Glioblastoma (GBM) is the most frequent and lethal malignant brain tumor in adults. Combined mathematical simulations and on-chip validation of malignant cellular structures formation in GBM has confirmed their synergistic usability to better understand the tumor behavior.

Another modern mathematical model has predicted a relation between tumor’s growth speed, and so the patient outcome, with the width of contrast enhancing areas measured on the pre-surgery post-contrast 3D T1-weighted magnetic resonance images. Other works have hypothesized the role of the tumor’s surface as a driver for growth and infiltration in cancer. A retrospective multi-center study, developed for the validation of the model predictions, has showed that geometrical features obtained from pretreatment T1-weighted images and age predict survival of GBM patients. Adding qualitative information on the extent of resection allowed to substantially improve the predictive value of those measures.

Funding: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

References:

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