High frequency oscillation network dynamics predict outcome in non-palliative epilepsy surgery

Jack Lin, Garnett C. Smith, Stephen V. Gliske, Michal Zochowski, Kerby Shedden, William C. Stacey

Research output: Contribution to journalArticlepeer-review

Abstract

High frequency oscillations are a promising biomarker of outcome in intractable epilepsy. Prior high frequency oscillation work focused on counting high frequency oscillations on individual channels, and it is still unclear how to translate those results into clinical care. We show that high frequency oscillations arise as network discharges that have valuable properties as predictive biomarkers. Here, we develop a tool to predict patient outcome before surgical resection is performed, based on only prospective information. In addition to determining high frequency oscillation rate on every channel, we performed a correlational analysis to evaluate the functional connectivity of high frequency oscillations in 28 patients with intracranial electrodes. We found that high frequency oscillations were often not solitary events on a single channel, but part of a local network discharge. Eigenvector and outcloseness centrality were used to rank channel importance within the connectivity network, then used to compare patient outcome by comparison with the seizure onset zone or a proportion within the proposed resected channels (critical resection percentage). Combining the knowledge of each patient’s seizure onset zone resection plan along with our computed high frequency oscillation network centralities and high frequency oscillation rate, we develop a Naïve Bayes model that predicts outcome (positive predictive value: 100%) better than predicting based upon fully resecting the seizure onset zone (positive predictive value: 71%). Surgical margins had a large effect on outcomes: non-palliative patients in whom most of the seizure onset zone was resected (‘definitive surgery’, ≥ 80% resected) had predictable outcomes, whereas palliative surgeries (<80% resected) were not predictable. These results suggest that the addition of network properties of high frequency oscillations is more accurate in predicting patient outcome than seizure onset zone alone in patients with most of the seizure onset zone removed and offer great promise for informing clinical decisions in surgery for refractory epilepsy.

Original languageEnglish (US)
Article numberfcae032
JournalBrain Communications
Volume6
Issue number1
DOIs
StatePublished - 2024

Keywords

  • EEG
  • HFO
  • centrality
  • epilepsy
  • network

ASJC Scopus subject areas

  • Neurology
  • Psychiatry and Mental health
  • Cellular and Molecular Neuroscience
  • Biological Psychiatry

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