Applying an MRI-based mathematical model to predict the response of cervical cancer to chemoradiation: Preliminary results

Motivation: Cervical cancer patients have a 20-30% risk of residual disease after standard-of-care chemoradiation, so there is a need for optimized therapeutic interventions. Goal(s): We aim to predict response of individual cervical cancer patients to chemoradiation using a mathematical model calibrated with quantitative MRI data. Approach: We calibrated a reaction-diffusion model of tumor cellularity with MRI data before (V1) and two weeks into chemoradiation (V2). The calibrated model predicted patient-specific tumor status after five weeks of treatment (V3). Results: For a responder and non-responder, the differences between the observed and predicted percent change in tumor cellularity from V1 to V3 were less than 10%. Impact: Our biology-based mathematical model using quantitative MRI data has the potential to accurately predict tumor response to chemoradiation for patients with locally advanced cervical cancer.