Résumé
The advent of magnetic resonance imaging (MRI) has allowed the follow-up of tumor growth by precise volumetric measurements. Such information about tumor dynamics is, however, usually not fully integrated in the therapeutic management, and the assessment of tumor evolution is still limited to qualitative description. In parallel, computational models have been developed to simulate in silico tumor growth and treatment efficacy. Nevertheless, direct clinical interest of these models remains questionable, and there is a gap between scientific advances and clinical practice. In this paper, WHO grade II glioma will serve as a paradigmatic example to illustrate that computational models allow characterizing tumor dynamics from serial MRIs. The role of these dynamics for both therapeutic management and biological research will be discussed.