The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread

Viktor Jirsa (1) , T. Proix (1) , D. Perdikis (1) , M. M. Woodman (1) , H. Wang (1) , J. Gonzalez-Martinez (2) , C. Bernard , C. Bénar (1) , Maxime Guye (3, 4) , Patrick Chauvel (3) , Fabrice Bartolomei (5, 1)

1 INS - Institut de Neurosciences des Systèmes
2 Cleveland Clinic
3 CRMBM - Centre de résonance magnétique biologique et médicale
4 CEMEREM - Centre d'Exploration Métabolique par Résonance Magnétique [Marseille]
5 TIMONE - Hôpital de la Timone [CHU - APHM]

Individual variability has clear effects upon the outcome of therapies and treatment approaches. The customization of healthcare options to the individual patient should accordingly improve treatment results. We propose a novel approach to brain interventions based on personalized brain network models derived from non-invasive structural data of individual patients. Along the example of a patient with bitemporal epilepsy, we show step by step how to develop a Virtual Epileptic Patient (VEP) brain model and integrate patient-specific information such as brain connectivity, epileptogenic zone and MRI lesions. Using high-performance computing, we systematically carry out parameter space explorations, fit and validate the brain model against the patient's empirical stereotactic EEG (SEEG) data and demonstrate how to develop novel personalized strategies towards therapy and intervention.

Domains: Life Sciences [q-bio]; Neurons and Cognition [q-bio.NC]; Life Sciences [q-bio]; Bioengineering

Viktor Jirsa, T. Proix, D. Perdikis, M. M. Woodman, H. Wang, et al.. The Virtual Epileptic Patient: Individualized whole-brain models of epilepsy spread. NeuroImage, 2016, 145, pp.377-388. ⟨10.1016/j.neuroimage.2016.04.049⟩. ⟨hal-01425499⟩