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Published on: October 13, 2016
Multimodal magnetic resonance imaging analysis of early mild cognitive impairment
Shuai Xu1, Yingao Fan1, Chenglu Mao1
1Department of Neurology, Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, China.
Abstract:
BackgroundEarly mild cognitive impairment (EMCI) represents a prodromal stage of dementia, and early detection is crucial for delaying dementia progression. However, accurately identifying its neuroimaging features remains challenging.ObjectiveTo comprehensively evaluate structural and functional neuroimaging changes in EMCI using multimodal magnetic resonance imaging (MRI) techniques.MethodsOne hundred and eleven participants were included from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 36 with cognitively normal (CN), 30 with EMCI, 32 with late mild cognitive impairment (LMCI), and 13 with Alzheimer's disease (AD). FreeSurfer software was employed to segment hippocampal and amygdala subregions. The amplitude of low-frequency fluctuation (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and functional connectivity were processed using Data Processing & Analysis for Brain Imaging toolbox. Graph Theoretical Network Analysis toolbox was utilized to evaluate global functional network.ResultsThe volume of most hippocampal and amygdala subregions was decreased in AD group than those of EMCI group in structural MRI. Significant differences were found between EMCI and AD group in fALFF (right insula) and ReHo (bilateral caudate regions). EMCI group exhibited stronger functional connectivity between left hippocampus and right inferior temporal gyrus (compared to CN), left inferior temporal gyrus (compared to LMCI), and cerebellum crus 8 (compared to AD). EMCI group exhibited stronger connectivity between right hippocampus and left anterior cingulate gyrus compared to AD. Network metrics showed no significant differences among these groups, but all exhibited small-world properties.ConclusionsMultimodal MRI analysis revealed the neuroimaging characteristics of EMCI and promoted the understanding of the mechanisms underlying neuroimaging changes in EMCI.
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