title: Simultaneous changes in gray matter volume and white matter fractional anisotropy in Alzheimer's disease revealed by multimodal CCA and joint ICA.
abstract: The prominent morphometric alterations of Alzheimer's disease (AD) occur both in gray matter and in white matter. Multimodal fusion can examine joint information by combining multiple neuroimaging datasets to identify the covariant morphometric alterations in AD in greater detail. In the current study, we conducted a multimodal canonical correlation analysis and joint independent component analysis to identify the covariance patterns of the gray and white matter by fusing structural magnetic resonance imaging and diffusion tensor imaging data of 39 AD patients (23 males and 16 females, mean age: 74.91±8.13years) and 41 normal controls (NCs) (20 males and 21 females, mean age: 73.97±6.34years) derived from the Alzheimer's Disease Neuroimaging Initiative database. The results revealed 25 joint independent components (ICs), of which three joint ICs exhibited strong links between the gray matter volume and the white matter fractional anisotropy (FA) and significant differences between the AD and NC group. The joint IC maps revealed that the simultaneous changes in the gray matter and FA values primarily involved the following areas: (1) the temporal lobe/hippocampus-cingulum, (2) the frontal/cingulate gyrus-corpus callosum, and (3) the temporal/occipital/parietal lobe-corpus callosum/corona radiata. Our findings suggest that gray matter atrophy is associated with reduced white matter fiber integrity in AD and possibly expand the understanding of the neuropathological mechanisms in AD.
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: X
authors.initials: X
authors.lastname: Ouyang
authors.affiliation: Banner Alzheimer's Institute and Banner Good Samaritan PET Center, Phoenix, AZ, USA.
authors.forename: K
authors.initials: K
authors.lastname: Chen
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
authors.forename: L
authors.initials: L
authors.lastname: Yao
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: B
authors.initials: B
authors.lastname: Hu
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
authors.forename: X
authors.initials: X
authors.lastname: Wu
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China.
authors.forename: Q
authors.initials: Q
authors.lastname: Ye
authors.affiliation: College of Information Science and Technology, Beijing Normal University, Beijing, China; State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China. Electronic address: gxj@bnu.edu.cn.
authors.forename: X
authors.initials: X
authors.lastname: Guo
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000473:pathology*; D016880:Anisotropy; D056324:Diffusion Tensor Imaging; D005260:Female; D066128:Gray Matter / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D009483:Neuropsychological Tests; D011569:Psychiatric Status Rating Scales; D066127:White Matter / Q000473:pathology*
keywords: Alzheimer’s disease; CCA and ICA; fractional anisotropy; gray matter; structural MRI and DTI