Impact Factor 2.635 | CiteScore 2.99
More on impact ›

Original Research ARTICLE Provisionally accepted The full-text will be published soon. Notify me

Front. Neurol. | doi: 10.3389/fneur.2019.00805

Semi-automated EEG enhancement improves localization of ictal onset zone with EEG-correlated fMRI

 Simon Van Eyndhoven1, 2*,  Borbála Hunyadi3, Patrick Dupont4, 5,  Wim Van Paesschen6, 7 and Sabine Van Huffel1, 2
  • 1Department of Electrical Engineering, KU Leuven, Belgium
  • 2Interuniversity Microelectronics Centre (IMEC), Belgium
  • 3Department of Microelectronics, Delft University of Technology, Netherlands
  • 4Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Belgium
  • 5Leuven Brain Institute, KU Leuven, Belgium
  • 6Department of Neurology, University Hospitals Leuven, Belgium
  • 7KU Leuven, Other, Belgium

Objective: To improve the accuracy of detecting the ictal onset zone, we propose to enhance the epilepsy-related activity present in the EEG signals, before mapping their BOLD correlates through EEG-correlated fMRI analysis.
Methods: Based solely on a segmentation of interictal epileptic discharges (IEDs) on the EEG, we train multi-channel Wiener filters (MWF) which enhance IED-like waveforms, and suppress background activity and noisy influences. Subsequently, we use EEG-correlated fMRI to find the brain regions in which the BOLD signal fluctuation corresponds to the filtered signals’ time-varying power (after convolving with the hemodynamic response function), and validate the identified regions by quantitatively comparing them to ground-truth maps of the (resected or hypothesized) ictal onset zone. We validate the performance of this novel predictor versus that of commonly used unitary or power-weighted predictors and a recently introduced connectivity-based metric, on a cohort of twelve patients with temporal lobe epilepsy.
Results: The novel predictor, derived from the filtered EEG signals, allowed the detection of the ictal onset zone in a larger percentage of epileptic patients (92% vs. at most 83% for the other predictors), and with higher statistical significance, compared to existing predictors. At the same time, the new method maintains maximal specificity by not producing false positive activations in healthy controls.
Significance: The findings of this study advocate for the use of the MWF to maximize the signal-to-noise ratio of IED-like events in the interictal EEG, and subsequently use time-varying power as a sensitive predictor of the BOLD signal, to localize the ictal onset zone.

Keywords: EEG-fMRI, Signal enhancement, Multi-channel Wiener filter (MWF), ictal onset zone, refractory epilepsy, Interictal epileptic discharge, Epilepsy, EEG-correlated fMRI, General Linear Model (GLM)

Received: 24 Apr 2019; Accepted: 11 Jul 2019.

Edited by:

Jose F. Tellez-Zenteno, University of Saskatchewan, Canada

Reviewed by:

Firas Fahoum, Tel Aviv Sourasky Medical Center, Israel
Paolo Federico, University of Calgary, Canada  

Copyright: © 2019 Van Eyndhoven, Hunyadi, Dupont, Van Paesschen and Van Huffel. 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.

* Correspondence: Mr. Simon Van Eyndhoven, Department of Electrical Engineering, KU Leuven, Leuven, Belgium,