Forecasting response of high-grade glioma patients to radiation therapy
The focus of this project is to translate our efforts at the pre-clinical level to the clinical setting. The longterm vision is to improve patient outcomes through the use of accurate predictive models personalized for each patient
Image-driven models of tumor growth in the pre-clinical setting
While not perfect, the pre-clinical setting is a great area to explore optimal ways to incorporate different imaging (MRI, PET, microscopy, etc) with mathematical models of tumor growth and response.
Repeatable & reproducible cancer imaging methods
Repeatable and reproducible approaches for acquiring and analyzing images is crucial for clinical decision making and for inclusion in mathematical models.