Abstract

We present an application of a previously developed agent-based glioma model (Chen et al 2009 Biosystems 95 234-42) for predicting spatio-temporal tumor progression using a patient-specific MRI lattice derived from apparent diffusion coefficient (ADC) data. Agents representing collections of migrating glioma cells are initialized based upon voxels at the outer border of the tumor identified on T1-weighted (Gd+) MRI at an initial time point. These simulated migratory cells exhibit a specific biologically inspired spatial search paradigm, representing a weighting of the differential contribution from haptotactic permission and biomechanical resistance on the migration decision process. ADC data from 9 months after the initial tumor resection were used to select the best search paradigm for the simulation, which was initiated using data from 6 months after the initial operation. Using this search paradigm, 100 simulations were performed to derive a probabilistic map of tumor invasion locations. The simulation was able to successfully predict a recurrence in the dorsal/posterior aspect long before it was depicted on T1-weighted MRI, 18 months after the initial operation.