Title: Leveraging Quantitative Magnetic Resonance Imaging Data for Tumor-specific Forecasts of Radiotherapy Response.
Speaker: David A. Hormuth II, Research Associate, Oden Institute for Computational Engineering and Sciences, Livestrong Cancer Institutes, The University of Texas at Austin, Austin, Texas
Abstract:
Intra- and inter-tumoral heterogeneity in cancer growth dynamics and vascularity influence tumor response to radiation therapy. Mathematical models that accurately characterize these dynamics could enable the optimization of patient care to address the heterogeneity in tumor properties. While there is a long history of phenomenological and mechanistic mathematical models of tumor and vasculature growth, it is not until recently that these models have had the potential to be personalized for individual subjects. A limitation to existing models is that they often contain model parameters which are impossible or impractical to determine for individual patients. Through non-invasive quantitative magnetic resonance imaging (MRI) methods, such as dynamic contrast enhanced MRI and diffusion weighted MRI, we are now able to quantify (in 3D) tumor properties such as perfusion, vascularity, proliferation, and cellularity for individual patients. These quantitative measures of tumor properties acquired before, during, or after the start of therapy facilitate the calibration (or personalization) of mathematical models for individual subjects. We hypothesize that these subject-specific modeling techniques could deliver the opportunity to predict patient response early in the course of therapy, simulate patient-specific treatment regimens, and eventually optimize or adapt therapy for individual tumors. In this talk, Dr. Hormuth II will present a framework for generating personalized forecasts of tumor and vasculature response to radiotherapy with examples from high-grade gliomas in the pre-clinical and clinical settings.
Attend in person at the Vet Med Small Animal Clinic