Automated long‐term EEG analysis to localize the epileptogenic zone

摘要

Summary ObjectiveWe investigated the performance of automatic spike detection and subsequent electroencephalogram (EEG) source imaging to localize the epileptogenic zone (EZ) from long-term EEG recorded during video-EEG monitoring. MethodsIn 32 patients, spikes were automatically detected in the EEG and clustered according to their morphology. The two spike clusters with most single events in each patient were averaged and localized in the brain at the half-rising time and peak of the spike using EEG source imaging. On the basis of the distance from the sources to the resection and the known patient outcome after surgery, the performance of the automated EEG analysis to localize the EZ was quantified. ResultsIn 28 out of the 32 patients, the automatically detected spike clusters corresponded with the reported interictal findings. The median distance to the resection in patients with Engel class I outcome was 6.5 and 15?mm for spike cluster 1 and 27 and 26?mm for cluster 2, at the peak and the half-rising time of the spike, respectively. Spike occurrence (cluster 1 vs. cluster 2) and spike timing (peak vs. half-rising) significantly influenced the distance to the resection (p? SignificanceWe showed that automated analysis of long-term EEG recordings results in a high sensitivity and specificity to localize the epileptogenic focus.