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


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%.

Publication DOI: https://doi.org/10.1142/S0129065718500016
Divisions: College of Health & Life Sciences
College of Health & Life Sciences > School of Psychology
College of Health & Life Sciences > Aston Institute of Health & Neurodevelopment (AIHN)
College of Health & Life Sciences > Clinical and Systems Neuroscience
Additional Information: © 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.
Uncontrolled Keywords: Epilepsy,intracranial-EEG (iEEG),High-frequency Oscillations (HFOs),Kurtosis,Wavelet transform.
Publication ISSN: 1793-6462
Last Modified: 27 May 2024 07:22
Date Deposited: 01 Feb 2018 09:25
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Related URLs: https://www.wor ... 129065718500016 (Publisher URL)
PURE Output Type: Article
Published Date: 2018-03-26
Accepted Date: 2018-01-02
Authors: Quitadamo, Lucia Rita (ORCID Profile 0000-0003-1877-4672)
Mai, Roberto
Gozzo, Francesca
Pelliccia, Veronica
Cardinale, Francesco
Seri, Stefano (ORCID Profile 0000-0002-9247-8102)



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License: Creative Commons Attribution

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