Automated detection of ripple oscillations in long-term scalp EEG from patients with infantile spasms

摘要

Objective. Scalp high-frequency oscillations (HFOs) are a promising biomarker of epileptogenicityin infantile spasms (IS) and many other epilepsy syndromes, but prior studies have relied on visualanalysis of short segments of data due to the prevalence of artifacts in EEG. Here we set out torobustly characterize the rate and spatial distribution of HFOs in large datasets from IS subjectsusing fully automated HFO detection techniques. Approach. We prospectively collected long-termscalp EEG data from 12 subjects with IS and 18 healthy controls. For patients with IS, recordingbegan prior to diagnosis and continued through initiation of treatment with adrenocorticotropichormone (ACTH). The median analyzable EEG duration was 18.2 h for controls and 84.5 h for ISsubjects (∼1300 h total). Ripples (80–250 Hz) were detected in all EEG data using an automatedalgorithm. Main results. HFO rates were substantially higher in patients with IS compared tocontrols. In IS patients, HFO rates were higher during sleep compared to wakefulness (median 5.5min~(−1) and 2.9 min~(−1), respectively; p=0.002); controls did not exhibit a difference in HFO ratebetween sleep and wakefulness (median 0.98 min~(−1) and 0.82 min~(−1), respectively). Spatially, ISpatients exhibited significantly higher rates of HFOs in the posterior parasaggital region andsignificantly lower HFO rates in frontal channels, and this difference was more pronounced duringsleep. In IS subjects, ACTH therapy significantly decreased the rate of HFOs. Significance. Here weprovide a detailed characterization of the spatial distribution and rates of HFOs associated with IS,which may have relevance for diagnosis and assessment of treatment response. We alsodemonstrate that our fully automated algorithm can be used to detect HFOs in long-term scalpEEG with sufficient accuracy to clearly discriminate healthy subjects from those with IS.