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Characteristic patterns of inter- and intra-hemispheric metabolic connectivity in patients with stable and progressive mild cognitive impairment and Alzheimer’s disease
Journal article   Open access   Peer reviewed

Characteristic patterns of inter- and intra-hemispheric metabolic connectivity in patients with stable and progressive mild cognitive impairment and Alzheimer’s disease

Sheng-Yao Huang, Jung-Lung Hsu, Kun-Ju Lin, Ho-Ling Liu, Shiaw-Pying Wey, Ing-Tsung Hsiao and Alzheimer’s Disease Neuroimaging Initiative
Scientific reports, Vol.8(1), 13807
12/01/2018
DOI: 10.1038/s41598-018-31794-8
PMCID: PMC6138637
PMID: 30218083
url
https://doi.org/10.1038/s41598-018-31794-8View
Published (Version of record) Open Access

Abstract

The change in hypometabolism affects the regional links in the brain network. Here, to understand the underlying brain metabolic network deficits during the early stage and disease evolution of AD (Alzheimer disease), we applied correlation analysis to identify the metabolic connectivity patterns using 18 F-FDG PET data for NC (normal control), sMCI (stable MCI), pMCI (progressive MCI) and AD, and explore the inter- and intra-hemispheric connectivity between anatomically-defined brain regions. Regions extracted from 90 anatomical structures were used to construct the matrix for measuring the inter- and intra-hemispheric connectivity. The brain connectivity patterns from the metabolic network show a decreasing trend of inter- and intra-hemispheric connections for NC, sMCI, pMCI and AD. Connection of temporal to the frontal or occipital regions is a characteristic pattern for conversion of NC to MCI, and the density of links in the parietal-occipital network is a differential pattern between sMCI and pMCI. The reduction pattern of inter and intra-hemispheric brain connectivity in the metabolic network depends on the disease stages, and is with a decreasing trend with respect to disease severity. Both frontal-occipital and parietal-occipital connectivity patterns in the metabolic network using 18 F-FDG PET are the key feature for differentiating disease groups in AD.

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