Randomness-aware multiscale models of glioma invasion and treatment

TL;DR

This paper introduces a stochastic multiscale model for glioma growth and invasion, integrating tissue heterogeneity, treatment effects, and uncertainties, with numerical experiments evaluating treatment protocols.

Contribution

It presents a novel stochastic multiscale framework linking microscopic cell dynamics to macroscopic tumor behavior under treatment uncertainties.

Findings

Model captures tumor cell migration influenced by tissue heterogeneity

Numerical experiments evaluate treatment protocols under uncertainty

Framework links microscopic and macroscopic tumor dynamics

Abstract

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.