Proliferation-invasion (reaction-diffusion) models of glioma
Gliomas grow by both dividing and migrating through the brain, and a two-parameter equation fitted to a patient's MRI scans estimates how far invisible cells have spread, which can guide how much brain to irradiate and how fast the tumour will grow.
Overview
Kristin Swanson, James Murray and colleagues modelled glioblastoma as a reaction-diffusion process: cells proliferate at rate rho and diffuse at rate D, faster along white matter. Fitting the two parameters to serial MRI gives a patient-specific 'velocity' of growth and an estimate of tumour cell density beyond the visible edge, which has been used to individualise radiotherapy margins, to define 'days gained' as a response measure, and to predict survival. The model is the most clinically tested biophysical tumour model but requires two pretreatment scans and simplifies the biology of invasion.
How it works
Partial differential equation dc/dt = grad(D grad c) + rho·c(1 - c/K): net growth from proliferation and spatial spread from diffusion, with D higher in white matter.
- Patient-specific from routine MRI
- Predicts invisible spread beyond the scan
- Tested in radiotherapy planning and response assessment
- Needs two scans before treatment
- Ignores immune and vascular effects
- Not yet in routine planning systems
Latest papers
topQuery for this technology: (TITLE:"Proliferation-invasion reaction-diffusion models of glioma" OR ABSTRACT:"Proliferation-invasion reaction-diffusion models of glioma") AND (cancer OR tumor OR tumour OR oncology OR carcinoma OR lymphoma OR leukemia OR leukaemia OR myeloma OR sarcoma OR melanoma OR glioma). Results are unfiltered search hits about Proliferation-invasion (reaction-diffusion) models of glioma, not a curated reading list.
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