查看更多>>摘要：目的 基于扩散张量成像（DTI）图论分析法探讨痉挛型脑瘫（SCP）患儿脑网络属性及其与认知功能的关系。 方法 该研究为横断面研究。回顾性分析2020年8月至2022年4月在遵义医科大学附属医院接受颅脑MRI检查的21例SCP患儿（SCP组）及32名健康儿童（对照组）的临床及影像资料。对所有受检者进行3D-T1WI、DTI及韦氏智力量表评估。韦氏智力量表包括言语理解指数（VCI）、加工速度指数（PSI）、工作记忆指数（WMI）、知觉推理指数（PRI）等，最终根据各分量表指数得到全量表智商（FSIQ）评分。采用独立样本t检验分析2组脑网络小世界属性［小世界指数（σ）、标准化最短路径长度（λ）、标准化聚类系数（γ）］、全局属性［全局效率（Eglob）、局部效率［（Eloc）、特征路径长度（Lp）、聚类系数（Cp）］及节点属性指标［节点中心度（DC）、节点效率（Ne）、介数中心性、节点最短路径长度（NLp）、节点聚类系数、节点局部效率］的差异；采用Spearman将2组差异有统计学意义的脑网络指标与韦氏智力量表各分量表指数及FSIQ评分进行相关性分析。 结果 SCP组韦氏智力量表中FSIQ评分及VCI、WMI、PSI、PRI均较对照组降低，差异均有统计学意义（P均<0.05）。2组脑网络均具有小世界属性，与对照组比较，SCP组患儿Eglob降低，Lp、λ增加（P均<0.05）；对照组比较，SCP组患儿多个脑区DC、Ne减低，NLp增高（P均<0.05，FDR校正）。相关性分析显示，SCP组右侧额下回后部DC与FSIQ评分、VCI、WMI、PRI呈正相关（r分别为0.53、0.47、0.47、0.60，P分别为0.019、0.045、0.044、0.020）；右侧额下回后部NLp与PRI呈负相关（r=-0.56，P=0.030）；左侧中央旁小叶、右侧额下回后部、右侧中央前回、右侧中央后回Ne与PRI呈正相关（r分别为0.62、0.56、0.53、0.54，P分别为0.015、0.031、0.044、0.039）；右侧中央前回Ne与WMI呈正相关（r=0.48、P=0.039）。 结论 SCP患儿全局及多个区域脑网络拓扑属性存在改变，右侧额下回后部、右侧中央前回、右侧中央后回和左侧中央旁小叶节点属性改变与患儿认知功能损伤相关。 Objective To explore brain network properties and their relationship with cognitive function in children with spastic cerebral palsy (SCP) using diffusion tensor imaging (DTI) based graph theory analysis. Methods The study was a cross-sectional study. Clinical and imaging data of 21 children with SCP (SCP group) and 32 healthy children (control group) who underwent cranial MRI at the Affiliated Hospital of Zunyi Medical University from August 2020 to April 2022 were analyzed retrospectively. 3D-T1WI, DTI and Wechsler Intelligence Scale were assessed for all subjects. The Wechsler Intelligence Scale included the verbal comprehension index (VCI), the processing speed index (PSI), the work memory index (WMI), and the perceptual reasoning index (PRI), etc., and ultimately the full scale intelligence quotient (FSIQ) scores were obtained based on the indices of each subscale. Independent samples t-test was used to analyze the differences in the small world attributes [small-world index (σ), normalized shortest path length (λ), normalized clustering coefficients (γ)], global attributes [global efficiency (Eglob), local efficiency (Eloc), characteristic path length (Lp), clustering efficiency (Cp)] and node attributes [degree centrality(DC), nodal efficiency (Ne), betweeness centrality (Bc), nodal shortest path length (NLp), nodal clustering efficiency, nodal local efficiency] between two groups of children′s brain networks. Brain network indicators with statistically significant differences between the 2 groups were correlated with Wechsler Intelligence Scale scores using Spearman. Results The FSIQ scores on the Wechsler Intelligence Scale and the VCI, WMI, PSI, and PRI were lower in the SCP group than in the control group, and the differences were all statistically significant (all P<0.05). Both groups of children′s brain networks had small world properties. Compared with the control group, Eglob decreased, Lp and λ increased in the SCP group (allP<0.05). Compared with the control group, DC and Ne in multiple brain regions decreased, NLp increased in the SCP group (allP<0.05, FDR corrected). Correlation analysis showed that DC in the right parsopercularis was positively correlated with FSIQ, VCI, WMI and PRI(r=0.53, 0.47, 0.47, 0.60,P=0.019, 0.045, 0.044, 0.020, respectively) NLp in the right parsopercularis was negatively correlated with PRI(r=-0.56, P=0.030) Ne in left paracentral, the right parsopercularis, right precentral, right postcentra were positively correlated with PRI(r=0.62, 0.56, 0.53, 0.54, P=0.015, 0.031, 0.044, 0.039, respectively) Ne in the right precentral was positively correlated with WMI (r=0.48, P=0.039) in the SCP group. Conclusions There are changes in the topological attributes of global and multiple regional brain networks in SCP. The changes in the attributes of nodes in the right parsopercularis, right precentral, right postcentral, and left paracentral could reflect cognitive dysfunction in children with SCP.
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