Subramanian Saraswathi, Rajamanickam Karunanithi, Prakash Joy Sebastian, Ramachandran Murugesan
Chettinad Academy of Research and Education, Faculty of Allied Health Sciences, Kelambakkam, Chennai, Tamil Nadu, India.
J Med Imaging (Bellingham). 2020 Jan;7(1):016002. doi: 10.1117/1.JMI.7.1.016002. Epub 2020 Feb 26.
Alzheimer's disease (AD) is characterized by the progressive accumulation of neurofibrillary tangles associated with amyloid plaques. We used 80 resting-state functional magnetic resonance imaging and 80 images acquired using MP-RAGE (magnetization-prepared rapid acquisition gradient echo) from Alzheimer's Disease Neuroimaging Initiative data to detect atrophy changes and functional connectivity patterns of the default mode networks (DMNs). The study subjects were classified into four groups (each with ) based on their Mini-Mental State Examination (MMSE) score as follows: cognitively normal (CN), early mild cognitive impairment, late mild cognitive impairment, and AD. The resting-state functional connectivity of the DMN was examined between the groups using the CONN functional connectivity toolbox. Loss of gray matter in AD was observed. Atrophy measured by the volume of selected subcortical regions, using the Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library's Integrated Registration and Segmentation Tool (FIRST), revealed significant volume loss in AD when compared to CN ( ). DMNs were selected to assess functional connectivity. The negative connectivity of DMN increased in AD group compared to controls. Graph theory parameters, such as global and local efficiency, betweenness centrality, average path length, and cluster coefficient, were computed. Relatively higher correlation between MMSE and functional metrics ( , ) was observed as compared to atrophy measures ( , ). In addition, the receiver operating characteristic analysis showed large area under the curve ( ) for functional parameters ( ), compared to morphometric changes ( ). In summary, it is observed that the functional connectivity measures may serve a better predictor in comparison to structural atrophy changes. We postulate that functional connectivity measures have the potential to evolve as a marker for the early detection of AD.
阿尔茨海默病（AD）的特征是与淀粉样斑块相关的神经原纤维缠结逐渐积累。我们使用了来自阿尔茨海默病神经影像倡议数据的80幅静息态功能磁共振成像以及80幅使用MP-RAGE（磁化准备快速采集梯度回波）获得的图像，以检测默认模式网络（DMN）的萎缩变化和功能连接模式。研究对象根据其简易精神状态检查表（MMSE）评分分为四组（每组各 ），如下：认知正常（CN）、早期轻度认知障碍、晚期轻度认知障碍和AD。使用CONN功能连接工具箱在各组之间检查DMN的静息态功能连接。观察到AD患者灰质丢失。使用脑功能磁共振成像（FMRIB）软件库的综合配准和分割工具（FIRST），通过选定皮质下区域的体积测量萎缩情况，结果显示与CN相比，AD患者存在显著的体积损失（ ）。选择DMN来评估功能连接。与对照组相比，AD组中DMN的负连接性增加。计算了图论参数，如全局和局部效率、中介中心性、平均路径长度和聚类系数。与萎缩测量值（ ， ）相比，观察到MMSE与功能指标（ ， ）之间的相关性相对较高。此外，与形态学变化（ ）相比，受试者工作特征分析显示功能参数（ ）的曲线下面积较大（ ）。总之，观察到与结构萎缩变化相比，功能连接测量可能是更好的预测指标。我们推测功能连接测量有潜力发展成为AD早期检测的标志物。
