The field of Mathematical NeuroOncology represents a marriage between applied mathematics, clinical oncology, cancer biology, radiology, pathology, artificial intelligence and informatics to enable practical clinical tools to benefit brain tumor patients. This site has evolved out of the Swanson Lab (now based at The Mayo Clinic in Phoenix, Arizona) which has been at the forefront of this field. As this field grows, we will use this site as a portal for access to works in the Mathematical NeuroOncology field from the Swanson Lab and beyond.
Our focus is on: 1) predicting patient-specific tumor growth, 2) seeking patient-specific markers of tumor progression, and, 3) identifying early predictors of response to therapy in individual patients.
Gliomas are diffuse and invasive brain tumors with the nefarious ability to recur despite extensive surgical resection. Chemotherapies are also seldom successful due to hindrance by the intricate capillary structure of the blood brain barrier. Based on a simple mathematical model of glioma growth and diffusion, below is a simulated prediction of the degree to which MRI underestimates the actual extent of diffuse invasion of the brain by glioma cells.
Inverse Mapping of Spatial-Temporal Molecular Heterogeneity from Imaging Phenotype
Funded by the NSF
Quantifying Multiscale Competitive Landscapes of Clonal Diversity in Glioblastoma
Funded by the NCI Cancer Systems Biology Consortium
Days Gained: An Early Dynamic Indicator of Treatment Response
Funded by the Ben and Catherine Ivy Foundation
The ENDURES Study: Environmental Dynamics Underlying Responsive Extreme Survivors of Glioblastoma
Funded by the James D. McDonnell Foundation