| 胡绮莉,王湘彬,李芸菲,宋英杰,孟凡华,张思斯,赵小虎.基于DTI数据分析轻度认知功能障碍患者脑结构网络[J].中国医学影像技术,2020,36(7):986~990 |
| 基于DTI数据分析轻度认知功能障碍患者脑结构网络 |
| Analysis of brain structural network of patients with mild cognitive impairment based on DTI |
| 投稿时间：2019-10-30 修订日期：2020-05-18 |
| DOI：10.13929/j.issn.1003-3289.2020.07.008 |
| 中文关键词: 认知障碍 磁共振成像 大脑结构网络 小世界特性 |
| 英文关键词:cognition disorders magnetic resonance imaging structural network small-worldness |
| 基金项目:上海市科委医学引导类（中、西医）科技支撑项目（18411970300）、上海市卫生和计划生育委员会临床研究项目（201840018）。 |
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| 中文摘要: |
| 目的 基于DTI数据构建大脑结构网络观察轻度认知障碍（MCI）患者脑结构网络是否具有小世界属性及其相关特征参数变化。方法 对26例MCI患者（MCI组）和27名正常老年人（NC组）采集大脑DTI数据，以PANDA软件对图像进行预处理，以自动解剖标定（AAL）模板将大脑皮质划分为90个区域，采用确定性纤维示踪算法示踪纤维，以每对脑区间纤维束数目（FN）为阈值T，构建白质纤维连接网络。设定T的取值范围为1~5，步长为1，分别计算不同T值时脑结构网络特征参数，包括平均路径长度（LP）、聚类系数（CP）、全局效率（Eglobal）及局部效率（Elocal），若满足γ=C/Crand>1且λ=L/Lrand≈1（rand代表相应随机网络）或δ=γ/λ>1，则脑结构网络具有小世界特性。比较不同T值时2组大脑结构网络特征参数的差异。结果 1≤T≤5时，MCI组和NC组均符合γ>1且λ≈1；MCI组LP均高于NC组（P均<0.05）；MCI组Cp与NC组差异均无统计学意义（P均>0.05）。1≤T≤4时，MCI组Eglobal均低于NC组（P均<0.05）；T=2时，MCI组Elocal值低于NC组（P<0.05）。结论 MCI患者大脑结构网络具有小世界属性，但其小世界特性受损。 |
| 英文摘要: |
| Objective To construct brain structural network based on DTI data,so as to investigate whether the brain structural network of with mild cognitive impairment (MCI) patients has small-world property,also to observe the changes of relevant characteristic parameters. Methods Brain DTI data of 26 MCI patients (MCI group) and 27 healthy elders (NC group) were collected. The images were preprocessed with PANDA software, and the cerebral cortex was divided into 90 regions using automated anatomical labeling (AAL) template. Diffusion tensor tractography was implemented using deterministic fiber tracing algorithm, and the white matter fiber connection network was constructed with the fiber number (FN) between 2 brain regions as the threshold T value. T value was set in the range of 1-5, step length was 1, then the characteristic parameters of the brain network at different T value were calculated, including average path length (Lp), aggregation coefficient (CP), global efficiency (Eglobal) and local efficiency (Elocal). The network was considered to be a small-world network if γ=C/Crand>1 and λ=L/Lrand≈1 (rand representing relative random networks) or δ=γ/λ>1 were satisfied. The differences of brain structural network characteristic parameters were compared between 2 groups. Results When 1 ≤ T ≤ 5, MCI group and NC group both met the criteria of γ>1 and λ≈1; LP of MCI group were all higher than those of NC group (all P<0.05), no statistical difference of CP was found between 2 groups (all P>0.05). When 1 ≤ T ≤ 4, Eglobal of MCI group were all lower than those of NC group (all P<0.05), when T=2, Elocal of MCI group was lower than that of NC group (P<0.05). Conclusion The brain structural network of MCI patients has small-world property, but its small-world characteristics are impaired. |
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