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ASAF: altered spontaneous activity fingerprinting in Alzheimer’s disease based on multisite fMRI 被引量:4
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作者 Jiachen Li Dan Jin +20 位作者 Ang Li Bing Liu Chengyuan Song Pan Wang Dawei Wang Kaibin Xu Hongwei Yang Hongxiang Yao Bo Zhou alexandre bejanin Gael Chetelat Tong Han Jie Lu Qing Wang Chunshui Yu Xinqing Zhang Yuying Zhou Xi Zhang Tianzi Jiang Yong Liu Ying Han 《Science Bulletin》 SCIE EI CAS CSCD 2019年第14期998-1010,共13页
Several monocentric studies have noted alterations in spontaneous brain activity in Alzheimer's disease (AD), although there is no consensus on the altered amplitude of low-frequency fluctuations in AD patients. T... Several monocentric studies have noted alterations in spontaneous brain activity in Alzheimer's disease (AD), although there is no consensus on the altered amplitude of low-frequency fluctuations in AD patients. The main aim of the present study was to identify a reliable and reproducible abnormal brain activity pattern in AD. The amplitude of local brain activity (AM), which can provide fast mapping of spontaneous brain activity across the whole brain, was evaluated based on multisite rs-fMRI data for 688 subjects (215 normal controls (NCs), 221 amnestic mild cognitive impairment (aMCI) 252 AD). Two-sample t-tests were used to detect group differences between AD patients and NCs from the same site. Differences in the AM maps were statistically analyzed via the Stouffer's meta-analysis. Consistent regions of lower spontaneous brain activity in the default mode network and increased activity in the bilateral hippocampus/parahippocampus, thalamus, caudate nucleus, orbital part of the middle frontal gyrus and left fusiform were observed in the AD patients compared with those in NCs. Significant correlations (P?<?0.05, Bonferroni corrected) between the normalized amplitude index and Mini-Mental State Examination scores were found in the identified brain regions, which indicates that the altered brain activity was associated with cognitive decline in the patients. Multivariate analysis and leave-one-site-out cross-validation led to a 78.49% prediction accuracy for single-patient classification. The altered activity patterns of the identified brain regions were largely correlated with the FDG-PET results from another independent study. These results emphasized the impaired brain activity to provide a robust and reproducible imaging signature of AD. 展开更多
关键词 Brain SPONTANEOUS activity Multisite Biomarkers Leave-one-site-out cross-validation Alzheimer's disease
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