Thomas Yankeelov, MathBio Talk
Our lab is focused on developing tumor forecasting methods by integrating advanced imaging technologies with mathematical models to predict tumor growth and treatment response. In this presentation, we will focus on how quantitative magnetic resonance imaging (MRI) data can be employed to calibrate mathematical models built on first-order effects related to well-established “hallmarks” of cancer including proliferation, migration/invasion, vascular status, and drug-related tumor growth inhibition and cell death. In particular, we will present some of our recent results on using these models to build personalized digital twins that provide a rigorous, but practical, methodology for optimizing therapeutic interventions on a patient-specific basis.