Herta J, Koren J, Fürbass F, Hartmann M, Gruber A, Baumgartner C
Department of Neurosurgery, Medical University of Vienna, Vienna, Austria.
Karl Landsteiner Institute for Clinical Epilepsy Research and Cognitive Neurology, 2nd Neurological Department, General Hospital Hietzing with Neurological Center Rosenhuegel, Vienna, Austria.
Clin Neurophysiol. 2017 Aug;128(8):1524-1531. doi: 10.1016/j.clinph.2017.04.012. Epub 2017 Apr 26.
To investigate the effect of systematic electrode reduction from a common 10-20 EEG system on pattern detection sensitivity (SEN).
Two reviewers rated 17130 one-minute segments of 83 prospectively recorded cEEGs according to the ACNS standardized critical care EEG terminology (CCET), including burst suppression patterns (BS) and unequivocal electrographic seizures. Consensus annotations between reviewers were used as a gold standard to determine pattern detection SEN and specificity (SPE) of a computational algorithm (baseline, 19 electrodes). Electrodes were than reduced one by one in four different variations. SENs and SPEs were calculated to determine the most beneficial assembly with respect to the number and location of electrodes.
High automated baseline SENs (84.99-93.39%) and SPEs (90.05-95.6%) were achieved for all patterns. Best overall results in detecting BS and CCET patterns were found using the "hairline+vertex" montage. While the "forehead+behind ear" montage showed an advantage in detecting ictal patterns, reaching a 15% drop of SEN with 10 electrodes, all montages could detect BS sufficiently if at least nine electrodes were available.
For the first time an automated approach was used to systematically evaluate the effect of electrode reduction on pattern detection SEN in cEEG.
Prediction of the expected detection SEN of specific EEG patterns with reduced EEG montages in ICU patients.
研究从常见的10-20脑电图系统进行系统性电极减少对模式检测灵敏度(SEN)的影响。
两名审阅者根据美国临床神经生理学会(ACNS)标准化的重症监护脑电图术语(CCET),对83份前瞻性记录的连续脑电图(cEEG)的17130个一分钟片段进行评分,包括爆发抑制模式(BS)和明确的脑电图癫痫发作。审阅者之间的一致注释用作金标准,以确定计算算法(基线,19个电极)的模式检测SEN和特异性(SPE)。然后以四种不同的变体逐个减少电极。计算SEN和SPE,以确定关于电极数量和位置的最有利组合。
所有模式均实现了较高的自动基线SEN(84.99%-93.39%)和SPE(90.05%-95.6%)。使用“发际线+顶点”组合在检测BS和CCET模式方面获得了最佳总体结果。虽然“前额+耳后”组合在检测发作期模式方面显示出优势,在使用10个电极时SEN下降了15%,但如果至少有9个电极可用,所有组合都能充分检测到BS。
首次使用自动化方法系统评估电极减少对cEEG模式检测SEN的影响。
预测ICU患者脑电图组合减少时特定脑电图模式的预期检测SEN。