Kurtosis-based detection of intracranial high-frequency oscillations for the identification of the seizure onset zone

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Abstract

Pathological High-Frequency Oscillations (HFOs) have been recently proposed as potential biomarker of the seizure onset zone (SOZ) and have shown superior accuracy to interictal epileptiform discharges in delineating its anatomical boundaries. Characterization of HFOs is still in its infancy and this is reflected in the heterogeneity of analysis and reporting methods across studies and in clinical practice. The clinical approach to HFOs identification and quantification usually still relies on visual inspection of EEG data. In this study, we developed a pipeline for the detection and analysis of HFOs. This includes preliminary selection of the most informative channels exploiting statistical properties of the pre-ictal and ictal intracranial EEG (iEEG) time series based on spectral kurtosis, followed by wavelet-based characterization of the time-frequency properties of the signal. We performed a preliminary validation analyzing EEG data in the ripple frequency band (80-250[Formula: see text]Hz) from six patients with drug-resistant epilepsy who underwent pre-surgical evaluation with stereo-EEG (SEEG) followed by surgical resection of pathologic brain areas, who had at least two-year positive post-surgical outcome. In this series, kurtosis-driven selection and wavelet-based detection of HFOs had average sensitivity of 81.94% and average specificity of 96.03% in identifying the HFO area which overlapped with the SOZ as defined by clinical presurgical workup. Furthermore, the kurtosis-based channel selection resulted in an average reduction in computational time of 66.60%.

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Original languageEnglish
Article number10.1142/S0129065718500016
Pages (from-to)1850001
Number of pages18
JournalInternational Journal of Neural Systems
VolumeIn press
Early online date26 Mar 2018
DOIs
Publication statusE-pub ahead of print - 26 Mar 2018

Bibliographic note

© The Author(s) This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. Funding: MSCA-IF-2014-EF -Marie Skłodowska-Curie Individual Fellowship.

    Keywords

  • Epilepsy, intracranial-EEG (iEEG), High-frequency Oscillations (HFOs), Kurtosis, Wavelet transform.

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