Magnetic Resonance Oncometabolic Imaging in DLGG Beyond the Image

Increasing knowledge in both genomic-metabolic and magnetic resonance imaging fields have generated more and more data from year to the next. In addition to give accurate statistical analysis, mathematic tools appear mandatory to (1) allow parameter extraction from MR sequences; (2) provide comprehensive and coherent analysis biodynamic systems, as it is the case for diffuse low-grade glioma: to fit their metabolic evolution for predicting their malignant transformation.