Mapping joint grey and white matter reductions in Alzheimer's disease using joint independent component analysis

NEUROSCIENCE LETTERS

卷:531

Article

Guo, Xiaojuan^1,2  Han, Yuan²  Chen, Kewei^3,4  Wang, Yan¹  Yao, Li^1,2 

[1] Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China

[2] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China

[3] Banner Alzheimers Inst, Phoenix, AZ USA

[4] Banner Good Samaritan PET Ctr, Phoenix, AZ USA

关键词: Alzheimer's disease;    Joint source;    Joint independent component analysis;    Structural MRI;    Voxel-based morphometry;   

DOI  :  10.1016/j.neulet.2012.10.038

来源: Elsevier

【 摘 要 】

Alzheimer's disease (AD) is a neurodegenerative disease concomitant with grey and white matter damages. However, the interrelationship of volumetric changes between grey and white matter remains poorly understood in AD. Using joint independent component analysis, this study identified joint grey and white matter volume reductions based on structural magnetic resonance imaging data to construct the covariant networks in twelve AD patients and fourteen normal controls (NC). We found that three networks showed significant volume reductions in joint grey-white matter sources in AD patients, including (1) frontal/parietal/temporal-superior longitudinal fasciculus/corpus callosum, (2) temporal/parietal/occipital-frontal/occipital, and (3) temporal-precentral/postcentral. The corresponding expression scores distinguished AD patients from NC with 85.7%, 100% and 85.7% sensitivity for joint sources 1, 2 and 3, respectively; 75.0%, 66.7% and 75.0% specificity for joint sources 1, 2 and 3, respectively. Furthermore, the combined source of three significant joint sources best predicted the AD/NC group membership with 92.9% sensitivity and 83.3% specificity. Our findings revealed joint grey and white matter loss in AD patients, and these results can help elucidate the mechanism of grey and white matter reductions in the development of AD. (C) 2012 Elsevier Ireland Ltd. All rights reserved.

【 授权许可】

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