Department of Circuit Theory, Faculty of Electrical Engineering, Czech Technical University in Prague, Prague, Czech Republic; Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic.
Department of Paediatric Neurology, Full Member of the ERN EpiCAR, Second Faculty of Medicine, Charles University and Motol University Hospital, Prague, Czech Republic.
Clin Neurophysiol. 2021 Aug;132(8):1927-1936. doi: 10.1016/j.clinph.2021.04.016. Epub 2021 May 26.
Epilepsy surgery fails in > 30% of patients with focal cortical dysplasia (FCD). The seizure persistence after surgery can be attributed to the inability to precisely localize the tissue with an endogenous potential to generate seizures. In this study, we aimed to identify the critical components of the epileptic network that were actively involved in seizure genesis.
The directed transfer function was applied to intracranial EEG recordings and the effective connectivity was determined with a high temporal and frequency resolution. Pre-ictal network properties were compared with ictal epochs to identify regions actively generating ictal activity and discriminate them from the areas of propagation.
Analysis of 276 seizures from 30 patients revealed the existence of a seizure-related network reconfiguration in the gamma-band (25-170 Hz; p < 0.005) - ictogenic nodes. Unlike seizure onset zone, resecting the majority of ictogenic nodes correlated with favorable outcomes (p < 0.012).
The prerequisite to successful epilepsy surgery is the accurate identification of brain areas from which seizures arise. We show that in FCD-related epilepsy, gamma-band network markers can reliably identify and distinguish ictogenic areas in macroelectrode recordings, improve intracranial EEG interpretation and better delineate the epileptogenic zone.
Ictogenic nodes localize the critical parts of the epileptogenic tissue and increase the diagnostic yield of intracranial evaluation.
在患有局灶性皮质发育不良（FCD）的患者中，> 30%的癫痫手术失败。手术后癫痫持续存在可归因于无法精确定位具有内生潜力引发癫痫发作的组织。在这项研究中，我们旨在确定积极参与癫痫发作发生的癫痫网络的关键组成部分。
应用有向传递函数对颅内 EEG 记录进行分析，并以高时间和频率分辨率确定有效连接。将发作前期网络特性与发作期进行比较，以识别主动产生发作活动的区域，并将其与传播区域区分开来。
对 30 名患者的 276 次癫痫发作进行分析，揭示了在γ频带（25-170 Hz；p < 0.005）中存在与癫痫发作相关的网络重构 - 致痫节点。与发作起始区不同，切除大多数致痫节点与良好的结果相关（p < 0.012）。
成功的癫痫手术的前提是准确识别癫痫发作起源的脑区。我们表明，在 FCD 相关癫痫中，γ频带网络标志物可在宏观电极记录中可靠地识别和区分致痫区，提高颅内 EEG 解释能力，并更好地描绘致痫区。
致痫节点定位了致痫组织的关键部分，并提高了颅内评估的诊断效果。
