Patient-specific biomathematical model to predict benefit of resection in human gliomas.

e13017 Background: Gliomas are incurable, primary brain tumors noted for their invasion of brain parenchyma. Our goal was to apply a biomathematical model to estimate the overall tumor invasiveness on an individual basis and determine whether the estimated number of residual glioma cells after resection of any extent is predictive of survival. Methods: Estimates of net rates of proliferation (ρ) and diffusion (D) of glioma cells, based on a biomathematical model of cell density, yield a ratio describing relative invasiveness (ρ/D). This metric was derived for 185 contrast enhancing gliomas from pretreatment MRIs. The residual MRI-detectable volume was combined with the ρ/D tuned to each patient's tumor to allow estimation of the number of glioma cells remaining post-resection. The patients were split into three cohorts by ρ/D values. Within each cohort, all possible cut-off values were considered as a possible threshold between low and high residual patient groups. Log-rank tests were performed for each p...