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首页> 外文期刊>Brain & Development >Localization of epileptogenic zones in Lennox-Gastaut syndrome (LGS) using graph theoretical analysis of ictal intracranial EEG: A preliminary investigation
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Localization of epileptogenic zones in Lennox-Gastaut syndrome (LGS) using graph theoretical analysis of ictal intracranial EEG: A preliminary investigation

机译:利用图谱分析颅内脑电图在Lennox-Gastaut综合征(LGS)中致癫痫区的定位:初步研究

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Introduction: Precise localization of epileptogenic zones is essential for the successful surgical treatment of refractory epilepsy including Lennox-Gastaut syndrome (LGS). The surgical resection areas are generally determined by epileptologists based on diverse neuroimaging modalities; however, exact epileptogenic zones cannot be accurately localized in many patients with LGS using the conventional methods. Therefore, new reliable algorithms are still required for enhancing the success rate of the resective epilepsy surgery. In the present study, we introduce an approach to localize epileptogenic zones in LGS based on the graph theoretical analysis of ical intracranial EEG (iEEG). Methods: Four patients with LGS who became seizure-free after the resective epilepsy surgery were selected. Before the surgery, their epileptogenic zones were delineated using EEG, iEEG, and several conventional imaging modalities. Phase locking value (PLV) analysis was applied to construct functional connectivity networks during ictal events, and then several graph theoretical indices including betweenness centrality (BC) were evaluated for each iEEG sensor to find the primary hubs of the ictal epileptic network. The graph theoretical index values were then overlaid on 3D individual cortical surface. Results: The iEEG channels with high BC values coincided well with the surgical resection areas. Among various graph theoretical measures such as local efficiency, participation coefficient, and eigenvector centrality, only BC showed fair correspondence with the surgical resection areas. Conclusions: The primary hubs in the ictal epileptic networks coincided well with areas of surgical resection in LGS patients with successful surgical outcomes. This observation warrants further studies to determine if the graph theoretical network analysis of ictal iEEG recordings can serve as a new auxiliary tool to localize epileptogenic zones in LGS. (C) 2014 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
机译:简介:癫痫发生区的精确定位对于成功手术治疗难治性癫痫(包括伦诺克斯-盖索特综合征(LGS))至关重要。外科切除区域通常由癫痫医师根据不同的神经影像学方法确定。然而,使用传统方法无法在许多LGS患者中准确定位精确的致癫痫区。因此,仍然需要新的可靠算法来提高切除性癫痫手术的成功率。在本研究中,我们基于颅内脑电图(iEEG)的图论分析,介绍了在LGS中定位癫痫发生区的方法。方法:选择4例切除性癫痫手术后无癫痫发作的LGS患者。手术前,使用EEG,iEEG和几种常规成像方式划定其癫痫发生区。将锁相值(PLV)分析应用于在发作事件期间构建功能连接网络,然后针对每个iEEG传感器评估了包括介电中心度(BC)在内的几种图形理论指标,以找到发作癫痫网络的主要枢纽。然后将图形理论指标值覆盖在3D单个皮质表面上。结果:高BC值的iEEG通道与手术切除区域重合。在各种图形理论测量方法中,例如局部效率,参与系数和特征向量中心性,只有BC与手术切除区域显示出合理的对应关系。结论:在成功手术结局的LGS患者中,发作性癫痫网络的主要枢纽与手术切除区域重合。该观察结果值得进一步研究,以确定ital记录的理论图网络分析是否可以作为在LGS中定位致痫区的新辅助工具。 (C)2014年日本儿童神经病学会。由Elsevier B.V.发布。保留所有权利。

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