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Disrupted Regional Cerebral Blood Flow, Functional Activity and Connectivity in Alzheimer’s Disease: A Combined ASL Perfusion and Resting State fMRI Study

静息状态功能磁共振成像 楔前 脑血流 后扣带 默认模式网络 功能磁共振成像 顶叶下小叶 神经科学 医学 心脏病学 内科学 心理学
作者
Wengang Zheng,Bin Cui,Ying Han,Haiqing Song,Kuncheng Li,Yong He,Zhi­qun Wang
出处
期刊:Frontiers in Neuroscience [Frontiers Media]
卷期号:13 被引量:43
标识
DOI:10.3389/fnins.2019.00738
摘要

Recent studies have demonstrated the close relationship between the regional cerebral blood flow (rCBF) and resting state functional connectivity changes in the normal healthy people. However, little is known about the different parameters changes of the most vulnerable regions in Alzheimer's disease (AD). In this study, we collected resting-state perfusion and functional magnetic resonance imaging (fMRI) data including 40 AD patients and 30 healthy controls. By using voxel wise arterial spin labeling (ASL) perfusion, we firstly identified several regions of the altered rCBF in the AD patients. And then, by using resting state fMRI analysis including amplitude low frequency fluctuation (ALFF) and seed based functional connectivity, we explored the changes of the functional activities and connectivities based on the identified rCBF regions. We extracted the cognitive related parameters and search for the sensitive biomarker to differentiate the AD and normal controls. As the results, compared with controls, the AD patients showed distinct disruption of rCBF, which were mainly located in the left posterior cingulate cortex (PCC), left and right dorsolateral prefrontal cortex (DLPFC), left inferior parietal lobule (IPL), right middle temporal gyrus (MTG), left middle occipital gyrus (MOG), and left precuneus (PCu). ALFF was performed based on the seven regions identified by the ASL method, AD patients showed significantly decreased ALFF in left PCC, left IPL, right MTG, left MOG, and left PCu and increased ALFF in the bilateral DLPFC. We constitute the network based on the seven regions and found the decreased connectivity among the identified regions in the AD patients, predicting to the disruption of the default mode network (DMN), executive control network (ECN) and visual network (VN). Furthermore, these abnormal parameters are closely correlated with cognitive performances in the AD patients. We combined the rCBF and ALFF value of PCC/PCu as biomarker to differciate the two groups and reached the sensitivity of 85.3% and specificity of 88.5%. Conclusively, our findings suggested that disrupted regional cerebral blood flow, functional activity and connectivity in specific cognitive related regions in Alzheimer’s disease, which can be used as the valuable imaging biomarker for the diagnosis of AD.

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