Magnetoencephalography Spectral Abnormalities: A Potential Novel Biomarker of the Epileptogenic Zone for Presurgical Evaluation
Abstract number :
2.034
Submission category :
3. Neurophysiology / 3D. MEG
Year :
2022
Submission ID :
2204297
Source :
www.aesnet.org
Presentation date :
12/4/2022 12:00:00 PM
Published date :
Nov 22, 2022, 05:24 AM
Authors :
Eleanor Hill, MSci – Montreal Neurological Institute and Hospital, McGill University; Alex Wiesman, PhD – Montreal Neurological Institute and Hospital, McGill University; Jeremy Moreau, PhD – Cumming School of Medicine, University of Calgary, Calgary; Erica Minato, MSc – Montreal Neurological Institute and Hospital, McGill University; Marc Lalancette, MSc – Montreal Neurological Institute and Hospital, McGill University; Elisabeth Simard-Tremblay, MD, FRCPC, CSCN(EEG) – Department of Pediatrics, Division of Pediatric Neurology – Montreal Children’s Hospital, McGill University; Roy Dudley, MD, PhD – Department of Pediatric Surgery, Division of Neurosurgery – Montreal Children’s Hospital, McGill University; Sylvain Baillet, PhD – Montreal Neurological Institute and Hospital, McGill University
Rationale: Achieving seizure freedom for focal epilepsy cases requires accurate presurgical identification of the epileptogenic zone (EZ), which remains extremely challenging for poorly-defined cases (i.e., the lesion and/or its borders are not seen on MRI). Magnetoencephalography (MEG, a non-invasive functional imaging modality) has become a well-established component of the presurgical evaluation and it is typically used to source localize interictal epileptiform discharges (IEDs). But marking such events is time-consuming and prone to human error, if they are captured during the relatively short (~ 1 hour) recording. Here we explore the potential of detecting abnormal spectral variants in source spectral power density (PSD) in pediatric focal epilepsy cases relative to a large normative database, as a novel marker for EZ delineation.
Methods: We used MEG rest recordings of pediatric patients (n = 97), using a 275 channel CTF system, and obtained maps of delta- to gamma-band brain activity. We applied the same procedure to create a normative distribution of PSD brain maps in healthy controls from the Open MEG Archive (n = 200). Each patient was contrasted against this normative distribution to identify deviations from healthy variants. The open-source neuroimaging software Brainstorm and in-house functions were used.
Results: Preliminary results from 20 pediatric cases show a concordance between PSD maps and IED localizations in 85% of cases, with delta being the most consistent (75% of cases). We will present the full results and discuss the prediction of surgical outcomes from spectral deviation maps and their relevance to other demographic/surgical information.
Conclusions: PSD mapping has the potential for efficient, reproducible, and faster MEG analyses in epilepsy. Relating these findings to a normative distribution (in progress), intracranial recordings, individual surgical resection zones, post-surgical outcomes, and histopathology will advance our understanding of the nature of aberrant in-vivo, human neural dynamics in epilepsy. Furthermore, it may establish a novel marker for EZ delineation in the presurgical evaluation and may improve surgical outcomes in these complex cases all the while eliminating the time-consuming task of IED marking for epileptologists.
Funding: S.B. was supported by Natural Science and Engineering Research Council of Canada Discovery Grant 436355-13, Canada Research Chair of Neural Dynamics of Brain Systems, National Institutes of Health Grant 1R01EB026299-01, Healthy Brains for Healthy Lives Canada Excellence Research Fund, and Brain Canada Foundation Platform Support Grant PSG15-3755. R.W.D was supported by the Foundation of the Department of Neurosurgery, McGill University, grant number/charitable registration number: 73954 0920 RR 0001, and by the McGill University Health Centers Research Institute - New Directions in Research Competition Award in 2016.
Neurophysiology