In this work, we develop a stochastic multiscale model for glioma growth and invasion in the brain, incorporating the effects of therapeutic interventions. The model accounts for tumor cell migration influenced by brain tissue heterogeneity and anti-crowding mechanisms, while explicitly addressing treatment-related uncertainties through stochastic processes. Starting from a microscopic description of individual cell dynamics, we derive the corresponding system of macroscopic random reaction-diffusion-taxis equations governing cell density and tissue evolution. Finally, we conduct several numerical experiments to assess the efficacy of different treatment protocols, evaluated with respect to both established and newly proposed clinical criteria and measurable outcomes.
@article{arxiv.2602.08008,
title = {Randomness-aware multiscale models of glioma invasion and treatment},
author = {Martina Conte and Sandesh Hiremath and Christina Surulescu},
journal= {arXiv preprint arXiv:2602.08008},
year = {2026}
}