Mathematical modeling of low-grade glioma

Magnetic resonance imaging can be used to quantify, low-grade glioma growth with millimetric accuracy Mathematical modeling helps to analyze individual glioma growth curves and tumor dynamics. Here we focus on the most extensively studied model, based on a proliferation-diffusion equation. We examine how this model offers a new quantitative approach to the natural history of low-grade glioma, including tumor kinetics and other well-known prognostic factors. This approach, based on quantitative imaging coupled with mathematical modeling, has the potential to help optimize treatment strategies.