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全面强直阵挛发作癫痫儿童灰质结构协方差网络拓扑属性受损:一项图论分析

Impaired Topological Properties of Gray Matter Structural Covariance Network in Epilepsy Children With Generalized Tonic-Clonic Seizures: A Graph Theoretical Analysis.

作者信息

Li Yongxin, Wang Ya, Wang Yanfang, Wang Huirong, Li Ding, Chen Qian, Huang Wenhua

机构信息

Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.

Guangdong Provincial Key Laboratory of Medical Biomechanics, School of Basic Medical Sciences, Southern Medical University, Guangzhou, China.

出版信息

Front Neurol. 2020 Apr 16;11:253. doi: 10.3389/fneur.2020.00253. eCollection 2020.

DOI:10.3389/fneur.2020.00253
PMID:32373045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7176815/
Abstract

Modern network science has provided exciting new opportunities for understanding the human brain as a complex network of interacting regions. The improved knowledge of human brain network architecture has made it possible for clinicians to detect the network changes in neurological diseases. Generalized tonic-clonic seizure (GTCS) is a subtype of epilepsy characterized by generalized spike-wave discharge involving the bilateral hemispheres during seizure. Network researches in adults with GTCS exhibited that GTCS can be conceptualized as a network disorder. However, the overall organization of the brain structural covariance network in children with GTCS remains largely unclear. Here, we used a graph theory method to assess the gray matter structural covariance network organization of 14 pediatric patients diagnosed with GTCS and 29 healthy control children. The group differences in regional and global topological properties were investigated. Results revealed significant changes in nodal betweenness locating in brain regions known to be abnormal in GTCS (the right thalamus, bilateral temporal pole, and some regions of default mode network). The network hub analysis results were in accordance with the regional betweenness, which presented a disrupted regional topology of structural covariance network in children with GTCS. To our knowledge, the present study is the first work reporting the changes of structural topological properties in children with GTCS. The findings contribute new insights into the understanding of the neural mechanisms underlying GTCS and highlight critical regions for future neuroimaging research in children with GTCS.

摘要

现代网络科学为将人类大脑理解为一个由相互作用区域构成的复杂网络提供了令人兴奋的新机遇。对人类脑网络架构的深入了解使临床医生能够检测神经系统疾病中的网络变化。全面强直阵挛发作(GTCS)是癫痫的一种亚型,其特征是发作期间涉及双侧半球的全面棘波放电。针对成年GTCS患者的网络研究表明,GTCS可被视为一种网络障碍。然而,GTCS患儿脑结构协方差网络的整体组织情况仍 largely 不清楚。在此,我们使用图论方法评估了14名被诊断为GTCS的儿科患者和29名健康对照儿童的灰质结构协方差网络组织。研究了区域和全局拓扑属性的组间差异。结果显示,位于GTCS中已知异常的脑区(右侧丘脑、双侧颞极和默认模式网络的一些区域)的节点介数有显著变化。网络枢纽分析结果与区域介数一致,这表明GTCS患儿的结构协方差网络区域拓扑结构遭到破坏。据我们所知,本研究是首次报道GTCS患儿结构拓扑属性变化的工作。这些发现为理解GTCS潜在的神经机制提供了新见解,并突出了GTCS患儿未来神经影像学研究的关键区域。

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