論文

査読有り 国際誌
2020年3月24日

Distributed source analysis of magnetoencephalography using a volume head model combined with statistical methods improves focus diagnosis in epilepsy surgery.

Scientific reports
  • Tomotaka Ishizaki
  • ,
  • Satoshi Maesawa
  • ,
  • Daisuke Nakatsubo
  • ,
  • Hiroyuki Yamamoto
  • ,
  • Sou Takai
  • ,
  • Masashi Shibata
  • ,
  • Sachiko Kato
  • ,
  • Jun Natsume
  • ,
  • Minoru Hoshiyama
  • ,
  • Toshihiko Wakabayashi

10
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開始ページ
5263
終了ページ
5263
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1038/s41598-020-62098-5

Deep-seated epileptic focus estimation using magnetoencephalography is challenging because of its low signal-to-noise ratio and the ambiguity of current sources estimated by interictal epileptiform discharge (IED). We developed a distributed source (DS) analysis method using a volume head model as the source space of the forward model and standardized low-resolution brain electromagnetic tomography combined with statistical methods (permutation tests between IEDs and baselines and false discovery rate between voxels to reduce variation). We aimed to evaluate the efficacy of the combined DS (cDS) analysis in surgical cases. In total, 19 surgical cases with adult and pediatric focal epilepsy were evaluated. Both cDS and equivalent current dipole (ECD) analyses were performed in all cases. The concordance rates of the two methods with surgically identified epileptic foci were calculated and compared with surgical outcomes. Concordance rates from the cDS analysis were significantly higher than those from the ECD analysis (68.4% vs. 26.3%), especially in cases with deep-seated lesions, such as in the interhemispheric, fronto-temporal base, and mesial temporal structures (81.8% vs. 9.1%). Furthermore, the concordance rate correlated well with surgical outcomes. In conclusion, cDS analysis has better diagnostic performance in focal epilepsy, especially with deep-seated epileptic focus, and potentially leads to good surgical outcomes.

リンク情報
DOI
https://doi.org/10.1038/s41598-020-62098-5
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/32210314
PubMed Central
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7093400
ID情報
  • DOI : 10.1038/s41598-020-62098-5
  • PubMed ID : 32210314
  • PubMed Central 記事ID : PMC7093400

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