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Component-Related Bold Response to Localize Epileptic Focus Using Simultaneous Eeg-Fmri Recordings at 3T Publisher Pubmed



Ebrahimzadeh E1, 2 ; Soltanianzadeh H1, 3, 4 ; Araabi BN1 ; Fesharaki SSH5 ; Habibabadi JM6
Authors
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Authors Affiliations
  1. 1. CIPCE, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
  2. 2. Department of Clinical Neurosciences, Hotchkiss Brain Institute, Cumming School of Medicine, Seaman Family MR Research Centre University of Calgary, Calgary, Alberta, Canada
  3. 3. School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
  4. 4. Image Analysis Laboratory, Departments of Radiology and Research Administration, Henry Ford Health System, Detroit, MI, United States
  5. 5. Pars Advanced Medical Research Center, Pars Hospital, Tehran, Iran
  6. 6. Isfahan Neurosciences Research Center, Department of Neurology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Journal of Neuroscience Methods Published:2019


Abstract

Background: Simultaneous EEG-fMRI experiments record spatiotemporal dynamics of epileptic activity. A shortcoming of spike-based EEG-fMRI studies is their inability to provide information about behavior of epileptic generators when no spikes are visible. New method: We extract time series of epileptic components identified on EEG and fit them with Generalized Linear Model (GLM)model. This allows a precise and reliable localization of epileptic foci in addition to predicting generator's behavior. The proposed method works in the source domain and delineates generators considering spatial correlation between spike template and candidate components in addition to patient's medical records. Results: The proposed method was applied on 20 patients with refractory epilepsy and 20 age- and gender-matched healthy controls. The identified components were examined statistically and threshold of localization accuracy was determined as 86% based on Receiver Operating Characteristic (ROC)curve analysis. Accuracy, sensitivity, and specificity were found to be 88%, 85%, and 95%, respectively. Contribution of EEG-fMRI and concordance between EEG and fMRI were also evaluated. Concordance was found in 19 patients and contribution in 17. Comparison with existing methods: We compared the proposed method with conventional methods. Our comparisons showed superiority of the proposed method. In particular, when epileptogenic zone was located deep in the brain, the method outperformed existing methods. Conclusions: This study contributes substantially to increasing the yield of EEG-fMRI and presents a realistic estimate of the neural behavior of epileptic generators, to the best of our knowledge, for the first time in the literature. © 2019 Elsevier B.V.