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Proceedings Paper

A multivariate pattern analysis study of the HIV-related white matter anatomical structural connections alterations
Author(s): Zhenchao Tang; Zhenyu Liu; Ruili Li; Xinwei Cui; Hongjun Li; Enqing Dong; Jie Tian
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Paper Abstract

It’s widely known that HIV infection would cause white matter integrity impairments. Nevertheless, it is still unclear that how the white matter anatomical structural connections are affected by HIV infection. In the current study, we employed a multivariate pattern analysis to explore the HIV-related white matter connections alterations. Forty antiretroviraltherapy- naïve HIV patients and thirty healthy controls were enrolled. Firstly, an Automatic Anatomical Label (AAL) atlas based white matter structural network, a 90 × 90 FA-weighted matrix, was constructed for each subject. Then, the white matter connections deprived from the structural network were entered into a lasso-logistic regression model to perform HIV-control group classification. Using leave one out cross validation, a classification accuracy (ACC) of 90% (P=0.002) and areas under the receiver operating characteristic curve (AUC) of 0.96 was obtained by the classification model. This result indicated that the white matter anatomical structural connections contributed greatly to HIV-control group classification, providing solid evidence that the white matter connections were affected by HIV infection. Specially, 11 white matter connections were selected in the classification model, mainly crossing the regions of frontal lobe, Cingulum, Hippocampus, and Thalamus, which were reported to be damaged in previous HIV studies. This might suggest that the white matter connections adjacent to the HIV-related impaired regions were prone to be damaged.

Paper Details

Date Published: 13 March 2017
PDF: 6 pages
Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101370P (13 March 2017); doi: 10.1117/12.2254200
Show Author Affiliations
Zhenchao Tang, Shandong Univ. at Weihai (China)
Institute of Automation (China)
Zhenyu Liu, Institute of Automation (China)
Ruili Li, Beijing YouAn Hospital, Capital Medical Univ. (China)
Xinwei Cui, Zhengzhou Univ. (China)
Hongjun Li, Beijing YouAn Hospital, Capital Medical Univ. (China)
Enqing Dong, Shandong Univ. at Weihai (China)
Jie Tian, Institute of Automation (China)


Published in SPIE Proceedings Vol. 10137:
Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor Gimi, Editor(s)

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