|Awarded On||February 16, 2022|
|Title||Imaging-informed, biophysical computational modeling to forecast tumor progression in gliomas|
|Award Mechanism||Individual Investigator Research Awards for Computational Biology|
|Institution/Organization||The University of Texas at Austin|
|Principal Investigator/Program Director||David Hormuth|
|Cancer Sites||Brain and Other Nervous System|
The vision for this proposal is to develop and validate a clinical-computational framework to predict and spatially-map more aggressive and treatment-resistant regions to enable personalized treatment in patients receiving radiation therapy for gliomas. We seek to accomplish this goal through the integration of multiparametric magnetic resonance imaging (mpMRI) data with mechanism-based mathematical modeling to predict disease response. This will enable clinicians to forecast tumor behavior during the course of radiotherapy (RT) instead of merely assessing post treatment.
The ability to predict spatiotemporal disease progression creates a paradigm shift as it enables timely adaptations of t...