Data-Driven EEG Informed Functional MRI Combined with Network Analysis Successfully Identifies the Seizure Onset Zone

Pauly Ossenblok*, Albert Colon, Liesbeth Geerts, Paul Boon, Petra van Houdt, Jan de Munck

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

A data-driven network analysis strategy was developed to apply EEG-informed functional MRI to identify the seizure onset zone in the presurgical work-up of epilepsy patients (n = 10). Instead of voxel-wise general linear model analysis the time series of independent components were correlated with the interictal epileptic discharges density function, yielding the so-called epileptic network. We used eigenvector centrality mapping and a symmetry index to detect the epileptic independent component (ICE) out of the epileptic network. The location of the ICE was for 9 of the 10 patients studied concordant with the clinical hypothesis. Moreover, the clinical evaluation including the outcome of surgery indicated successful localization of the ICE for 6 out of 8 patients who had a resection. The robustness of the methods used to identify the ICE was demonstrated by evaluating the results of the patient study against the results of similar network analysis procedures applied to the functional MRI sequences of 10 healthy controls. In conclusion, the data-driven network analysis strategy successfully identifies the ICE. The concordance of the ICE with the clinical information, including outcome of the resection of the patients, is in support of the usefulness of EEG-fMRI as initial diagnostic tool in the presurgical work-up of epilepsy patients.
Original languageEnglish
Title of host publicationBioengineering and Biomedical Signal and Image Processing - First International Conference, BIOMESIP 2021, Proceedings
EditorsIgnacio Rojas, Daniel Castillo-Secilla, Luis Javier Herrera, Héctor Pomares
PublisherSpringer Science and Business Media Deutschland GmbH
Pages218-230
Number of pages13
Volume12940 LNCS
ISBN (Print)9783030881627
DOIs
Publication statusPublished - 2021
Event1st International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021 - Meloneras, Spain
Duration: 19 Jul 202121 Jul 2021

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12940 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021
Country/TerritorySpain
CityMeloneras
Period19/07/202121/07/2021

Cite this