- Author:
Yida QU
1
;
Pan WANG
2
;
Hongxiang YAO
2
;
Dawei WANG
3
;
Chengyuan SONG
4
;
Hongwei YANG
5
;
Zengqiang ZHANG
6
;
Pindong CHEN
1
;
Xiaopeng KANG
1
;
Kai DU
1
;
Lingzhong FAN
1
;
Bo ZHOU
7
;
Tong HAN
8
;
Chunshui YU
9
;
Xi ZHANG
7
;
Nianming ZUO
1
;
Tianzi JIANG
1
;
Yuying ZHOU
2
;
Bing LIU
1
;
Ying HAN
10
;
Jie LU
11
;
Yong LIU
12
Author Information
- Collective Name:Multi-Center Alzheimer’s Disease Imaging (MCADI) Consortium
- Publication Type:Journal Article
- Keywords: Alzheimer’s disease; Cross-validation; Diffusion tensor imaging; White matter tracts
- MeSH: Humans; White Matter/diagnostic imaging*; Diffusion Tensor Imaging/methods*; Alzheimer Disease/complications*; Reproducibility of Results; Cognition; Cognitive Dysfunction/complications*; Brain/diagnostic imaging*
- From: Neuroscience Bulletin 2023;39(10):1533-1543
- CountryChina
- Language:English
- Abstract: Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.