EPINETLAB:a software for seizure-onset zone identification from intracranial EEG signal in epilepsy

Abstract

The pre-operative workup of patients with drug-resistant epilepsy requires in some candidates the identification from intracranial EEG (iEEG) of the seizure-onset zone (SOZ), defined as the area responsible of the generation of the seizure and therefore candidate for resection. High-frequency oscillations (HFOs) contained in the iEEG signal have been proposed as biomarker of the SOZ. Their visual identification is a very onerous process and an automated detection tool could be an extremely valuable aid for clinicians, reducing operator-dependent bias and computational time. In this manuscript we present the EPINETLAB software, developed as a collection of routines integrated in the EEGLAB framework that aim to provide clinicians with a structured analysis pipeline for HFOs detection and SOZ identification. The tool implements an analysis strategy developed by our group and underwent a preliminary clinical validation that identifies the HFOs area by extracting the statistical properties of HFOs signal and that provides useful information for a topographic characterization of the relationship between clinically defined SOZ and HFO area. Additional functionalities such as inspection of spectral properties of ictal iEEG data and import and analysis of source-space MEG data were also included. EPINETLAB was developed with user-friendliness in mind to support clinicians in the identification and quantitative assessment of HFOs in iEEG and source space MEG data and aid the evaluation of the SOZ for pre-surgical assessment.

Publication DOI: https://doi.org/10.3389/fninf.2018.00045
Divisions: College of Health & Life Sciences
College of Health & Life Sciences > School of Psychology
College of Health & Life Sciences > Aston Institute of Health & Neurodevelopment (AIHN)
College of Health & Life Sciences > Clinical and Systems Neuroscience
Additional Information: © 2018 Quitadamo, Foley, Mai, de Palma, Specchio and Seri. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Funding: This study has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant agreement No. 655016.
Uncontrolled Keywords: EEGLAB,Epilepsy,high-frequency oscillations,Seizure-onset zone,iEEG,stereo-EEG
Publication ISSN: 1662-5196
Last Modified: 18 Mar 2024 08:25
Date Deposited: 26 Jun 2018 12:45
Full Text Link:
Related URLs: https://www.fro ... .00045/abstract (Publisher URL)
PURE Output Type: Article
Published Date: 2018-07-11
Accepted Date: 2018-06-21
Authors: Quitadamo, Lucia Rita (ORCID Profile 0000-0003-1877-4672)
Foley, Elaine (ORCID Profile 0000-0003-4459-9855)
Mai, Roberto
De Palma, Luca
Specchio, Nicola
Seri, Stefano (ORCID Profile 0000-0002-9247-8102)

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