Abstract
Objective: Vascular cognitive impairment (VCI) is a common complication in adult patients with moyamoya disease (MMD), and is reversible by surgical revascularization in its early stage of mild VCI. However, accurate diagnosis of mild VCI is difficult based on neuropsychological examination alone. This study proposed a method of dynamic resting-state functional connectivity (FC) network to recognize global cognitive impairment in MMD.Methods: For MMD, 36 patients with VCI and 43 patients with intact cognition (Non-VCI) were included, as well as 26 normal controls (NCs). Using resting-state fMRI, dynamic low-order FC networks were first constructed with multiple brain regions which were generated through a sliding window approach and correlated in temporal dimension. In order to obtain more information of network interactions along the time, high-order FC networks were established by calculating correlations among each pair of brain regions. Afterwards, a sparse representation-based classifier was constructed to recognize MMD (experiment 1) and its cognitive impairment (experiment 2) with features extracted from both low- and high-order FC networks. Finally, the ten-fold cross-validation strategy was proposed to train and validate the performance of the classifier.Results: The three groups did not differ significantly in demographic features (p > 0.05), while the VCI group exhibited the lowest MMSE scores (p = 0.001). The Non-VCI and NCs groups did not differ significantly in MMSE scores (p = 0.054). As for the classification between MMD and NCs, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the classifier reached 90.70, 88.57, 93.67, and 73.08%, respectively. While for the classification between VCI and Non-VCI, the AUC, accuracy, sensitivity, and specificity of the classifier reached 91.02, 84.81, 80.56, and 88.37%, respectively.Conclusion: This study not only develops a promising classifier to recognize VCI in adult MMD in its early stage, but also implies the significance of time-varying properties in dynamic FC networks.
Highlights
Moyamoya disease (MMD) is a cerebrovascular disease characterized by both progressive stenosis of the terminal portion of the bilateral internal carotid arteries, and extensive network of cerebral collaterals (Suzuki and Kodama, 1983)
After assessed through the neuropsychological testing of global cognitive state using the mini-mental state examination (MMSE), 36 patients were diagnosed with Vascular cognitive impairment (VCI) and the rest 43 patients were with intact cognition (Non-VCI) in accordance with 2011 AHA/ASA statement of VCI (Gorelick et al, 2011)
In the following experiment 2, the 36 patients with VCI were selected as positive samples, while the rest 43 patients with Non-VCI were used as negative samples
Summary
Moyamoya disease (MMD) is a cerebrovascular disease characterized by both progressive stenosis of the terminal portion of the bilateral internal carotid arteries, and extensive network of cerebral collaterals (Suzuki and Kodama, 1983). Initial presentations of MMD are categorized into symptoms due to either cerebral ischemia (i.e., ischemic stroke) or compensatory mechanisms responding to the ischemia (i.e., intracranial bleeding from fragile collaterals) (Scott and Smith, 2009). Vascular cognitive impairment (VCI) is a common complication in adult patients with MMD, the diagnostic criteria of which is based on a link between the cognitive disorder and evidences of subclinical cerebral vascular damage or clinical stroke (Gorelick et al, 2011). The occurrence of VCI in MMD has been proved to be caused by subclinical cerebral vascular defects or clinical stroke (Karzmark et al, 2012). The VCI is reversible in its early stage of mild impairment through surgical revascularization (Gorelick et al, 2011; Lei et al, 2017a). An alternative measurement with high sensitivity, reliability, and validity is needed
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