Yan Peter, Melman Tamar, Yan Sherry, Otgonsuren Munkhzul, Grinspan Zachary
Weill Cornell Medical College, Department of Neurology, United States; Weill Cornell Medical College, Department of Health Policy and Research, United States.
Weill Cornell Medical College, Feil Family Brain and Mind Research Institute, United States.
Seizure. 2017 Aug;50:109-117. doi: 10.1016/j.seizure.2017.06.016. Epub 2017 Jun 15.
(1) To evaluate how well resident physicians use a novel EEG spectral analysis tool (the median power spectrogram; MPS) to detect seizures. (2) To assess the capability of the MPS to identify different seizure types.
120 EEG records from children with intractable seizures were converted to MPS by taking the median power across leads and using multi-taper spectral estimation. Twelve blinded neurology residents were trained to interpret the spectrogram with a five-minute video tutorial and post-test. Two residents independently assessed each set for presence of seizures. Their performance was compared to seizures identified using conventional EEG. Two blinded neurologists separately reviewed the EEGs and spectrograms to independently categorize the seizures. Their results were used to determine the spectrogram's capability to reveal seizures and visualize different seizure types for the user.
Three key MPS features distinguished seizures from inter-ictal background: power difference relative to background, down-sloping resonance bands, and power in high frequencies. Using these features, residents identified seizures with 77% sensitivity and 72% specificity. 86% (51/59) of focal seizures and 81% (22/27) of generalized seizures were detected by at least one resident. Missed seizures included brief (<60s) seizures, tonic seizures, seizures with predominant delta (0-4Hz) activity, and seizures evident primarily in supplementary low temporal leads.
The MPS is a novel qEEG modality that requires minimal training to interpret. It enables physicians without extensive neurophysiology training to identify seizures with sensitivity and specificity comparable to more complex multi-modal qEEG displays.
(1)评估住院医师使用新型脑电图频谱分析工具(中位数功率谱图;MPS)检测癫痫发作的效果。(2)评估MPS识别不同癫痫发作类型的能力。
通过跨导联取中位数功率并使用多窗谱估计,将120例难治性癫痫患儿的脑电图记录转换为MPS。12名不知情的神经科住院医师通过5分钟的视频教程和测试后培训来解读频谱图。两名住院医师独立评估每组是否存在癫痫发作。将他们的表现与使用传统脑电图识别的癫痫发作进行比较。两名不知情的神经科医生分别审查脑电图和频谱图,以独立对癫痫发作进行分类。他们的结果用于确定频谱图对用户揭示癫痫发作和可视化不同癫痫发作类型的能力。
MPS的三个关键特征将癫痫发作与发作间期背景区分开来:相对于背景的功率差异、向下倾斜的共振带和高频功率。利用这些特征,住院医师识别癫痫发作的灵敏度为77%,特异度为72%。至少一名住院医师检测到86%(51/59)的局灶性癫痫发作和81%(22/27)的全身性癫痫发作。漏诊的癫痫发作包括短暂(<60秒)癫痫发作、强直发作、以δ波(0-4Hz)活动为主的癫痫发作以及主要在颞叶下部辅助导联明显的癫痫发作。
MPS是一种新型定量脑电图模式,解读所需培训极少。它使没有广泛神经生理学培训的医生能够以与更复杂的多模式定量脑电图显示相当的灵敏度和特异度识别癫痫发作。