Literature DB >> 23454472

EEG-fMRI correlation patterns in the presurgical evaluation of focal epilepsy: a comparison with electrocorticographic data and surgical outcome measures.

Petra J van Houdt1, Jan C de Munck2, Frans S S Leijten3, Geertjan J M Huiskamp3, Albert J Colon4, Paul A J M Boon5, Pauly P W Ossenblok6.   

Abstract

EEG-correlated functional MRI (EEG-fMRI) visualizes brain regions associated with interictal epileptiform discharges (IEDs). This technique images the epileptiform network, including multifocal, superficial and deeply situated cortical areas. To understand the role of EEG-fMRI in presurgical evaluation, its results should be validated relative to a gold standard. For that purpose, EEG-fMRI data were acquired for a heterogeneous group of surgical candidates (n=16) who were later implanted with subdural grids and strips (ECoG). The EEG-fMRI correlation patterns were systematically compared with brain areas involved in IEDs ECoG, using a semi-automatic analysis method, as well as to the seizure onset zone, resected area, and degree of seizure freedom. In each patient at least one of the EEG-fMRI areas was concordant with an interictally active ECoG area, always including the early onset area of IEDs in the ECoG data. This confirms that EEG-fMRI reflects a pattern of onset and propagation of epileptic activity. At group level, 76% of the BOLD regions that were covered with subdural grids, were concordant with interictally active ECoG electrodes. Due to limited spatial sampling, 51% of the BOLD regions were not covered with electrodes and could, therefore, not be validated. From an ECoG perspective it appeared that 29% of the interictally active ECoG regions were missed by EEG-fMRI and that 68% of the brain regions were correctly identified as inactive with EEG-fMRI. Furthermore, EEG-fMRI areas included the complete seizure onset zone in 83% and resected area in 93% of the data sets. No clear distinction was found between patients with a good or poor surgical outcome: in both patient groups, EEG-fMRI correlation patterns were found that were either focal or widespread. In conclusion, by comparison of EEG-fMRI with interictal invasive EEG over a relatively large patient population we were able to show that the EEG-fMRI correlation patterns are spatially accurate at the level of neurosurgical units (i.e. anatomical brain regions) and reflect the underlying network of IEDs. Therefore, we expect that EEG-fMRI can play an important role for the determination of the implantation strategy.
Copyright © 2013 Elsevier Inc. All rights reserved.

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Year:  2013        PMID: 23454472     DOI: 10.1016/j.neuroimage.2013.02.033

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  21 in total

1.  Spatial correlation of hemodynamic changes related to interictal epileptic discharges with electric and magnetic source imaging.

Authors:  Marcel Heers; Tanguy Hedrich; Dongmei An; François Dubeau; Jean Gotman; Christophe Grova; Eliane Kobayashi
Journal:  Hum Brain Mapp       Date:  2014-02-24       Impact factor: 5.038

Review 2.  Brain imaging in the assessment for epilepsy surgery.

Authors:  John S Duncan; Gavin P Winston; Matthias J Koepp; Sebastien Ourselin
Journal:  Lancet Neurol       Date:  2016-02-24       Impact factor: 44.182

Review 3.  Methods and utility of EEG-fMRI in epilepsy.

Authors:  Louis André van Graan; Louis Lemieux; Umair Javaid Chaudhary
Journal:  Quant Imaging Med Surg       Date:  2015-04

4.  Clinical Yield of Electromagnetic Source Imaging and Hemodynamic Responses in Epilepsy: Validation With Intracerebral Data.

Authors:  Chifaou Abdallah; Tanguy Hedrich; Andreas Koupparis; Jawata Afnan; Jeffrey Alan Hall; Jean Gotman; Francois Dubeau; Nicolas von Ellenrieder; Birgit Frauscher; Eliane Kobayashi; Christophe Grova
Journal:  Neurology       Date:  2022-04-26       Impact factor: 11.800

Review 5.  Localization of Epileptic Foci Based on Simultaneous EEG-fMRI Data.

Authors:  Seyyed Mostafa Sadjadi; Elias Ebrahimzadeh; Mohammad Shams; Masoud Seraji; Hamid Soltanian-Zadeh
Journal:  Front Neurol       Date:  2021-04-27       Impact factor: 4.003

6.  Network analysis of EEG related functional MRI changes due to medication withdrawal in focal epilepsy.

Authors:  Kees Hermans; Pauly Ossenblok; Petra van Houdt; Liesbeth Geerts; Rudolf Verdaasdonk; Paul Boon; Albert Colon; Jan C de Munck
Journal:  Neuroimage Clin       Date:  2015-06-09       Impact factor: 4.881

Review 7.  Electrophysiological correlates of the BOLD signal for EEG-informed fMRI.

Authors:  Teresa Murta; Marco Leite; David W Carmichael; Patrícia Figueiredo; Louis Lemieux
Journal:  Hum Brain Mapp       Date:  2014-10-03       Impact factor: 5.038

8.  Interictal Epileptiform Discharge Dynamics in Peri-sylvian Polymicrogyria Using EEG-fMRI.

Authors:  Noa Cohen; Yoram Ebrahimi; Mordekhay Medvedovsky; Guy Gurevitch; Orna Aizenstein; Talma Hendler; Firas Fahoum; Tomer Gazit
Journal:  Front Neurol       Date:  2021-06-03       Impact factor: 4.003

Review 9.  Network Connectivity in Epilepsy: Resting State fMRI and EEG-fMRI Contributions.

Authors:  Maria Centeno; David W Carmichael
Journal:  Front Neurol       Date:  2014-07-04       Impact factor: 4.003

10.  Sensitivity and Specificity of Interictal EEG-fMRI for Detecting the Ictal Onset Zone at Different Statistical Thresholds.

Authors:  Simon Tousseyn; Patrick Dupont; Karolien Goffin; Stefan Sunaert; Wim Van Paesschen
Journal:  Front Neurol       Date:  2014-07-17       Impact factor: 4.003

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