Semi-Automatic Electric Source Localization of Interictal Discharges During Entire Long-Term Monitoring: A Prospective Study
Abstract number :
3.127
Submission category :
3. Neurophysiology / 3A. Video EEG Epilepsy-Monitoring
Year :
2021
Submission ID :
1826433
Source :
www.aesnet.org
Presentation date :
12/6/2021 12:00:00 PM
Published date :
Nov 22, 2021, 06:54 AM
Authors :
Pieter van Mierlo, PhD - Ghent University; Laurent Spinelli - University Hospital of Geneva; Amir Ghasemi Baroumand - Ghent University; Serge Vulliémoz - University Hospital of Geneva; Margitta Seeck - University Hospital of Geneva
Rationale: The added value of using automated EEG source imaging (ESI) in the presurgical evaluation of epilepsy patients to localize the epileptogenic focus has been shown in several retrospective studies. However, up to date there is no prospective study that investigates the value of automated ESI in the presurgical evaluation.
Methods: The prospective study started in March 2017 in the University Hospital of Geneva. So far 112 patients with mean age of 29 years (range 3-62) were enrolled. All patients underwent long-term video-EEG monitoring with 38 electrodes and a mean duration of 5 days. For each recording an automated ESI report was provided by Epilog NV. These reports include interictal epileptiform discharge (IED) detection, clustering of the detections and source localization at the onset, half-rising phase and peak of the averaged spikes. The source localization of the most relevant cluster, given the patient’s clinical context, was compared to the surgical resection at sub-lobar level.
Results: The mean number of spikes detected per patient was 12.579. Thirty-seven patients who underwent epilepsy surgery had at least 12 months follow-up. In this group 46% had ETLE, 35% had a non-contributive MRI and 86% was seizure-free after surgery. Automated ESI had an accuracy of 81%, with a sensitivity of 81%, a specificity of 80% and odds ratio of 17. In the MRI-negative patients, the accuracy was 83% and the odds ratio was 11.
Conclusions: Automated ESI has a good accuracy to localize the epileptogenic focus in the presurgical evaluation, also in MRI-negative patients.
Funding: Please list any funding that was received in support of this abstract.: Pieter van Mierlo is funded by the Swiss National Science Foundation grants no. CRSII5 180365 and CRSII5 170873. Margitta Seeck is funded by Swiss National Science Foundation grants no. SNSF 163398 and Sinergia 180365. Serge Vulliémoz is funded by Swiss National Science Foundation grants no. 169198, 192749, and CRSII5 170873. The funders were not involved in the study design, in the collection, analysis and interpretation of data, in the writing of the report, or in the decision to submit the abstract for publication.
Neurophysiology