Learning Metabolic Brain Networks in MCI and AD by Robustness and Leave-One-Out Analysis: An FDG-PET Study. Issue 1 (February 2018)

• Record Type: Journal Article
• Authors: Yao, Zhijun; Hu, Bin; Chen, Xuejiao; Xie, Yuanwei; Gutknecht, Jürg; Majoe, Dennis
• Is Part Of: American journal of Alzheimer's disease & other dementias. Volume 33:Issue 1(2018)
• Page Start: 42
• Page End: 54
• Publication Date: 2018-02
• Subjects: AD -- MCI -- Metabolic brain network -- Network robustness -- Leave-one-out -- FDG-PET; Alzheimer's disease -- Periodicals; Dementia -- Periodicals; Alzheimer's disease -- Patients -- Care -- United States -- Periodicals; 616.83
• DOI: 10.1177/1533317517731535
• Languages: English
• ISSNs: 1533-3175

Abstract

This study attempted to better understand the properties associated with the metabolic brain network in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Graph theory was employed to investigate the topological organization of metabolic brain network among 86 patients with MCI, 89 patients with AD, and 97 normal controls (NCs) using 18F fluoro-deoxy-glucose positron emission tomography (FDG-PET) data. The whole brain was divided into 82 areas by Brodmann atlas to construct networks. We found that MCI and AD showed a loss of small-world properties and topological aberrations, and MCI showed an intermediate measurement between NC and AD. The networks of MCI and AD were vulnerable to attacks resulting from the altered topological pattern. Furthermore, individual contributions were correlated with Mini-Mental State Examination and Clinical Dementia Rating. The present study indicated that the topological patterns of the metabolic networks were aberrant in patients with MCI and AD, which may be particularly helpful in uncovering the pathophysiology underlying the cognitive dysfunction in MCI and AD.