Indications, Techniques, and Outcomes of Robot-Assisted Insular Stereo-Electro-Encephalography: A Review - De Barros, Amaury; Zaldivar-Jolissaint, Julien Francisco; Hoffmann, Dominique; Job-Chapron, Anne-Sophie; Minotti, Lorella; Kahane, Philippe; De Schlichting, Emmanuel; Chabardès, Stephan (Frontiers in Neurology, 2020)
Stereo-electro-encephalography (SEEG) is an invasive, surgical, and electrophysiological method for three-dimensional registration and mapping of seizure activity in drug-resistant epilepsy. It allows the accurate analysis of spatio-temporal seizure activity by multiple intraparenchymal depth electrodes. The technique requires rigorous non-invasive pre-SEEG evaluation (clinical, video-EEG, and neuroimaging investigations) in order to plan the insertion of the SEEG electrodes with minimal risk and maximal recording accuracy. The resulting recordings are used to precisely define the surgical limits of resection of the epileptogenic zone in relation to adjacent eloquent structures. Since the initial description of the technique by Talairach and Bancaud in the 1950's, several techniques of electrode insertion have been used with accuracy and relatively few complications. In the last decade, robot-assisted surgery has emerged as a safe, accurate, and time-saving electrode insertion technique due to its unparalleled potential for orthogonal and oblique insertion trajectories, guided by rigorous computer-assisted planning. SEEG exploration of the insular cortex remains difficult due to its anatomical location, hidden by the temporal and frontoparietal opercula. Furthermore, the close vicinity of Sylvian vessels makes surgical electrode insertion challenging. Some epilepsy surgery teams remain cautious about insular exploration due to the potential of neurovascular injury. However, several authors have published encouraging results regarding the technique's accuracy and safety in both children and adults. We will review the indications, techniques, and outcomes of insular SEEG exploration with emphasis on robot-assisted implantation.