OBJECTIVE: High-frequency oscillations are considered among the most promising interictal biomarkers of the epileptogenic zone in patients suffering from pharmacoresistant focal epilepsy. However, there is no clear definition of pathological high-frequency oscillations, and the existing detectors vary in methodology, performance, and computational costs. This study proposes relative entropy as an easy-to-use novel interictal biomarker of the epileptic tissue. METHODS: We evaluated relative entropy and high-frequency oscillation biomarkers on intracranial electroencephalographic data from 39 patients with seizure-free postoperative outcome (Engel Ia) from three institutions. We tested their capability to localize the epileptogenic zone, defined as resected contacts located in the seizure onset zone. The performance was compared using areas under the receiver operating curves (AUROCs) and precision-recall curves. Then we tested whether a universal threshold can be used to delineate the epileptogenic zone across patients from different institutions. RESULTS: Relative entropy in the ripple band (80-250 Hz) achieved an average AUROC of .85. The normalized high-frequency oscillation rate in the ripple band showed an identical AUROC of .85. In contrast to high-frequency oscillations, relative entropy did not require any patient-level normalization and was easy and fast to calculate due to its clear and straightforward definition. One threshold could be set across different patients and institutions, because relative entropy is independent of signal amplitude and sampling frequency. SIGNIFICANCE: Although both relative entropy and high-frequency oscillations have a similar performance, relative entropy has significant advantages such as straightforward definition, computational speed, and universal interpatient threshold, making it an easy-to-use promising biomarker of the epileptogenic zone.

Analytical Neurophysiology Lab Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada

Bioelectronics Neurophysiology and Engineering Laboratory Departments of Neurology and Physiology and Biomedical Engineering Mayo Clinic Rochester Minnesota USA

Central European Institute of Technology Masaryk University Brno Czech Republic

Department of Neurology Brno Epilepsy Center St Anne's University Hospital and Medical Faculty of Masaryk University Brno Czech Republic

Institute of Scientific Instruments Czech Academy of Sciences Brno Czech Republic

International Clinical Research Center St Anne's University Hospital Brno Czech Republic

Montreal Neurological Institute and Hospital McGill University Montreal Quebec Canada

Epilepsia. 2023 Jun;64(6):1695. doi: 10.1111/epi.17597. PubMed

Epilepsia. 2023 Jun;64(6):1694. doi: 10.1111/epi.17599. PubMed

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Multicentre analysis of seizure outcome predicted by removal of high-frequency oscillations

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