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

Weimin Zheng, Bin Cui, Ying Han, Haiqing Song, Kuncheng Li, Yong He, Zhiqun Wang, Weimin Zheng, Bin Cui, Ying Han, Haiqing Song, Kuncheng Li, Yong He, Zhiqun Wang

Abstract

Recent studies have demonstrated a close relationship between regional cerebral blood flow (rCBF) and resting state functional connectivity changes in normal healthy people. However, little is known about the parameter changes in the most vulnerable regions in Alzheimer's disease (AD). Forty AD patients and 30 healthy controls participated in this study. The data of resting-state perfusion and functional magnetic resonance imaging (fMRI) was collected. By using voxel-wise arterial spin labeling (ASL) perfusion, we identified several regions of altered rCBF in AD patients. Then, by using resting state fMRI analysis, including amplitude low frequency fluctuation (ALFF) and seed-based functional connectivity, we investigated the changes of functional activity and connectivity among the identified rCBF regions. We extracted cognition-related parameters and searched for a sensitive biomarker to differentiate the AD patients from the normal controls (NC). Compared with controls, AD patients showed special disruptions in rCBF, which were mainly located in the left posterior cingulate cortex (PCC), the left and right dorsolateral prefrontal cortex (DLPFC), the left inferior parietal lobule (IPL), the right middle temporal gyrus (MTG), the left middle occipital gyrus (MOG), and the left precuneus (PCu). ALFF was performed based on the seven regions identified by the ASL method, and AD patients presented significantly decreased ALFF in the left PCC, left IPL, right MTG, left MOG, and left PCu and increased ALFF in the bilateral DLPFC. We constituted the network based on the seven regions and found that there was decreased connectivity among the identified regions in the AD patients, which predicted a disruption in the default mode network (DMN), executive control network (ECN) and visual network (VN). Furthermore, these abnormal parameters are closely associated with cognitive performances in AD patients. We combined the rCBF and ALFF value of PCC/PCu as a biomarker to differentiate the two groups and reached a sensitivity of 85.3% and a specificity of 88.5%. Our findings suggested that there was disrupted rCBF, functional activity and connectivity in specific cognition-related regions in Alzheimer's disease, which can be used as a valuable imaging biomarker for the diagnosis of AD.

Keywords: Alzheimer’s disease; amplitude low frequency fluctuation; arterial spin labeling; functional connectivity; regional cerebral blood flow; resting state fMRI.

Figures

FIGURE 1
FIGURE 1
Whole brain rCBF maps in the AD and NC groups (with FEW-corrected P < 0.05).
FIGURE 2
FIGURE 2
Voxel-wise percentage rCBF changes in patients with AD compared with healthy controls. Decreased rCBF in AD patients compared to healthy controls were mainly located in LPCC, LDLPFC, PDLPFC, LIPL, RMTG, LMOG, and LPCu (with FEW-corrected P < 0.05). L, left; R, right; PPC, posterior cingulate cortex; DLPFC, dorsolateral prefrontal cortex; IPL, inferior parietal lobule; MTG, middle temporal gyrus; MOG, middle occipital gyrus; PCu, precuneus; FEW, Familywise error.
FIGURE 3
FIGURE 3
Voxel-wise ALFF changes in patients with AD compared with healthy controls in specific regions which were significantly decreased in rCBF. ∗∗Represents significantly changed ALFF in the AD patients compared with healthy controls (P < 0.01). *Represents slightly changed ALFF (P < 0.05).
FIGURE 4
FIGURE 4
Functional connectivities alterations in the AD patients relative to controls using seed-based interregional correlation analysis.
FIGURE 5
FIGURE 5
(A) Scatterplot of uncorrected rCBF in the IPL plotted against MMSE score, and in the PCC, MTG, MOG, PCu against ADL score. MMSE, mini-mental state examination; ADL, activity of daily living scale. (B) Scatterplot of functional connectivities of the DMN, ECN and VN plotted against MMSE score (P < 0.01). DMN, default mode network; ECN, executive control network; VN, visual network.
FIGURE 6
FIGURE 6
(A) Receiver operating characteristic (ROC) curve for uncorrected rCBF in PCC/PCu of patients with AD and healthy controls. An optimal rCBF cutoff value was determined at a sensitivity of 87.2% and specificity of 86.7%. The area under the curve (AUC) for the ROC was 0.908 (95% confidence intervals from 0.836 to 0.979). (B) ROC curve for ALFF in PCC/PCu of patients with AD and healthy controls. An optimal ALFF cutoff value was determined at a sensitivity of 65.7% and specificity of 73.1%. The AUC for the ROC was 0.734 (95% confidence intervals from 0.608 to 0.861). (C) ROC curve for uncorrected rCBF combined with ALFF in PCC/PCu of patients with AD and healthy controls. When using the two values simultaneously, it can reach a sensitivity of 85.3% and specificity of 88.5%. The AUC for the ROC was 0.921 (95% confidence intervals from 0.855 to 0.986).

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