Project Grant 2625744

The National Science Foundation Division of Mathematical Sciences awarded Worcester Polytechnic Institute $247,931 on January 1, 2027, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical foundations for adaptable digital twins of glioblastoma.

The project will create patient-specific computational models that integrate individual patient data, generate predictions, and quantify uncertainty in those predictions. Digital twin development for brain disorders presents technical challenges: clinically important processes such as cell infiltration are not directly observable through standard imaging technologies, mechanistic models describing the disorder may be incomplete, and both data and underlying science evolve over time, requiring the model to adapt to new knowledge and imaging modalities. The project uses glioblastoma—an aggressive brain cancer whose cells infiltrate tissue beyond the tumor region visible on standard MRI imaging—as a test case. The methodology will extend to other infiltrative tumors and neurodegenerative diseases including Alzheimer's disease and may support evaluation of new medical technologies.

The technical work addresses four coupled mathematical problems: identifying mechanistic models from indirect imaging data, calibrating patient-specific parameters, quantifying prediction uncertainty, and adapting the pipeline as scientific knowledge and imaging modalities evolve. The unifying framework is the bilevel local operator (BILO) methodology. The project will release frameworks and trained models openly and train students from high school through graduate school at the interface of applied mathematics, computer science, and biomedicine.

Performance occurs in Worcester, Massachusetts with completion targeted for December 31, 2029.