Literature DB >> 33633670

Specific Oscillatory Power Changes and Their Efficacy for Determining Laterality in Mesial Temporal Lobe Epilepsy: A Magnetoencephalographic Study.

Yuta Tanoue1, Takehiro Uda1, Hideyuki Hoshi2, Yoshihito Shigihara2,3, Toshiyuki Kawashima1, Kosuke Nakajo1, Naohiro Tsuyuguchi1,4, Takeo Goto1.   

Abstract

Appropriate determination of the epileptic focus and its laterality are important for the diagnosis of mesial temporal lobe epilepsy (MTLE). The aims of this study are to establish a specific oscillatory distribution and laterality of the oscillatory power in unilateral MTLE with frequency analysis of magnetoencephalography (MEG), and to confirm their potential to carry significant information for determining lateralization of the epileptic focus. Thirty-five patients with MTLE [left (LtMTLE), 16; right (RtMTLE), 19] and 102 healthy control volunteers (CTR) were enrolled. Cortical oscillatory powers were compared among the groups by contrasting the source images using a one-way ANOVA model for each frequency band. Further, to compare the lateralization of regional oscillatory powers between LtMTLEs and RtMTLEs, the laterality index (LI) was calculated for four brain regions (frontal, temporal, parietal, and occipital) in each frequency band, which were compared between patient groups (LtMTLE, RtMTLE, and CTR), and used for machine learning prediction of the groups with support vector machine (SVM) with linear kernel function. Significant oscillatory power differences between MTLE and CTR were found in certain areas. In the theta to high-frequency oscillation bands, there were marked increases in the parietal lobe, especially on the left side, in LtMTLE. In the theta, alpha, and high-gamma bands, there were marked increases in the parietal lobe, especially on the right side in RtMTLE. Compared with CTR, LIs were significantly higher in 24/28 regions in LtMTLE, but lower in 4/28 regions and higher in 10/28 regions in RtMTLE. LI at the temporal lobe in the theta band was significantly higher in LtMTLE and significantly lower in RtMTLE. Comparing LtMTLE and RtMTLE, there were significant LI differences in most regions and frequencies (21/28 regions). In all frequency bands, there were significant differences between LtMTLE and RtMTLE in the temporal and parietal lobes. The leave-one-out cross-validation of the linear-SVM showed the classification accuracy to be over 91%, where the model had high specificity over 96% and mild sensitivity ~68-75%. Using MEG frequency analysis, the characteristics of the oscillatory power distribution in the MTLE were demonstrated. Compared with CTR, LIs shifted to the side of the epileptic focus in the temporal lobe in the theta band. The machine learning approach also confirmed that LIs have significant predictive ability in the lateralization of the epileptic focus. These results provide useful additional information for determining the laterality of the focus.
Copyright © 2021 Tanoue, Uda, Hoshi, Shigihara, Kawashima, Nakajo, Tsuyuguchi and Goto.

Entities:  

Keywords:  lateralizing sign; machine learning; magnetoencephalography; mesial temporal lobe epilepsy; oscillatory power change

Year:  2021        PMID: 33633670      PMCID: PMC7900569          DOI: 10.3389/fneur.2021.617291

Source DB:  PubMed          Journal:  Front Neurol        ISSN: 1664-2295            Impact factor:   4.003


  39 in total

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Journal:  Epilepsy Behav       Date:  2011-02       Impact factor: 2.937

2.  Multiple sparse priors for the M/EEG inverse problem.

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Journal:  Neuroimage       Date:  2007-10-10       Impact factor: 6.556

3.  Magnetoencephalography source localization and surgical outcome in temporal lobe epilepsy.

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Journal:  Clin Neurophysiol       Date:  2004-09       Impact factor: 3.708

4.  Clinical applications of magnetoencephalography in epilepsy.

Authors:  Amit Ray; Susan M Bowyer
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5.  Statistical parametric mapping for analyzing interictal magnetoencephalography in patients with left frontal lobe epilepsy.

Authors:  Haitao Zhu; Jinlong Zhu; Forrest Sheng Bao; Hongyi Liu; Xuchuang Zhu; Ting Wu; Lu Yang; Yuanjie Zou; Rui Zhang; Gang Zheng
Journal:  Seizure       Date:  2015-11-21       Impact factor: 3.184

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Authors:  Gadi Goelman; Rotem Dan; Filip Růžička; Ondrej Bezdicek; Evžen Růžička; Jan Roth; Josef Vymazal; Robert Jech
Journal:  Sci Rep       Date:  2017-03-08       Impact factor: 4.379

7.  Resting-State Magnetoencephalography Reveals Neurobiological Bridges Between Pain and Cognitive Impairment.

Authors:  Yoshihito Shigihara; Hideyuki Hoshi; Keisuke Fukasawa; Sayuri Ichikawa; Momoko Kobayashi; Yuki Sakamoto; Kazuyuki Negishi; Rika Haraguchi; Shin Konno
Journal:  Pain Ther       Date:  2020-10-23

8.  Magnetoencephalography Reveals a Widespread Increase in Network Connectivity in Idiopathic/Genetic Generalized Epilepsy.

Authors:  Adham Elshahabi; Silke Klamer; Ashish Kaul Sahib; Holger Lerche; Christoph Braun; Niels K Focke
Journal:  PLoS One       Date:  2015-09-14       Impact factor: 3.240

9.  Towards the Automatic Localization of the Irritative Zone Through Magnetic Source Imaging.

Authors:  Gianvittorio Luria; Dunja Duran; Elisa Visani; Davide Rossi Sebastiano; Alberto Sorrentino; Laura Tassi; Alice Granvillano; Silvana Franceschetti; Ferruccio Panzica
Journal:  Brain Topogr       Date:  2020-08-07       Impact factor: 3.020

10.  Biomagnetic biomarkers for dementia: A pilot multicentre study with a recommended methodological framework for magnetoencephalography.

Authors:  Laura E Hughes; Richard N Henson; Ernesto Pereda; Ricardo Bruña; David López-Sanz; Andrew J Quinn; Mark W Woolrich; Anna C Nobre; James B Rowe; Fernando Maestú
Journal:  Alzheimers Dement (Amst)       Date:  2019-06-14
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  1 in total

1.  Two Distinct Neural Mechanisms Underlying Acupuncture Analgesia.

Authors:  Yasutaka Kato; Kazuhiro Yachi; Hideyuki Hoshi; Toyoji Okada; Yoshihito Shigihara
Journal:  Front Pain Res (Lausanne)       Date:  2022-05-18
  1 in total

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