title: Electrophysiological resting-state biomarker for diagnosing mesial temporal lobe epilepsy with hippocampal sclerosis.
abstract: The main aim of the present study was to evaluate whether resting-state functional connectivity of magnetoencephalography (MEG) signals can differentiate patients with mesial temporal lobe epilepsy (MTLE) from healthy controls (HC) and can differentiate between right and left MTLE as a diagnostic biomarker. To this end, a support vector machine (SVM) method among various machine learning algorithms was employed. We compared resting-state functional networks between 46 MTLE (right MTLE=23; left MTLE=23) patients with histologically proven HS who were free of seizure after surgery, and 46 HC. The optimal SVM group classifier distinguished MTLE patients with a mean accuracy of 95.1% (sensitivity=95.8%; specificity=94.3%). Increased connectivity including the right posterior cingulate gyrus and decreased connectivity including at least one sensory-related resting-state network were key features reflecting the differences between MTLE patients and HC. The optimal SVM model distinguished between right and left MTLE patients with a mean accuracy of 76.2% (sensitivity=76.0%; specificity=76.5%). We showed the potential of electrophysiological resting-state functional connectivity, which reflects brain network reorganization in MTLE patients, as a possible diagnostic biomarker to differentiate MTLE patients from HC and differentiate between right and left MTLE patients.
authors.affiliation: Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; iMediSyn Inc., Seoul, Republic of Korea. Electronic address: shjin43@gmail.com.
authors.forename: Seung-Hyun
authors.initials: SH
authors.lastname: Jin
authors.affiliation: Neuroscience Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University Hospital, Seoul, Republic of Korea; Department of Neurosurgery, Seoul National University College of Medicine, Seoul, Republic of Korea; Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea. Electronic address: chungc@snu.ac.kr.
authors.forename: Chun Kee
authors.initials: CK
authors.lastname: Chung
mesh_terms: D000328:Adult; D001921:Brain / Q000473:pathology / Q000503:physiopathology* / Q000601:surgery; D004833:Epilepsy, Temporal Lobe / Q000145:classification / Q000175:diagnosis* / Q000503:physiopathology* / Q000601:surgery; D005260:Female; D005500:Follow-Up Studies; D007839:Functional Laterality; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000473:pathology / Q000503:physiopathology / Q000601:surgery; D012146:Rest; D012189:Retrospective Studies; D012598:Sclerosis / Q000145:classification / Q000175:diagnosis / Q000503:physiopathology / Q000601:surgery; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine; D055815:Young Adult
keywords: Mesial temporal lobe epilepsy; Resting-state magnetoencephalography; Support vector machine