Software-assisted spike detection in long-term EEG

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  • Sakuraba Rie
    Department of Epileptology, Tohoku University Graduate School of Medicine
  • Iwasaki Masaki
    Department of Neurosurgery, Tohoku University Graduate School of Medicine
  • Jin Kazutaka
    Department of Epileptology, Tohoku University Graduate School of Medicine
  • Itabashi Izumi
    Department of Epileptology, Tohoku University Graduate School of Medicine
  • Kato Kazuhiro
    Department of Epileptology, Tohoku University Graduate School of Medicine Department of Neurology, Tohoku University Graduate School of Medicine
  • Itabashi Hisashi
    Department of Epileptology, Tohoku University Graduate School of Medicine
  • Nakasato Nobukazu
    Department of Epileptology, Tohoku University Graduate School of Medicine

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Other Title
  • Brain Electrical Source Analysis (BESA) Epilepsyを使用した長時間脳波判読補助: 棘波検出の効率化の検討
  • Brain Electrical Source Analysis (BESA) Epilepsy オ シヨウ シタ チョウジカン ノウハ ハンドク ホジョ : キョクハ ケンシュツ ノ コウリツカ ノ ケントウ

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Abstract

Long-term video electroencephalography (LTVEEG) reading is time-consuming. BESA Epilepsy (BESAE) is a software package that detects and clusters spike-like events automatically, to assist manual interpretation. The software potentially improves the efficiency of LTVEEG reading, although it has not been applied clinically. In this study, we compared the localization of epileptic spikes between BESAE-assisted and conventional visual detection in 83 patients with suspected diagnoses of epilepsy (average age of 33 years ranging from 13 to 64; 31 males). The spike localization with the two methods was concordant in 55.4%, partially concordant in 20.5%, and discordant in 24.1%. The major reason for discordance was the presence of epileptic spikes missed by BESAE. The spike localization by means of BESAE-assisted detection was consistent with the clinical diagnosis in 75.9% of the patients. It took an average of 7 minutes 43 seconds for a BESAE-assisted review to analyze a 3-to-4-day LTVEEG record. This study showed that BESAE-assisted spike detection for LTVEEG is efficient and fairly reliable compared with visual detection. Further improvement is necessary for clinical application.

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