicity.