AUTHOR=Pérez-García Fernando , Alim-Marvasti Ali , Romagnoli Gloria , Clarkson Matthew J. , Sparks Rachel , Duncan John S. , Ourselin Sébastien TITLE=Software tool for visualization of a probabilistic map of the epileptogenic zone from seizure semiologies JOURNAL=Frontiers in Neuroinformatics VOLUME=16 YEAR=2022 URL=https://www.frontiersin.org/journals/neuroinformatics/articles/10.3389/fninf.2022.990859 DOI=10.3389/fninf.2022.990859 ISSN=1662-5196 ABSTRACT=

Around one third of epilepsies are drug-resistant. For these patients, seizures may be reduced or cured by surgically removing the epileptogenic zone (EZ), which is the portion of the brain giving rise to seizures. If noninvasive data are not sufficiently lateralizing or localizing, the EZ may need to be localized by precise implantation of intracranial electroencephalography (iEEG) electrodes. The choice of iEEG targets is influenced by clinicians' experience and personal knowledge of the literature, which leads to substantial variations in implantation strategies across different epilepsy centers. The clinical diagnostic pathway for surgical planning could be supported and standardized by an objective tool to suggest EZ locations, based on the outcomes of retrospective clinical cases reported in the literature. We present an open-source software tool that presents clinicians with an intuitive and data-driven visualization to infer the location of the symptomatogenic zone, that may overlap with the EZ. The likely EZ is represented as a probabilistic map overlaid on the patient's images, given a list of seizure semiologies observed in that specific patient. We demonstrate a case study on retrospective data from a patient treated in our unit, who underwent resective epilepsy surgery and achieved 1-year seizure freedom after surgery. The resected brain structures identified as EZ location overlapped with the regions highlighted by our tool, demonstrating its potential utility.