基于分形特征的阿尔茨海默病脑网络结构分析

Structural analysis of Alzheimer's disease brain networks based on fractal features

阿尔茨海默病患者的功能脑网络在小世界及聚类系数等拓扑属性上与认知正常者存在差异。为进一步揭示阿尔茨海默病患者脑网络的结构特征及其与认知正常者脑网络结构的差异,引入分形特征进行对比分析。实验结果表明,阿尔茨海默病患者与认知正常者的脑网络在相同盒覆盖半径下的最小盒子数与连接比例存在显著差异。脑网络阈值为0.4时,认知正常者脑网络的连接比例值分布在区间[0,1],而阿尔茨海默病患者脑网络的连接比例值分布在区间(0.5,1)。同时,不同阈值下,阿尔茨海默病患者脑网络的平均连接比例均高于认知正常者。上述网络结构差异可为阿尔茨海默病的诊断提供一种新参考。

It had been demonstrated that the functional brain networks of Alzheimer’s patients exhibit topological properties distinct from those of cognitively normal individuals,including small-world and clustering coefficients.To further elucidate the structural characteristics of the brain networks of Alzheimer’s patients and their differences in brain network structure with cognitively normal individuals,fractal features were introduced for comparative analysis.Experimental results demonstrated a significant difference in the minimum number of boxes and connection ratio between brain networks of Alzheimer’s patients and cognitively normal individuals at the same box-covering radius.At the brain network threshold of 0.4,the connection ratio values of cognitively normal individuals’brain networks were distributed in the[0,1]interval,while the connection ratio values of Alzheimer’s patients’brain networks were distributed in the(0.5,1)interval.Furthermore,the average connection ratio of Alzheimer’s patients’brain networks was found to be higher than that of cognitively normal individuals at different thresholds.These differences in network structure provide a new reference for the diagnosis of Alzheimer’s disease.