The goal of this clinical trial is to improve non-invasive identification of epileptogenic networks in drug-resistant epileptic patient.
The investigators aim to compare epileptogenic network identification with stereo-EEG (used as glod standard) with the identification of the same network using advanced MRI (rs-fMRI, microstructural analysis of white matter, ...). The main goals are to:
1. Compare the accuracy of network identification. 2. Analyse the effect of the MRI sequences on candidates selection and target identification.
Participants will already have been selected for stereoEEG and will undergo a supplementary MRI (about 1h) with the additional MRI sequences. Follow-up MRI are scheduled for patient undergoing a second, therapeutic epileptic surgery.
Patient suffering from drug-resistant epilepsy
Patient already selected for SEEG implantation as part of their epileptic networks
Patient excluded from SEEG (pregnant women, children too young for the procedure, patient unable to undergo the procedure)
Contra-indication for MRI
Single group
Advanced MRI
Deviceresting-state functional MRI, diffusion with advanced post-processing (microstructure analysis), myelin mapping
Network identification with MRI
Analysis of the anatomical overlap of radiological network (with MRI) and the electrophysiological network (with SEEG) using coregistration and a sublobar analysis. Overlap will be quantified in %.
Prognosis of network targetting with surgery
Analysis of the impact on epileptic outcome in accordance with effect of the surgery on the network. The impact of the surgery on the network will be assessed by coregistration to determine which part of the network has been removed or disconnected. The epileptic outcome will be assessed using the Engel classification
Interest of adding epileptic network radiological analysis in a standard epileptic work-up
Analyse the impact on therapeutic and/or diagnostic decision of the network radiological analysis in a standard clinical practice. This impact will be assessed by measuring the change in the type of decision (further work-up, invasive EEG, "curative" surgery, "palliative" surgery or no modification) or the modification in the extent of surgery (more/less electrodes for invasive EEG, more/less tissue targeted with surgery)
Network quantification
Analysis of the strength of the network using radiological data (r², Z-score, diffusion metrics obtained via microfingerprinting such as fiber volume fraction and fiber fraction) vs electrophysiological metrics (epileptogenic index, h²)
Network regulation with surgery
Analysis of the impact of the surgery on the radiological parameters of the network cited in outcome 4 (r² and Z-score for rsfMRI, number of tracts for tractography and strenght of tract with fiber fraction and fiber volume fraction for microfingerprinting)
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