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Comparison of 11 High Frequency Oscillation (HFO) Detectors across Scalp and Intracranial EEG to Evaluate Clinical Utility

Maltseva, M.; Lachner-Piza, D.; LeVan, P.; Krisel Manalo, M.; Hader, W.; Jacobs, J.

2026-05-06 neurology
10.64898/2026.05.05.26352459 medRxiv
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IntroductionTo leverage high-frequency oscillations (HFOs) as a biomarker with significant potential, this study compared a large set of detectors on a unified dataset, aiming to evaluate their clinical applicability under realistic conditions. MethodsEleven automatic detectors were applied to a retrospective dataset of intracranial and scalp EEGs from 27 consecutive pediatric patients. Inter-detector agreement was assessed using Spearmans Rho, and the area under the curve (AUC) for seizure onset zone (SOZ) prediction served as a consistent reference standard to enable reliable comparisons across recording modalities. Analyses were conducted separately for HFO and Spike-HFO detections. ResultsThe average age of our cohort was 12.4 years (SD 4.0; range 5-18). AUC values in scalp EEG ranged from 0.61 to 0.67 for HFOs and from 0.53 to 0.63 for Spike-HFO. AUC values in intracranial EEG ranged from 0.48 to 0.66 for HFOs and 0.54 to 0.69 in Spike-HFO. Although only three of the 11 detectors were specifically developed or adapted for scalp EEG, the detectors generally achieved higher AUC values and stronger agreement in scalp EEG ConclusionsWe present the first study comparing intracranial and scalp detectors by testing them beyond the modalities for which they were originally designed. Although the clinical utility of detections was comparable across EEG modalities, it remained lower than reported in original studies assessing the diagnostic value of HFOs. Caution is warranted when applying a publicly available detector to a new dataset, and detector robustness remains a critical issue. Key points- A comprehensive head-to-head comparison of 11 detectors demonstrated significant variability in detector agreement and clinical utility - Clinical utility was not necessarily linked to the EEG recording type the detector was originally designed for - Despite widely accepted use of automatic detections, detector robustness remains a critical issue

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