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Identifying the white matter impairments among ART-naïve HIV patients: a multivariate pattern analysis of DTI data

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To identify the white matter (WM) impairments of the antiretroviral therapy (ART)-naïve HIV patients by conducting a multivariate pattern analysis (MVPA) of Diffusion Tensor Imaging (DTI) data

Methods

We enrolled 33 ART-naïve HIV patients and 32 Normal controls in the current study. Firstly, the DTI metrics in whole brain WM tracts were extracted for each subject and feed into the Least Absolute Shrinkage and Selection Operators procedure (LASSO)-Logistic regression model to identify the impaired WM tracts. Then, Support Vector Machines (SVM) model was constructed based on the DTI metrics in the impaired WM tracts to make HIV-control group classification. Pearson correlations between the WM impairments and HIV clinical statics were also investigated.

Results

Extensive HIV-related impairments were observed in the WM tracts associated with motor function, the corpus callosum (CC) and the frontal WM. With leave-one-out cross validation, accuracy of 83.08% (P=0.002) and the area under the Receiver Operating Characteristic curve of 0.9110 were obtained in the SVM classification model. The impairments of the CC were significantly correlated with the HIV clinic statics.

Conclusion

The MVPA was sensitive to detect the HIV-related WM changes. Our findings indicated that the MVPA had considerable potential in exploring the HIV-related WM impairments.

Key points

• WM impairments along motor pathway were detected among the ART-naïve HIV patients

• Prominent HIV-related WM impairments were observed in CC and frontal WM

• The impairments of CC were significantly related to the HIV clinic statics

• The CC might be susceptible to immune dysfunction and HIV replication

• Multivariate pattern analysis had potential for studying the HIV-related white matter impairments

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Abbreviations

ART:

Antiretroviral Therapy

MVPA:

Multivariate Pattern Analysis

DTI:

Diffusion tensor Imaging

WM:

White Matter

FA:

Fractional Anisotropy

MD:

Mean Diffusivity

AD:

Axial Diffusivity

RD:

Radial Diffusivity

ROI:

Regions of Interests

LASSO:

The Least Absolute Shrinkage and Selection Operators procedure

SVM:

Support Vector Machines

ACC:

Accuracy

ROC:

Receiver Operating Characteristic

AUC:

Area under the ROC curve

LOOCV:

Leave one out cross-validation

CC:

Corpus Callosum

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Acknowledgements

This paper was supported by the National Natural Science Foundation of China under Grant No. 81671848, 81501549, 81527805, 81371635, 81227901, 61231004, 81571634, the Science and Technology Service Network Initiative Program of Chinese Academy of Science under Grant NO. KFJ-SW-STS-160, the Strategic Priority Research Program from the Chinese Academy of Sciences under Grant NO. XDB02060010, the Beijing Municipal Science & Technology Commission No. Z161100002616022, the Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding under Grant NO. ZYLX201511, and the Beijing Municipal Administration of Hospitals Incubating Program under Grant NO. PX2016036. The study was approved by the Ethics Committee of the Beijing YouAn Hospital, Capital Medical University. All the subjects had provided written informed consent after a detailed explanation of this study. The authors would like to express their deep appreciation to all anonymous reviewers for their kind comments.

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Author notes

  1. Zhenchao Tang, Zhenyu Liu and Ruili Li contributed equally to this article.

Authors and Affiliations

  1. School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, Shandong Province, 264209, China

    Zhenchao Tang & Enqing Dong

  2. CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, 100190, China

    Zhenchao Tang, Zhenyu Liu, Xin Yang, Shuo Wang, Dongdong Yu & Jie Tian

  3. Department of Radiology, Beijing YouAn Hospital, Capital Medical University, Beijing, 100069, China

    Ruili Li & Hongjun Li

  4. Cooperative Innovation Center of Internet Healthcare, Zhengzhou University, Zhengzhou, China, 450052

    Xingwei Cui

  5. University of Chinese Academy of Sciences, Beijing, 100049, China

    Jie Tian

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  1. Zhenchao Tang
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Corresponding authors

Correspondence to Hongjun Li, Enqing Dong or Jie Tian.

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Guarantor

The scientific guarantor of this publication is Jie Tian.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Funding

This paper is supported by the National Natural Science Foundation of China under Grant No. 81671848, 81501549, 81527805, 81371635, 81227901, 61231004, 81571634, Science and Technology Service Network Initiative Program of Chinese Academy of Science under Grant NO. KFJ-SW-STS-160, the Strategic Priority Research Program from Chinese Academy of Sciences under Grant NO. XDB02060010, the Beijing Municipal Science & Technology Commission No. Z161100002616022, the Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding under Grant NO. ZYLX201511, and the Beijing Municipal Administration of Hospitals Incubating Program under Grant NO. PX2016036.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

The study was approved by the Ethics Committee of the Beijing YouAn Hospital, Capital Medical University.

Methodology

• retrospective

• cross sectional study

• performed at one institution

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Tang, Z., Liu, Z., Li, R. et al. Identifying the white matter impairments among ART-naïve HIV patients: a multivariate pattern analysis of DTI data. Eur Radiol 27, 4153–4162 (2017). https://doi.org/10.1007/s00330-017-4820-1

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  • DOI: https://doi.org/10.1007/s00330-017-4820-1

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