Zhang Zhiqiang, Liao Wei, Xu Qiang, Wei Wei, Zhou Helen Juan, Sun Kangjian, Yang Fang, Mantini Dante, Ji Xueman, Lu Guangming
Department of Medical Imaging, Jinling Hospital, Nanjing University School of Medicine, Nanjing, 210002, China.
State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210093, China.
Hum Brain Mapp. 2017 Feb;38(2):753-766. doi: 10.1002/hbm.23415. Epub 2016 Sep 28.
In mesial temporal lobe epilepsy (mTLE), the causal relationship of morphometric alterations between hippocampus and the other regions, that is, how the hippocampal atrophy leads to progressive morphometric alterations in the epileptic network regions remains largely unclear. In this study, a causal network of structural covariance (CaSCN) was proposed to map the causal effects of hippocampal atrophy on the network-based morphometric alterations in mTLE. It was hypothesized that if cross-sectional morphometric MRI data could be attributed temporal information, for example, by sequencing the data according to disease progression information, GCA would be a feasible approach for constructing a CaSCN. Based on a large cohort of mTLE patients (n = 108), the hippocampus-associated CaSCN revealed that the hippocampus and the thalamus were prominent nodes exerting causal effects (i.e., GM reduction) on other regions and that the prefrontal cortex and cerebellum were prominent nodes being subject to causal effects. Intriguingly, compensatory increased gray matter volume in the contralateral temporal region and post cingulate cortex were also detected. The method unraveled richer information for mapping network atrophy in mTLE relative to the traditional methods of stage-specific comparisons and structured covariance network. This study provided new evidence on the network spread mechanism in terms of the causal influence of hippocampal atrophy on progressive brain structural alterations in mTLE. Hum Brain Mapp 38:753-766, 2017. © 2016 Wiley Periodicals, Inc.
在内侧颞叶癫痫(mTLE)中,海马体与其他区域之间形态学改变的因果关系,即海马萎缩如何导致癫痫网络区域的渐进性形态学改变,在很大程度上仍不清楚。在本研究中,提出了一个结构协方差因果网络(CaSCN)来描绘海马萎缩对mTLE中基于网络的形态学改变的因果效应。假设如果横断面形态学MRI数据能够被赋予时间信息,例如,通过根据疾病进展信息对数据进行排序,广义因果分析(GCA)将是构建CaSCN的一种可行方法。基于一大群mTLE患者(n = 108),与海马体相关的CaSCN显示,海马体和丘脑是对其他区域产生因果效应(即灰质减少)的突出节点,而前额叶皮质和小脑是受到因果效应影响的突出节点。有趣的是,还检测到对侧颞叶区域和扣带后皮质的灰质体积代偿性增加。相对于传统的阶段特异性比较和结构协方差网络方法,该方法揭示了mTLE中映射网络萎缩的更丰富信息。本研究为海马萎缩对mTLE中进行性脑结构改变的因果影响方面的网络传播机制提供了新证据。《人类大脑图谱》38:753 - 766,2017年。© 2016威利期刊公司。