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Updated: Nov 6, 2025

Author Spotlight: Advancing Pediatric Epilepsy Surgery in Children Through Novel Biomarkers and Enhanced Localization
Published on: September 20, 2024
Automated ictal EEG source imaging: A retrospective, blinded clinical validation study
Amir G Baroumand1, Anca A Arbune2, Gregor Strobbe3
1Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Campus UZ Corneel Heymanslaan 10, 9000 Ghent, Belgium; Epilog NV, Vlasgaardstraat 52, 9000 Ghent, Belgium.
Objective:
EEG source imaging (ESI) is a validated tool in the multimodal workup of patients with drug resistant focal epilepsy. However, it requires special expertise and it is underutilized. To circumvent this, automated analysis pipelines have been developed and validated for the interictal discharges. In this study, we present the clinical validation of an automated ESI for ictal EEG signals.
Methods:
We have developed an automated analysis pipeline of ictal EEG activity, based on spectral analysis in source space, using an individual head model of six tissues. The analysis was done blinded to all other data. As reference standard, we used the concordance with the resected area and one-year postoperative outcome.
Results:
We analyzed 50 consecutive patients undergoing epilepsy surgery (34 temporal and 16 extra-temporal). Thirty patients (60%) became seizure-free. The accuracy of the automated ESI was 74% (95% confidence interval: 59.66-85.37%).
Conclusions:
Automated ictal ESI has a high accuracy for localizing the seizure onset zone.
Significance:
Automating the ESI of the ictal EEG signals will facilitate implementation of this tool in the presurgical evaluation.
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