ASAF: altered spontaneous activity fingerprinting in Alzheimer's disease based on multisite fMRI.

Alzheimer’s disease Biomarkers Brain spontaneous activity Leave-one-site-out cross-validation Multisite

Journal

Science bulletin
ISSN: 2095-9281
Titre abrégé: Sci Bull (Beijing)
Pays: Netherlands
ID NLM: 101655530

Informations de publication

Date de publication:
30 Jul 2019
Historique:
received: 16 11 2018
revised: 22 03 2019
accepted: 25 03 2019
entrez: 20 1 2023
pubmed: 30 7 2019
medline: 30 7 2019
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 36659811
pii: S2095-9273(19)30268-3
doi: 10.1016/j.scib.2019.04.034
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

998-1010

Informations de copyright

Copyright © 2019 Science China Press. Published by Elsevier B.V. All rights reserved.

Auteurs

Jiachen Li (J)

Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.

Dan Jin (D)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.

Ang Li (A)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China.

Bing Liu (B)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Chengyuan Song (C)

Department of Neurology, Qilu Hospital of Shandong University, Ji'nan 250012, China.

Pan Wang (P)

Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China; Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing 100853, China.

Dawei Wang (D)

Department of Radiology, Qilu Hospital, Ji'nan 250012, China.

Kaibin Xu (K)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Hongwei Yang (H)

Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.

Hongxiang Yao (H)

Department of Radiology, Chinese PLA General Hospital, Beijing 100853, China.

Bo Zhou (B)

Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing 100853, China.

Alexandre Bejanin (A)

Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen 14000, France.

Gael Chetelat (G)

Université Normandie, Inserm, Université de Caen-Normandie, Inserm UMR-S U1237, GIP Cyceron, Caen 14000, France.

Tong Han (T)

Department of Radiology, Tianjin Huanhu Hospital, Tianjin 300350, China.

Jie Lu (J)

Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.

Qing Wang (Q)

Department of Radiology, Qilu Hospital, Ji'nan 250012, China.

Chunshui Yu (C)

Department of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.

Xinqing Zhang (X)

Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.

Yuying Zhou (Y)

Department of Neurology, Tianjin Huanhu Hospital, Tianjin 300350, China.

Xi Zhang (X)

Institute of Geriatrics and Gerontology, Chinese PLA General Hospital, Beijing 100853, China.

Tianzi Jiang (T)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China.

Yong Liu (Y)

Brainnetome Center & National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China; Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China. Electronic address: yliu@nlpr.ia.ac.cn.

Ying Han (Y)

Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China; Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing 100053, China; Beijing Institute of Geriatrics, Beijing 100053, China; National Clinical Research Center for Geriatric Disorders, Beijing 100053, China. Electronic address: hanying@xwh.ccmu.edu.cn.

Classifications MeSH