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高频振荡并不优于棘波作为致痫性组织的生物标志物。

High-frequency oscillations are not better biomarkers of epileptogenic tissues than spikes.

机构信息

Aix Marseille Univ, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France.

APHM, Timone Hospital, Clinical Neurophysiology, Marseille, France.

出版信息

Ann Neurol. 2018 Jan;83(1):84-97. doi: 10.1002/ana.25124.

Abstract

OBJECTIVE

High-frequency oscillations (HFOs) in intracerebral EEG (stereoelectroencephalography; SEEG) are considered as better biomarkers of epileptogenic tissues than spikes. How this can be applied at the patient level remains poorly understood. We investigated how well HFOs and spikes can predict epileptogenic regions with a large spatial sampling at the patient level.

METHODS

We analyzed non-REM sleep SEEG recordings sampled at 2,048Hz of 30 patients. Ripples (Rs; 80-250Hz), fast ripples (FRs; 250-500Hz), and spikes were automatically detected. Rates of these markers and several combinations-spikes co-occurring with HFOs or FRs and cross-rate (Spk⊗HFO)-were compared to a quantified measure of the seizure onset zone (SOZ) by performing a receiver operating characteristic analysis for each patient individually. We used a Wilcoxon signed-rank test corrected for false-discovery rate to assess whether a marker was better than the others for predicting the SOZ.

RESULTS

A total of 2,930 channels was analyzed (median of 100 channels per patient). The HFOs or any of its variants were not statistically better than spikes. Only one feature, the cross-rate, was better than all the other markers. Moreover, fast ripples, even though very specific, were not delineating all epileptogenic tissues.

INTERPRETATION

At the patient level, the performance of HFOs is weakened by the presence of strong physiological HFO generators. Fast ripples are not sensitive enough to be the unique biomarker of epileptogenicity. Nevertheless, combining HFOs and spikes using our proposed measure-the cross-rate-is a better strategy than using only one marker. Ann Neurol 2018;83:84-97.

摘要

目的

与尖波相比,脑电(立体脑电图;SEEG)中的高频振荡(HFOs)被认为是更好的致痫灶生物标志物。但在患者层面上,这一方法如何应用尚不清楚。本研究旨在调查在患者层面上,HFOs 和尖波在大范围采样时,预测致痫区的能力。

方法

我们分析了 30 例患者的非快速眼动睡眠 SEEG 记录,采样频率为 2048Hz。自动检测到棘波(Rs;80-250Hz)、快棘波(FRs;250-500Hz)和尖波。对这些标记物的比率以及几种组合(尖波与 HFOs 或 FRs 同时出现,交叉比率(Spk⊗HFO))与量化的致痫灶起始区(SOZ)进行了比较,对每位患者分别进行了受试者工作特征分析。我们使用校正错误发现率的 Wilcoxon 符号秩检验来评估标记物是否优于其他标记物来预测 SOZ。

结果

共分析了 2930 个通道(每个患者中位数 100 个通道)。HFOs 或其任何变体在统计学上均不如尖波。只有一个特征,即交叉比率,优于所有其他标记物。此外,虽然快棘波具有很强的特异性,但不能描绘出所有的致痫组织。

结论

在患者层面上,由于存在强生理 HFO 发生器,HFOs 的性能受到削弱。快棘波的敏感性不足以成为唯一的致痫性生物标志物。然而,使用我们提出的方法(交叉比率)结合 HFOs 和尖波,比使用单一标记物更好。Ann Neurol 2018;83:84-97.

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