Gerner Nathalie, Thomschewski Aljoscha, Marcu Adrian, Trinka Eugen, Höller Yvonne
Department of Neurology, Christian-Doppler Medical Centre, Centre for Cognitive Neuroscience, Paracelsus Medical University, Salzburg, Austria.
Department of Mathematics, Paris-Lodron University of Salzburg, Salzburg, Austria.
Front Neurol. 2020 Jun 2;11:432. doi: 10.3389/fneur.2020.00432. eCollection 2020.
Intracranially recorded high-frequency oscillations (>80 Hz) are considered a candidate epilepsy biomarker. Recent studies claimed their detectability on the scalp surface. We aimed to investigate the applicability of high-frequency oscillation analysis to routine surface EEG obtained at an epilepsy monitoring unit. We retrospectively analyzed surface EEGs of 18 patients with focal epilepsy and six controls, recorded during sleep under maximal medication withdrawal. As a proof of principle, the occurrence of motor task-related events during wakefulness was analyzed in a subsample of six patients with seizure- or syncope-related motor symptoms. Ripples (80-250 Hz) and fast ripples (>250 Hz) were identified by semi-automatic detection. Using semi-parametric statistics, differences in spontaneous and task-related occurrence rates were examined within subjects and between diagnostic groups considering the factors diagnosis, brain region, ripple type, and task condition. We detected high-frequency oscillations in 17 out of 18 patients and in four out of six controls. Results did not show statistically significant differences in the mean rates of event occurrences, neither regarding the laterality of the epileptic focus, nor with respect to active and inactive task conditions, or the moving hand laterality. Significant differences in general spontaneous incidence [WTS(1) = 9.594; = 0.005] that indicated higher rates of fast ripples compared to ripples, notably in patients with epilepsy compared to the control group, may be explained by variations in data quality. The current analysis methods are prone to biases. A common agreement on a standard operating procedure is needed to ensure reliable and economic detection of high-frequency oscillations.
颅内记录的高频振荡（>80Hz）被认为是一种潜在的癫痫生物标志物。最近的研究称在头皮表面可检测到它们。我们旨在研究高频振荡分析在癫痫监测单元获取的常规头皮脑电图中的适用性。我们回顾性分析了18例局灶性癫痫患者和6例对照者在最大程度撤药睡眠期间记录的头皮脑电图。作为原理验证，在6例有癫痫发作或晕厥相关运动症状的患者亚组中分析了清醒时与运动任务相关事件的发生情况。通过半自动检测识别出涟漪（80 - 250Hz）和快速涟漪（>250Hz）。使用半参数统计，考虑诊断、脑区、涟漪类型和任务条件等因素，在受试者内部和诊断组之间检查自发和任务相关发生率的差异。我们在18例患者中的17例以及6例对照者中的4例检测到了高频振荡。结果在事件发生的平均率方面未显示出统计学上的显著差异，无论是关于癫痫病灶的侧别，还是关于活跃和不活跃任务条件，或移动手的侧别。一般自发发生率的显著差异[WTS(1) = 9.594；P = 0.005]表明快速涟漪的发生率高于涟漪，特别是在癫痫患者与对照组相比时，这可能由数据质量的差异来解释。当前的分析方法容易产生偏差。需要就标准操作程序达成共识，以确保可靠且经济地检测高频振荡。
