Department of Radiology, Eye & ENT Hospital of Shanghai Medical School, Fudan University, Shanghai, China.
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China.
BMC Med Imaging. 2022 Mar 9;22(1):40. doi: 10.1186/s12880-022-00769-7.
White matter hyperintensity (WMH) is one of the typical neuroimaging manifestations of cerebral small vessel disease (CSVD), and the WMH correlates closely to cognitive impairment (CI). CSVD patients with WMH own altered topological properties of brain functional network, which is a possible mechanism that leads to CI. This study aims to identify differences in the characteristics of some brain functional network among patients with different grades of WMH and estimates the correlations between these different brain functional network characteristics and cognitive assessment scores.
110 CSVD patients underwent 3.0 T Magnetic resonance imaging scans and neuropsychological cognitive assessments. WMH of each participant was graded on the basis of Fazekas grade scale and was divided into two groups: (A) WMH score of 1-2 points (n = 64), (B) WMH score of 3-6 points (n = 46). Topological indexes of brain functional network were analyzed using graph-theoretical method. T-test and Mann-Whitney U test was used to compare the differences in topological properties of brain functional network between groups. Partial correlation analysis was applied to explore the relationship between different topological properties of brain functional networks and overall cognitive function.
Patients with high WMH scores exhibited decreased clustering coefficient values, global and local network efficiency along with increased shortest path length on whole brain level as well as decreased nodal efficiency in some brain regions on nodal level (p < 0.05). Nodal efficiency in the left lingual gyrus was significantly positively correlated with patients' total Montreal Cognitive Assessment (MoCA) scores (p < 0.05). No significant difference was found between two groups on the aspect of total MoCA and Mini-mental State Examination (MMSE) scores (p > 0.05).
Therefore, we come to conclusions that patients with high WMH scores showed less optimized small-world networks compared to patients with low WMH scores. Global and local network efficiency on the whole-brain level, as well as nodal efficiency in certain brain regions on the nodal level, can be viewed as markers to reflect the course of WMH.
脑白质高信号（WMH）是脑小血管病（CSVD）的典型神经影像学表现之一，WMH 与认知障碍（CI）密切相关。CSVD 合并 WMH 患者的脑功能网络拓扑性质发生改变，这可能是导致 CI 的机制之一。本研究旨在识别不同 WMH 程度 CSVD 患者脑功能网络特征的差异，并评估这些不同脑功能网络特征与认知评估评分之间的相关性。
110 例 CSVD 患者行 3.0T 磁共振成像扫描及神经心理学认知评估。基于 Fazekas 分级量表对每位患者的 WMH 进行分级，分为 2 组：（A）WMH 评分 1-2 分（n=64），（B）WMH 评分 3-6 分（n=46）。采用图论方法分析脑功能网络拓扑指标。采用 t 检验和 Mann-Whitney U 检验比较两组间脑功能网络拓扑性质的差异。采用偏相关分析探讨不同脑功能网络拓扑性质与整体认知功能的关系。
高 WMH 评分患者全脑水平的聚类系数、全局和局部网络效率以及最短路径长度降低，节点效率升高，节点水平的部分脑区节点效率降低（p<0.05）。左侧舌回节点效率与患者蒙特利尔认知评估（MoCA）总分呈显著正相关（p<0.05）。两组患者 MoCA 总分和简易精神状态检查（MMSE）评分差异无统计学意义（p>0.05）。
高 WMH 评分患者的脑功能网络呈现出小世界网络优化程度降低的特征，全脑水平的全局和局部网络效率以及节点水平的某些脑区节点效率可作为反映 WMH 病程的标志物。
