Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
Department of Neurology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin.
Epilepsia. 2019 Sep;60(9):1838-1848. doi: 10.1111/epi.16290. Epub 2019 Jul 26.
Benign epilepsy with centrotemporal spikes (BECTS) is the most common childhood idiopathic localization-related epilepsy syndrome. BECTS presents normal routine magnetic resonance imaging (MRI); however, quantitative analytic techniques have captured subtle cortical and subcortical magnetic resonance anomalies. Network science, including graph theory (GT) analyses, facilitates understanding of brain covariance patterns, potentially informing in important ways how this common self-limiting epilepsy syndrome may impact normal patterns of brain and cognitive development.
GT analyses examined the developmental covariance among cortical and subcortical regions in children with new/recent onset BECTS (n = 19) and typically developing healthy controls (n = 22) who underwent high-resolution MRI and cognitive assessment at baseline and 2 years later. Global (transitivity, global efficiency, and modularity index [Q]) and regional measures (local efficiency and hubs) were investigated to characterize network development in each group. Associations between baseline-based GT measures and cognition at both time points addressed the implications of GT analyses for cognition and prospective cognitive development. Furthermore, an individual contribution measure was investigated, reflecting how important for cognition it is for BECTS to resemble the correlation matrices of controls.
Groups exhibited similar Q and overall network configuration, with BECTS presenting significantly higher transitivity and both global and local efficiency. Furthermore, both groups presented a similar number of hubs, with BECTS showing a higher number in temporal lobe regions compared to controls. The investigated measures were negatively associated with 2-year cognitive outcomes in BECTS.
Children with BECTS present a higher-than-normal global developmental configuration compared to controls, along with divergence from normality in terms of regional configuration. Baseline GT measures demonstrate potential as a cognitive biomarker to predict cognitive outcome in BECTS 2 years after diagnosis. Similarities and differences in developmental network configurations and their implications for cognition and behavior across common epilepsy syndromes are of theoretical interest and clinical relevance.
良性癫痫伴中央颞区棘波（BECTS）是最常见的儿童特发性局灶性相关癫痫综合征。BECTS 表现为常规磁共振成像（MRI）正常；然而，定量分析技术已经捕捉到了皮质和皮质下的细微磁共振异常。网络科学，包括图论（GT）分析，有助于理解大脑协方差模式，可能以重要的方式告知这种常见的自限性癫痫综合征如何影响大脑和认知发育的正常模式。
GT 分析检查了新/近期发作 BECTS 患儿（n=19）和正常发育健康对照组（n=22）皮质和皮质下区域之间的发育协方差，这些患儿在基线和 2 年后接受了高分辨率 MRI 和认知评估。研究了全局（传递性、全局效率和模块指数[Q]）和区域指标（局部效率和枢纽），以描述每组网络的发展。基于基线的 GT 指标与两个时间点的认知之间的关联解决了 GT 分析对认知和前瞻性认知发展的影响。此外，还研究了个体贡献指标，反映了 BECTS 与对照组的相关矩阵相似对认知的重要性。
两组的 Q 和整体网络结构相似，BECTS 的传递性和全局及局部效率显著较高。此外，两组都有相似数量的枢纽，BECTS 比对照组在颞叶区域有更多的枢纽。所研究的指标与 BECTS 的 2 年认知结果呈负相关。
与对照组相比，BECTS 患儿的全球发育结构高于正常水平，区域结构也偏离正常。基线 GT 指标具有作为认知生物标志物的潜力，可以预测 BECTS 诊断后 2 年的认知结果。常见癫痫综合征之间发育网络结构的相似性和差异及其对认知和行为的影响具有理论意义和临床相关性。
