Pyrzowski Jan, Siemiński Mariusz, Sarnowska Anna, Jedrzejczak Joanna, Nyka Walenty M
Department of Adult Neurology, Medical University of Gdansk, Poland.
Department of Neurology and Epileptology, Medical Centre for Postgraduate Education, Warsaw, Poland.
Sci Rep. 2015 Nov 10;5:16230. doi: 10.1038/srep16230.
The contemporary use of interictal scalp electroencephalography (EEG) in the context of focal epilepsy workup relies on the visual identification of interictal epileptiform discharges. The high-specificity performance of this marker comes, however, at a cost of only moderate sensitivity. Zero-crossing interval analysis is an alternative to Fourier analysis for the assessment of the rhythmic component of EEG signals. We applied this method to standard EEG recordings of 78 patients divided into 4 subgroups: temporal lobe epilepsy (TLE), frontal lobe epilepsy (FLE), psychogenic nonepileptic seizures (PNES) and nonepileptic patients with headache. Interval-analysis based markers were capable of effectively discriminating patients with epilepsy from those in control subgroups (AUC0.8) with diagnostic sensitivity potentially exceeding that of visual analysis. The identified putative epilepsy-specific markers were sensitive to the properties of the alpha rhythm and displayed weak or non-significant dependences on the number of antiepileptic drugs (AEDs) taken by the patients. Significant AED-related effects were concentrated in the theta interval range and an associated marker allowed for identification of patients on AED polytherapy (AUC0.9). Interval analysis may thus, in perspective, increase the diagnostic yield of interictal scalp EEG. Our findings point to the possible existence of alpha rhythm abnormalities in patients with epilepsy.
在局灶性癫痫检查中，目前使用发作间期头皮脑电图（EEG）依赖于对发作间期癫痫样放电的视觉识别。然而，该标志物的高特异性是以仅中等敏感性为代价的。过零间隔分析是一种用于评估EEG信号节律成分的替代傅里叶分析的方法。我们将该方法应用于78例患者的标准EEG记录，这些患者分为4个亚组：颞叶癫痫（TLE）、额叶癫痫（FLE）、精神性非癫痫发作（PNES）和非癫痫性头痛患者。基于间隔分析的标志物能够有效地区分癫痫患者与对照组亚组中的患者（AUC0.8），其诊断敏感性可能超过视觉分析。所确定的假定癫痫特异性标志物对α节律的特性敏感，并且对患者服用的抗癫痫药物（AEDs）数量显示出弱的或无显著相关性。与AED相关的显著效应集中在θ间隔范围内，并且一个相关的标志物能够识别接受AED联合治疗的患者（AUC0.9）。因此，从长远来看，间隔分析可能会提高发作间期头皮EEG的诊断率。我们的研究结果表明癫痫患者可能存在α节律异常。
