Kienitz Ricardo, Strüber Michael, Merkel Nina, Süß Annika, Spyrantis Andrea, Strzelczyk Adam, Rosenow Felix
Goethe University Frankfurt, Epilepsy Center Frankfurt Rhine-Main, Department of Neurology, University Hospital Frankfurt, Frankfurt, Germany.
LOEWE Center for Personalized Translational Epilepsy Research (CePTER), Goethe University Frankfurt, Frankfurt, Germany.
Epilepsia. 2025 Mar;66(3):790-801. doi: 10.1111/epi.18218. Epub 2024 Dec 12.
To date, the identification of objective biomarkers of neural epileptic activity (EA) remains challenging. We therefore investigated whether neuronal complexity could serve as an interictal electroencephalographic measure of EA, independent of interictal epileptiform discharges (IEDs). By tapering anti-seizure medication (ASM) during video-EEG (electroencephalography) monitoring (VEM), we studied whether changes in neuronal complexity could reliably indicate the increase in EA and identify patients with epilepsy.
The study included 27 patients with unilateral mesial temporal lobe epilepsy (TLE) and 24 control patients with non-epileptic episodes (NEEs) only, each undergoing ASM reduction during VEM. Thirteen additional patients undergoing intracranial recordings during VEM were included to study the relation of surface EEG complexity to intracranial IED. Neuronal complexity was quantified using sample entropy. Delta power served as a control parameter. Receiver-operating characteristic (ROC) analysis was used to evaluate diagnostic performance.
As ASM was reduced, patients with epilepsy showed a significant decrease in neuronal complexity over consecutive days (p = .0008). In contrast, patients with NEE showed no significant change in neuronal complexity (p = .78). Delta power in contrast increased and did not differ significantly between patients with TLE and patients with NEE (p = 1). ROC analysis demonstrated that neuronal complexity effectively distinguished between patients with epilepsy and patients with NEE (area under the curve [AUC] = .76), whereas delta power performed at chance level (AUC = .5). Analysis of simultaneously recorded surface and intracranial EEG showed that hippocampal IEDs are followed by an increase in surface EEG delta power (p = 1.8 × 10) without any significant change in complexity (p = .39).
An increase in EA caused by ASM reduction resulted in a loss of neuronal complexity in surface EEG recordings of patients with epilepsy, independent of IEDs. These findings suggest that neuronal complexity could serve as a potential biomarker to differentiate between epilepsy patients and those with NEEs only. This holds promise for improving the clinical evaluation of EA in epilepsy, addressing the limitations of seizure frequency and IED identification.
迄今为止，识别神经癫痫活动（EA）的客观生物标志物仍然具有挑战性。因此，我们研究了神经元复杂性是否可以作为一种独立于发作间期癫痫样放电（IED）的EA发作间期脑电图测量指标。通过在视频脑电图（EEG）监测（VEM）期间逐渐减少抗癫痫药物（ASM），我们研究了神经元复杂性的变化是否能够可靠地表明EA的增加，并识别癫痫患者。
该研究纳入了27例单侧内侧颞叶癫痫（TLE）患者和24例仅患有非癫痫发作（NEE）的对照患者，每位患者在VEM期间均进行了ASM减量。另外纳入了13例在VEM期间进行颅内记录的患者，以研究头皮脑电图复杂性与颅内IED的关系。使用样本熵对神经元复杂性进行量化。δ波功率作为对照参数。采用受试者操作特征（ROC）分析来评估诊断性能。
随着ASM的减少，癫痫患者的神经元复杂性在连续几天内显著降低（p = 0.0008）。相比之下，NEE患者的神经元复杂性没有显著变化（p = 0.78）。相反，δ波功率增加，TLE患者和NEE患者之间没有显著差异（p = 1）。ROC分析表明，神经元复杂性能够有效地区分癫痫患者和NEE患者（曲线下面积[AUC] = 0.76），而δ波功率的表现处于随机水平（AUC = 0.5）。对同时记录的头皮和颅内脑电图的分析表明，海马区IED之后头皮脑电图δ波功率增加（p = 1.8×10），而复杂性没有任何显著变化（p = 0.39）。
ASM减少导致的EA增加导致癫痫患者头皮脑电图记录中神经元复杂性丧失，与IED无关。这些发现表明，神经元复杂性可以作为区分癫痫患者和仅患有NEE患者的潜在生物标志物。这有望改善癫痫中EA的临床评估，解决发作频率和IED识别的局限性。
