Literature DB >> 34891320

Mapping Functional Connectivity of Epileptogenic Networks through Virtual Implantation.

Ludovica Corona, Eleonora Tamilia, Joseph R Madsen, Steven M Stufflebeam, Phillip L Pearl, Christos Papadelis.   

Abstract

Children with medically refractory epilepsy (MRE) require resective neurosurgery to achieve seizure freedom, whose success depends on accurate delineation of the epileptogenic zone (EZ). Functional connectivity (FC) can assess the extent of epileptic brain networks since intracranial EEG (icEEG) studies have shown its link to the EZ and predictive value for surgical outcome in these patients. Here, we propose a new noninvasive method based on magnetoencephalography (MEG) and high-density (HD-EEG) data that estimates FC metrics at the source level through an "implantation" of virtual sensors (VSs). We analyzed MEG, HD-EEG, and icEEG data from eight children with MRE who underwent surgery having good outcome and performed source localization (beamformer) on noninvasive data to build VSs at the icEEG electrode locations. We analyzed data with and without Interictal Epileptiform Discharges (IEDs) in different frequency bands, and computed the following FC matrices: Amplitude Envelope Correlation (AEC), Correlation (CORR), and Phase Locking Value (PLV). Each matrix was used to generate a graph using Minimum Spanning Tree (MST), and for each node (i.e., each sensor) we computed four centrality measures: betweenness, closeness, degree, and eigenvector. We tested the reliability of VSs measures with respect to icEEG (regarded as benchmark) via linear correlation, and compared FC values inside vs. outside resection. We observed higher FC inside than outside resection (p<0.05) for AEC [alpha (8-12 Hz), beta (12-30 Hz), and broadband (1-50 Hz)] on data with IEDs and AEC theta (4-8 Hz) on data without IEDs for icEEG, AEC broadband (1-50 Hz) on data without IEDs for MEG-VSs, as well as for all centrality measures of icEEG and MEG/HD-EEG-VSs. Additionally, icEEG and VSs metrics presented high correlation (0.6-0.9, p<0.05). Our data support the notion that the proposed method can potentially replicate the icEEG ability to map the epileptogenic network in children with MRE.Clinical Relevance - The estimation of FC with noninvasive techniques, such as MEG and HD-EEG, via VSs is a promising tool that would help the presurgical evaluation by delineating the EZ without waiting for a seizure to occur, and potentially improve the surgical outcome of patients with MRE undergoing surgery.

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Mesh:

Year:  2021        PMID: 34891320      PMCID: PMC8893022          DOI: 10.1109/EMBC46164.2021.9629686

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  15 in total

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Journal:  Brain       Date:  2001-09       Impact factor: 13.501

2.  Epilepsy surgery outcome and functional network alterations in longitudinal MEG: a minimum spanning tree analysis.

Authors:  Edwin van Dellen; Linda Douw; Arjan Hillebrand; Philip C de Witt Hamer; Johannes C Baayen; Jan J Heimans; Jaap C Reijneveld; Cornelis J Stam
Journal:  Neuroimage       Date:  2013-10-12       Impact factor: 6.556

3.  A FreeSurfer-compliant consistent manual segmentation of infant brains spanning the 0-2 year age range.

Authors:  Katyucia de Macedo Rodrigues; Emma Ben-Avi; Danielle D Sliva; Myong-Sun Choe; Marie Drottar; Ruopeng Wang; Bruce Fischl; Patricia E Grant; Lilla Zöllei
Journal:  Front Hum Neurosci       Date:  2015-02-18       Impact factor: 3.169

4.  Identifying the epileptogenic zone in interictal resting-state MEG source-space networks.

Authors:  Ida A Nissen; Cornelis J Stam; Jaap C Reijneveld; Ilse E C W van Straaten; Eef J Hendriks; Johannes C Baayen; Philip C De Witt Hamer; Sander Idema; Arjan Hillebrand
Journal:  Epilepsia       Date:  2016-11-26       Impact factor: 5.864

Review 5.  Complications of epilepsy surgery: a systematic review of focal surgical resections and invasive EEG monitoring.

Authors:  Walter J Hader; Jose Tellez-Zenteno; Amy Metcalfe; Lisbeth Hernandez-Ronquillo; Samuel Wiebe; Churl-Su Kwon; Nathalie Jette
Journal:  Epilepsia       Date:  2013-04-03       Impact factor: 5.864

6.  Brainstorm: a user-friendly application for MEG/EEG analysis.

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Journal:  Comput Intell Neurosci       Date:  2011-04-13

7.  OpenMEEG: opensource software for quasistatic bioelectromagnetics.

Authors:  Alexandre Gramfort; Théodore Papadopoulo; Emmanuel Olivi; Maureen Clerc
Journal:  Biomed Eng Online       Date:  2010-09-06       Impact factor: 2.819

Review 8.  Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy.

Authors:  Eleonora Tamilia; Joseph R Madsen; Patricia Ellen Grant; Phillip L Pearl; Christos Papadelis
Journal:  Front Neurol       Date:  2017-01-30       Impact factor: 4.003

9.  Virtual localization of the seizure onset zone: Using non-invasive MEG virtual electrodes at stereo-EEG electrode locations in refractory epilepsy patients.

Authors:  Erika L Juárez-Martinez; Ida A Nissen; Sander Idema; Demetrios N Velis; Arjan Hillebrand; Cornelis J Stam; Elisabeth C W van Straaten
Journal:  Neuroimage Clin       Date:  2018-06-02       Impact factor: 4.881

10.  High interictal connectivity within the resection zone is associated with favorable post-surgical outcomes in focal epilepsy patients.

Authors:  Preya Shah; John M Bernabei; Lohith G Kini; Arian Ashourvan; Jacqueline Boccanfuso; Ryan Archer; Kelly Oechsel; Sandhitsu R Das; Joel M Stein; Timothy H Lucas; Danielle S Bassett; Kathryn A Davis; Brian Litt
Journal:  Neuroimage Clin       Date:  2019-06-19       Impact factor: 4.881

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