基于颅内脑电的癫痫脑网络研究

发布时间：2018-07-05 15:11

  本文选题：癫痫病灶 + IEEG　； 参考：《电子科技大学》2014年硕士论文

【摘要】：难治性癫痫患者通常要进行手术干预,在术前,患者需要接受侵入式视频脑电监测(IVEM)来确定癫痫发作部位和范围。在先前的研究中,将计算得到的病灶区域与手术切除区域或者医生用肉眼定位的区域做比较,发现对颅内脑电进行因果连接分析有助于癫痫病灶区域的定位,但是手术切除区域和医生肉眼识别的区域都不能准确定义病灶的范围。本研究将颅内脑电的因果连接分析应用于已通过磁共振成像(MRI)探测出新皮质损伤的癫痫患者,以便验证脑电的因果连接方法定位癫痫病灶的准确性。本文研究了三个有新皮质损伤的难治性癫痫病患者,使用自适应有向传递函数(adaptive directed transfer function,ADTF)的时变的因果连接方法分析各个频段的脑电数据,得到三个患者的癫痫发作期间的皮层癫痫网络。之后结合图论的方法,分别使用两个图论指标,出度(out-degree)和中间中心性(betweenness-centrality)来找出癫痫网络中的关键节点。在三个病人中,计算得出的最大出度和中间中心性的电极与其他电极相比,离病灶部分更近,而中间中心性的结果比出度更接近病灶。另外,我们发现出度和中间中心性两种网络指标得到的结果都是跟频率相关的,频率更高的Gamma段(30—80Hz)跟病灶相关性更大,先前的研究也有类似发现。这项研究表明,对IEEG信号分析所得到的因果连接活动模式,有助于加深我们对于癫痫脑电传播机制的认识,同时有助于提高对难治性癫痫患者的病灶术前评估的准确性。这项研究同时表明,在癫痫病灶定位方面,相比于出度,中间中心性可能是一种更好的网络指标。
[Abstract]:Patients with refractory epilepsy usually undergo surgical intervention. Before operation, patients need to undergo invasive video EEG monitoring (IVEM) to determine the location and extent of epileptic seizures. In previous studies, the calculated focus areas were compared with those that were surgically removed or where doctors located them with the naked eye, and it was found that the causal connection analysis of intracranial EEG could help locate the epileptic foci. However, the surgical resection area and the region recognized by the doctor do not accurately define the extent of the lesion. In this study, the causal connection analysis of intracranial EEG was applied to the epileptic patients with new cortical injury detected by magnetic resonance imaging (MRI), in order to verify the accuracy of the cause-and-effect connection method of EEG in locating epileptic foci. In this paper, three patients with intractable epilepsy with new cortical damage were studied. The time-varying causal connection method of adaptive directed transfer function (adaptive directed transfer) was used to analyze EEG data in different frequency bands. The cortical epileptic network of three patients was obtained during epileptic seizures. Then, two graph theory indexes, out-degree and betweenness-centrality, are used to find the key nodes in the epileptic network. In the three patients, the calculated maximum outliers and mesocentric electrodes were closer to the lesion than the other electrodes, while the mesocentric results were closer to the focus than the other electrodes. In addition, we found that both the outlier and the mesocentric network results are frequency dependent, and the higher-frequency Gamma segment (30-80Hz) is more correlated with the lesion. Similar findings have been made in previous studies. This study shows that the causal link activity pattern obtained by IEEG signal analysis is helpful to deepen our understanding of the transmission mechanism of epileptic EEG and to improve the accuracy of preoperative evaluation of the lesions in patients with intractable epilepsy. The study also suggests that mesocentricity may be a better network indicator of epileptic foci than its outlier.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：R742.1
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本文编号：2100649