Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease

Xin Ouyang; Xiaoyu Sun; Ting Guo; Qiaoyue Sun; Kewei Chen; Li Yao; Xia Wu; Xiaojuan Guo

doi:10.1117/12.2042237

Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease

Xin Ouyang, Xiaoyu Sun, Ting Guo, Qiaoyue Sun, Kewei Chen, Li Yao, Xia Wu, Xiaojuan Guo^*

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Alzheimera's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.

Original language	English
Title of host publication	Medical Imaging 2014
Subtitle of host publication	Biomedical Applications in Molecular, Structural, and Functional Imaging
Publisher	SPIE
ISBN (Print)	9780819498311
DOIs	https://doi.org/10.1117/12.2042237
Publication status	Published - 2014
Externally published	Yes
Event	Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging - San Diego, CA, United States Duration: 16 Feb 2014 → 18 Feb 2014

Publication series

Name	Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume	9038
ISSN (Print)	1605-7422

Conference

Conference	Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging
Country/Territory	United States
City	San Diego, CA
Period	16/02/14 → 18/02/14

Keywords

Alzheimer's disease
Diffusion tensor imaging
Fractional anisotropy
Independent component analysis

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10.1117/12.2042237

Cite this

Ouyang, X., Sun, X., Guo, T., Sun, Q., Chen, K., Yao, L., Wu, X., & Guo, X. (2014). Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease. In Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging Article 90380B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9038). SPIE. https://doi.org/10.1117/12.2042237

@inproceedings{e1aca5d639a144a8bd3f9544afe680e6,

title = "Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease",

abstract = "Alzheimera's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.",

keywords = "Alzheimer's disease, Diffusion tensor imaging, Fractional anisotropy, Independent component analysis",

author = "Xin Ouyang and Xiaoyu Sun and Ting Guo and Qiaoyue Sun and Kewei Chen and Li Yao and Xia Wu and Xiaojuan Guo",

year = "2014",

doi = "10.1117/12.2042237",

language = "English",

isbn = "9780819498311",

series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",

publisher = "SPIE",

booktitle = "Medical Imaging 2014",

address = "United States",

note = "Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging ; Conference date: 16-02-2014 Through 18-02-2014",

}

Ouyang, X, Sun, X, Guo, T, Sun, Q, Chen, K, Yao, L, Wu, X & Guo, X 2014, Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease. in Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging., 90380B, Progress in Biomedical Optics and Imaging - Proceedings of SPIE, vol. 9038, SPIE, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging, San Diego, CA, United States, 16/02/14. https://doi.org/10.1117/12.2042237

Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease. / Ouyang, Xin; Sun, Xiaoyu; Guo, Ting et al.
Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging. SPIE, 2014. 90380B (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 9038).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease

AU - Ouyang, Xin

AU - Sun, Xiaoyu

AU - Guo, Ting

AU - Sun, Qiaoyue

AU - Chen, Kewei

AU - Yao, Li

AU - Wu, Xia

AU - Guo, Xiaojuan

PY - 2014

Y1 - 2014

N2 - Alzheimera's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.

AB - Alzheimera's disease (AD) is a progressive neurodegenerative disease with the clinical symptom of the continuous deterioration of cognitive and memory functions. Multiple diffusion tensor imaging (DTI) indices such as fractional anisotropy (FA) and mean diffusivity (MD) can successfully explain the white matter damages in AD patients. However, most studies focused on the univariate measures (voxel-based analysis) to examine the differences between AD patients and normal controls (NCs). In this investigation, we applied a multivariate independent component analysis (ICA) to investigate the white matter covariances based on FA measurement from DTI data in 35 AD patients and 45 NCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. We found that six independent components (ICs) showed significant FA reductions in white matter covariances in AD compared with NC, including the genu and splenium of corpus callosum (IC-1 and IC-2), middle temporal gyral of temporal lobe (IC-3), sub-gyral of frontal lobe (IC-4 and IC-5) and sub-gyral of parietal lobe (IC-6). Our findings revealed covariant white matter loss in AD patients and suggest that the unsupervised data-driven ICA method is effective to explore the changes of FA in AD. This study assists us in understanding the mechanism of white matter covariant reductions in the development of AD.

KW - Alzheimer's disease

KW - Diffusion tensor imaging

KW - Fractional anisotropy

KW - Independent component analysis

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U2 - 10.1117/12.2042237

DO - 10.1117/12.2042237

M3 - Conference contribution

AN - SCOPUS:84901760602

SN - 9780819498311

T3 - Progress in Biomedical Optics and Imaging - Proceedings of SPIE

BT - Medical Imaging 2014

PB - SPIE

T2 - Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging

Y2 - 16 February 2014 through 18 February 2014

ER -

Independent component analysis of DTI data reveals white matter covariances in Alzheimer's disease

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