Mechanistic model of radiotherapy-induced lung fibrosis using coupled 3D Agent-Based and Monte Carlo simulations

Abstract Mechanistic modelling of normal tissue toxicities is unfolding as an alternative to the phenomenological Normal Tissue Complication Probability models currently used in the clinics that rely exclusively on limited patient data. Among the various approaches, Agent-Based Models (ABMs) are appealing as they provide the means to include patient-specific parameters and simulate long-term effects in complex systems. However, Monte Carlo (MC) tools remain the state-of-the-art for modelling radiation transport and provide measurements of the delivered dose with unmatched precision. In this work, we delineate the implementation of and characterize the first coupled 3D ABM-MC model that mechanistically simulates the onset of the radiation-induced lung fibrosis (RILF) in an alveolar segment. Our model replicates extracellular matrix patterns, RILF severity indexes (RSI) and functional-subunits (FSU) survivals that show qualitative agreement with experimental studies and are consistent with our past results. Moreover, in accordance with experimental results, higher FSUs survival and lower RSI were achieved when a 5-fractions treatment was simulated. Finally, the model showed increased sensitivity to peaked protons dose distributions with respect to flatter ones from photons irradiation. Our work lays thus the groundwork for further investigating the effects of different radiotherapeutic treatments on the onset of RILF via mechanistic modelling.