Marcel Heers1,2, Sebastian Böttcher1,2, Adam Kalina2,3, Stefan Katletz2,4, Dirk-Matthias Altenmüller1,2, Amir G Baroumand5,6, Gregor Strobbe5, Pieter van Mierlo5,6, Tim J von Oertzen2,4, Petr Marusic2,3, Andreas Schulze-Bonhage1,2, Sándor Beniczky2,7,8, Matthias Dümpelmann1,2. 1. Epilepsy Center, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany. 2. Member of European Reference Network EpiCARE. 3. Department of Neurology, Second Faculty of Medicine, Motol University Hospital, Charles University, Prague, Czech Republic. 4. Department of Neurology 1, Kepler Universitätsklinikum, Johannes Kepler University Linz, Linz, Austria. 5. Epilog, Ghent, Belgium. 6. Medical Image and Signal Processing Group, Department of Electronics and Information Systems, Ghent University, Ghent, Belgium. 7. Department of Clinical Neurophysiology, Danish Epilepsy Center, Dianalund, Denmark. 8. Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark.
Abstract
OBJECTIVES: High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus we compared semiautomated and automated detection of IED types in long-term video-EEG (electroencephalography) monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure-onset zone (SOZ). METHODS: We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40-electrode scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG, as well as visual detections in hdEEG, were compared against visually detected IED types and the SOZ in LTM. RESULTS: Fifty-two of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM, only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. SIGNIFICANCE: Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.
OBJECTIVES: High counts of averaged interictal epileptiform discharges (IEDs) are key components of accurate interictal electric source imaging (ESI) in patients with focal epilepsy. Automated detections may be time-efficient, but they need to identify the correct IED types. Thus we compared semiautomated and automated detection of IED types in long-term video-EEG (electroencephalography) monitoring (LTM) using an extended scalp EEG array and short-term high-density EEG (hdEEG) with visual detection of IED types and the seizure-onset zone (SOZ). METHODS: We prospectively recruited consecutive patients from four epilepsy centers who underwent both LTM with 40-electrode scalp EEG and short-term hdEEG with 256 electrodes. Only patients with a single circumscribed SOZ in LTM were included. In LTM and hdEEG, IED types were identified visually, semiautomatically and automatically. Concordances of semiautomated and automated detections in LTM and hdEEG, as well as visual detections in hdEEG, were compared against visually detected IED types and the SOZ in LTM. RESULTS: Fifty-two of 62 patients with LTM and hdEEG were included. The most frequent IED types per patient, detected semiautomatically and automatically in LTM and visually in hdEEG, were significantly concordant with the most frequently visually identified IED type in LTM and the SOZ. Semiautomated and automated detections of IED types in hdEEG were significantly concordant with visually identified IED types in LTM, only when IED types with more than 50 detected single IEDs were selected. The threshold of 50 detected IED in hdEEG was reached in half of the patients. For all IED types per patient, agreement between visual and semiautomated detections in LTM was high. SIGNIFICANCE: Semiautomated and automated detections of IED types in LTM show significant agreement with visually detected IED types and the SOZ. In short-term hdEEG, semiautomated detections of IED types are concordant with visually detected IED types and the SOZ in LTM if high IED counts were detected.
Authors: Anli A Liu; Simon Henin; Saman Abbaspoor; Anatol Bragin; Elizabeth A Buffalo; Jordan S Farrell; David J Foster; Loren M Frank; Tamara Gedankien; Jean Gotman; Jennifer A Guidera; Kari L Hoffman; Joshua Jacobs; Michael J Kahana; Lin Li; Zhenrui Liao; Jack J Lin; Attila Losonczy; Rafael Malach; Matthijs A van der Meer; Kathryn McClain; Bruce L McNaughton; Yitzhak Norman; Andrea Navas-Olive; Liset M de la Prida; Jon W Rueckemann; John J Sakon; Ivan Skelin; Ivan Soltesz; Bernhard P Staresina; Shennan A Weiss; Matthew A Wilson; Kareem A Zaghloul; Michaël Zugaro; György Buzsáki Journal: Nat Commun Date: 2022-10-12 Impact factor: 17.694