轻度认知功能障碍患者大脑fMRI网络小世界特性

发布时间：2018-07-02 22:09

  本文选题：轻度认知功能障碍 + 小世界特性　； 参考：《中国医学影像技术》2014年05期

【摘要】：目的应用静息态fMRI观察轻度认知功能障碍(MCI)患者大脑功能网络是否具有小世界特性。方法采集13例MCI患者(MCI组)和17名正常老年人(NC组)的大脑静息态BOLD-fMRI数据。采用SPM 5软件对图像进行预处理,将大脑分割为90个区域,计算90个区域间的相关系数。以矩阵稀疏度(Sparsity)为阈值,将相关矩阵转换为网络。计算网络的聚类系数(C)和平均路径长度(L),若满足γ=C/Crand1且λ=L/Lrand≈1(rand代表相应随机网络),为则认为大脑功能网络具有小世界特性。采用双样本t检验比较MCI组与NC组大脑功能网络小世界参数的差异。结果在0.10~0.40阈值范围内,MCI组和NC组均符合γ1且λ≈1。MCI组γ和δ均大于NC组,且在0.10≤Sparsity≤0.18时差异有统计学意义(P0.05);MCI组λ在各阈值处均小于NC组,在Sparsity=0.18、0.28和0.32处差异有统计学意义(P0.05)。结论 MCI患者大脑fMRI网络具有小世界特性,且与正常老年人相比有所增强。
[Abstract]:Objective to observe the small world characteristics of cerebral functional network in patients with mild cognitive impairment (MCI) by resting fMRI. Methods brain resting BOLD-fMRI data of 13 MCI patients (MCI group) and 17 normal elderly (NC group) were collected. SPM5 software was used to preprocess the image. The brain was divided into 90 regions and the correlation coefficients between 90 regions were calculated. The correlation matrix is transformed into a network using matrix sparsity as the threshold. The clustering coefficient (C) and the average path length (L) of the network are calculated. If 纬 C / Cr and 位 L / L rand 鈮，

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