Fredrik K. Andersson , Helena Gauffin , Hans Lindehammar , Patrick Vigren
{"title":"基于视频的抗药性癫痫发作自动检测：前瞻性探索研究","authors":"Fredrik K. Andersson , Helena Gauffin , Hans Lindehammar , Patrick Vigren","doi":"10.1016/j.yebeh.2024.110118","DOIUrl":null,"url":null,"abstract":"<div><h3>Objective</h3><div>The objective of this study was to evaluate the diagnostic yield and clinical utility of an automated AI video-based seizure detection device, Nelli®, (SDD) in pharmacoresistant epilepsy patients. The SDD captures and automatically classifies nocturnal motor behavior suggestive of epileptic seizures or non-epileptic motor behavior of potential clinical value.</div></div><div><h3>Methods</h3><div>Patients with focal epilepsy and pharmacoresistance referred for inpatient long-term video-EEG monitoring were prospectively recruited. Participants were monitored in their home at night with the SDD for a median of 15.5 nights. Captured video recordings were analyzed by clinical experts and each SDD-registration session was classified as diagnostic or not. Clinical utility for each participant was assessed from pre-specified utility measures. The outcome measures were compared between major focal motor and subtle focal motor seizures.</div></div><div><h3>Results</h3><div>One SDD-registration session in each of the 20 participants was performed and analyzed. Video recordings were captured in 18 sessions. Diagnostic yield was found in 11 registration sessions (55.0 %) and clinical utility in 8 registration sessions (40.0 %). No significant difference was found between the AI-algorithm classification and clinical experts’ consensus assessment of captured video recordings as epileptic or not. Positive predictive value was 81.8 % for registration sessions containing video recordings classified as epileptic seizures. The diagnostic yield and clinical utility were significantly higher among major focal motor seizures (81.8 % and 63.6 %) compared to subtle focal motor seizures.</div></div><div><h3>Significance</h3><div>The SDD is useful to evaluate patients with pharmacoresistant epilepsy and major focal motor seizures (hyperkinetic, tonic, clonic, focal to bilateral tonic-clonic seizures); it may facilitate the diagnostic process in patients referred for long-term inpatient video-EEG evaluation and beneficially change anti-seizure treatments. The SDD provided accurate classification of major focal motor seizures as epileptic, or non-epileptic, and may serve as a useful diagnostic tool to distinguish epileptic and non-epileptic episodic events with a prominent motor component.</div></div>","PeriodicalId":11847,"journal":{"name":"Epilepsy & Behavior","volume":"161 ","pages":"Article 110118"},"PeriodicalIF":2.3000,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Video-based automatic seizure detection in pharmacoresistant epilepsy: A prospective exploratory study\",\"authors\":\"Fredrik K. Andersson , Helena Gauffin , Hans Lindehammar , Patrick Vigren\",\"doi\":\"10.1016/j.yebeh.2024.110118\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><h3>Objective</h3><div>The objective of this study was to evaluate the diagnostic yield and clinical utility of an automated AI video-based seizure detection device, Nelli®, (SDD) in pharmacoresistant epilepsy patients. The SDD captures and automatically classifies nocturnal motor behavior suggestive of epileptic seizures or non-epileptic motor behavior of potential clinical value.</div></div><div><h3>Methods</h3><div>Patients with focal epilepsy and pharmacoresistance referred for inpatient long-term video-EEG monitoring were prospectively recruited. Participants were monitored in their home at night with the SDD for a median of 15.5 nights. Captured video recordings were analyzed by clinical experts and each SDD-registration session was classified as diagnostic or not. Clinical utility for each participant was assessed from pre-specified utility measures. The outcome measures were compared between major focal motor and subtle focal motor seizures.</div></div><div><h3>Results</h3><div>One SDD-registration session in each of the 20 participants was performed and analyzed. Video recordings were captured in 18 sessions. Diagnostic yield was found in 11 registration sessions (55.0 %) and clinical utility in 8 registration sessions (40.0 %). No significant difference was found between the AI-algorithm classification and clinical experts’ consensus assessment of captured video recordings as epileptic or not. Positive predictive value was 81.8 % for registration sessions containing video recordings classified as epileptic seizures. The diagnostic yield and clinical utility were significantly higher among major focal motor seizures (81.8 % and 63.6 %) compared to subtle focal motor seizures.</div></div><div><h3>Significance</h3><div>The SDD is useful to evaluate patients with pharmacoresistant epilepsy and major focal motor seizures (hyperkinetic, tonic, clonic, focal to bilateral tonic-clonic seizures); it may facilitate the diagnostic process in patients referred for long-term inpatient video-EEG evaluation and beneficially change anti-seizure treatments. The SDD provided accurate classification of major focal motor seizures as epileptic, or non-epileptic, and may serve as a useful diagnostic tool to distinguish epileptic and non-epileptic episodic events with a prominent motor component.</div></div>\",\"PeriodicalId\":11847,\"journal\":{\"name\":\"Epilepsy & Behavior\",\"volume\":\"161 \",\"pages\":\"Article 110118\"},\"PeriodicalIF\":2.3000,\"publicationDate\":\"2024-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Epilepsy & Behavior\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1525505024005006\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BEHAVIORAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epilepsy & Behavior","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1525505024005006","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BEHAVIORAL SCIENCES","Score":null,"Total":0}
Video-based automatic seizure detection in pharmacoresistant epilepsy: A prospective exploratory study
Objective
The objective of this study was to evaluate the diagnostic yield and clinical utility of an automated AI video-based seizure detection device, Nelli®, (SDD) in pharmacoresistant epilepsy patients. The SDD captures and automatically classifies nocturnal motor behavior suggestive of epileptic seizures or non-epileptic motor behavior of potential clinical value.
Methods
Patients with focal epilepsy and pharmacoresistance referred for inpatient long-term video-EEG monitoring were prospectively recruited. Participants were monitored in their home at night with the SDD for a median of 15.5 nights. Captured video recordings were analyzed by clinical experts and each SDD-registration session was classified as diagnostic or not. Clinical utility for each participant was assessed from pre-specified utility measures. The outcome measures were compared between major focal motor and subtle focal motor seizures.
Results
One SDD-registration session in each of the 20 participants was performed and analyzed. Video recordings were captured in 18 sessions. Diagnostic yield was found in 11 registration sessions (55.0 %) and clinical utility in 8 registration sessions (40.0 %). No significant difference was found between the AI-algorithm classification and clinical experts’ consensus assessment of captured video recordings as epileptic or not. Positive predictive value was 81.8 % for registration sessions containing video recordings classified as epileptic seizures. The diagnostic yield and clinical utility were significantly higher among major focal motor seizures (81.8 % and 63.6 %) compared to subtle focal motor seizures.
Significance
The SDD is useful to evaluate patients with pharmacoresistant epilepsy and major focal motor seizures (hyperkinetic, tonic, clonic, focal to bilateral tonic-clonic seizures); it may facilitate the diagnostic process in patients referred for long-term inpatient video-EEG evaluation and beneficially change anti-seizure treatments. The SDD provided accurate classification of major focal motor seizures as epileptic, or non-epileptic, and may serve as a useful diagnostic tool to distinguish epileptic and non-epileptic episodic events with a prominent motor component.
期刊介绍：
Epilepsy & Behavior is the fastest-growing international journal uniquely devoted to the rapid dissemination of the most current information available on the behavioral aspects of seizures and epilepsy.
Epilepsy & Behavior presents original peer-reviewed articles based on laboratory and clinical research. Topics are drawn from a variety of fields, including clinical neurology, neurosurgery, neuropsychiatry, neuropsychology, neurophysiology, neuropharmacology, and neuroimaging.
From September 2012 Epilepsy & Behavior stopped accepting Case Reports for publication in the journal. From this date authors who submit to Epilepsy & Behavior will be offered a transfer or asked to resubmit their Case Reports to its new sister journal, Epilepsy & Behavior Case Reports.
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