摘要
背景:阿尔茨海默氏病(AD)是一种进行性神经退行性疾病,起病隐匿,难以逆转和治愈。因此,从神经影像生物标记物发现更精确的生物学信息对于准确和自动检测AD至关重要。 方法:我们创新地使用可见性图(VG)来构建时间相关的大脑网络以及功能连接网络,以基于功能磁共振成像研究AD大脑的基本动力学。阿尔茨海默氏病神经影像学计划(ADNI)数据库中有32位AD患者和29位正常对照(NC)。首先,VG方法将单个大脑区域的时间序列映射到网络中。通过提取网络的拓扑特性,将最重要的特征作为判别特征选择到支持向量机中进行分类。此外,为了检测整个AD大脑中这些大脑区域的异常,基于区域度序列的相关性,计算了不同大脑区域之间的功能连接。 结果:根据局部复杂网络的拓扑异常探索,我们发现了几个异常的大脑区域,包括左岛,右扣带回和其他皮质区域。从局部复杂网络中提取的大脑区域特征的准确性为88.52%。关联分析表明,额叶回的左下眼部分,右枕中回,右顶顶回和右前突在AD中起着巨大的作用。 结论:这些结果将有助于揭示该疾病的潜在病理机制。
关键词: 阿尔茨海默氏病,功能磁共振成像,能见度图,功能网络,分类研究,局部复杂网络。
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