Yang Shengyu, Wu Ying, Sun Lanfeng, You Xiao, Wu Yuan
Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Department of Neurology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
Epilepsy Behav. 2023 Mar;140:109101. doi: 10.1016/j.yebeh.2023.109101. Epub 2023 Feb 1.
The white matter structural network changes remain poorly understood in patients with temporal lobe epilepsy and comorbid headache (PWH). This study aimed at exploring topological changes in the structural network.
Twenty-five PWH, 32 patients with temporal lobe epilepsy without headache, and 22 healthy controls were recruited in this study. High-resolution structural MRI and diffusion tensor imaging data were acquired from these participants. A graph theory-based approach was employed to characterize the topological properties of the structural network. A network-based statistical analysis was employed to explore abnormal connectivity alterations in PWH.
Compared with healthy controls, PWH exhibited significantly decreased small-world index, shortest path length, increased clustering coefficient, global efficiency, and local efficiency. Patients with temporal lobe epilepsy and comorbid headache displayed a significantly reduced small-world index, shortest path length, and increased global efficiency when compared with patients with temporal lobe epilepsy without headache. In addition, PWH exhibited abnormal local network parameters, mainly located in the prefrontal, temporal, occipital, and parietal regions. Furthermore, network-based statistical analysis revealed that PWH had abnormal structural connections between the temporoparietal lobe, occipital lobe, insula, cingulate gyrus, and thalamus.
This study reveals the abnormal white matter structural network alterations in PWH, allowing a better insight into the neuroanatomical mechanisms that predispose epileptic patients to comorbid headaches from the network levels.
颞叶癫痫合并头痛（PWH）患者的白质结构网络变化仍未得到充分了解。本研究旨在探索结构网络的拓扑变化。
本研究招募了25名PWH患者、32名无头痛的颞叶癫痫患者和22名健康对照者。从这些参与者身上获取了高分辨率结构MRI和扩散张量成像数据。采用基于图论的方法来表征结构网络的拓扑特性。采用基于网络的统计分析来探索PWH患者异常的连接改变。
与健康对照相比，PWH患者的小世界指数、最短路径长度显著降低，聚类系数、全局效率和局部效率增加。与无头痛的颞叶癫痫患者相比，颞叶癫痫合并头痛患者的小世界指数、最短路径长度显著降低，全局效率增加。此外，PWH患者表现出异常的局部网络参数，主要位于前额叶、颞叶、枕叶和顶叶区域。此外，基于网络的统计分析显示，PWH患者在颞顶叶、枕叶、岛叶、扣带回和丘脑之间存在异常的结构连接。
本研究揭示了PWH患者白质结构网络的异常改变，有助于从网络层面更好地理解使癫痫患者易患合并头痛的神经解剖学机制。
