Software tool offers insights into the epileptogenic zone!

Published on October 13, 2022

Imagine you’re planning a road trip, but you’re not sure which route to take. You could rely on your own experience and knowledge of the area, or you could use a GPS system that guides you based on data from other travelers who have taken similar journeys. In the field of epilepsy surgery, a similar approach is now available. Around one third of epilepsies don’t respond to medication, and for these patients, surgical removal of the epileptogenic zone (EZ) can provide relief. However, locating the EZ accurately is crucial. To address this challenge, researchers have developed an open-source software tool that harnesses data from retrospective clinical cases to provide clinicians with a visual map of the EZ based on seizure semiologies observed in each patient. By overlaying this probabilistic map onto the patient’s images, clinicians can better infer the location of the symptomatogenic zone, which may overlap with the EZ. This tool has the potential to standardize surgical planning and improve outcomes for epilepsy patients. To learn more about this exciting research, check out the original article!

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.

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