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Research ArticleUltra-High-Field MRI/Imaging of Epilepsy/Demyelinating Diseases/Inflammation/Infection

Dynamic Changes in Long-Standing Multiple Sclerosis Revealed by Longitudinal Structural Network Analysis Using Diffusion Tensor Imaging

Hui-Qin Zhang, Jacky Chi-Yan Lee, Lu Wang, Peng Cao, Koon-Ho Chan and Henry Ka-Fung Mak
American Journal of Neuroradiology March 2024, 45 (3) 305-311; DOI: https://doi.org/10.3174/ajnr.A8115
Hui-Qin Zhang
aFrom the Department of Diagnostic Radiology (H.-Q.Z.), National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
bDepartment of Diagnostic Radiology (H.-Q.Z., P.C., H.K.-F.M.), Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
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Jacky Chi-Yan Lee
cDepartment of Medicine (J.C.-Y.L., K.-H.C.), Queen Mary Hospital, Hong Kong SAR, China
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  • ORCID record for Jacky Chi-Yan Lee
Lu Wang
dDepartment of Health Technology and Informatics (L.W.), Hong Kong Polytechnic University, Hong Kong SAR, China
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Peng Cao
bDepartment of Diagnostic Radiology (H.-Q.Z., P.C., H.K.-F.M.), Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
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Koon-Ho Chan
cDepartment of Medicine (J.C.-Y.L., K.-H.C.), Queen Mary Hospital, Hong Kong SAR, China
eAlzheimer’s Disease Research Network (H.K.-F.M., K.-H.C.), University of Hong Kong, Hong Kong SAR, China
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Henry Ka-Fung Mak
bDepartment of Diagnostic Radiology (H.-Q.Z., P.C., H.K.-F.M.), Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong SAR, China
eAlzheimer’s Disease Research Network (H.K.-F.M., K.-H.C.), University of Hong Kong, Hong Kong SAR, China
fState Key Laboratory of Brain and Cognitive Sciences (H.K.-F.M.), University of Hong Kong, Hong Kong SAR, China
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Article Figures & Data

Figures

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  • FIG 1.
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    FIG 1.

    Plots of significant nodal network measurements of MS at different time points. *P < .05; **P < .01; ***P < .001.

  • FIG 2.
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    FIG 2.

    Three-dimensional graphs showed regions representing significant association with EDSS. A, Nodal degree. B, Nodal clustering coefficient. C, Nodal efficiency. D, Nodal path length. Brain region corresponding to the anatomical labels can be found in Automated Anatomical Labeling template.

  • FIG 3.
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    FIG 3.

    Plots of the stepwise linear regression between the nodal path length of superior frontal gyrus, medial orbital part (ORBsupmed), and baseline EDSS.

Tables

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    Table 1:

    Demographic and clinical characteristics of MS

    MSP Value
    Baseline6 Months12 Months
    Sample size181818NA
    Female:male13:513:513:5NA
    Age (yr)39.11 ± 13.0339.61 ± 13.0340.11 ± 13.03NA
    Duration (yr)12.78 ± 8.5313.28 ± 8.5313.78 ± 8.53NA
    EDSS3.94 ± 2.253.94 ± 2.254.03 ± 2.18.633
    • Note:—NA indicates not applicable. The continuous measurements are presented as mean ± standard deviation. EDSS did not show significant changes during the follow-up period. Duration: the time since initial diagnosis of MS.

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    Table 2:

    Selected linear regression model about EDSS

    Dependent VariableR2Adjusted R2Regression Coefficient95% CIP Value
    ModelEDSS(t1)0.3660.327———
    Constant———−46.625[−81.89, −11.35].013
    Nodal path length of ORBsupmed———34.231[10.36, 58.10].008
    • Note:—The en dash indicates not applicable.

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American Journal of Neuroradiology: 45 (3)
American Journal of Neuroradiology
Vol. 45, Issue 3
1 Mar 2024
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Cite this article
Hui-Qin Zhang, Jacky Chi-Yan Lee, Lu Wang, Peng Cao, Koon-Ho Chan, Henry Ka-Fung Mak
Dynamic Changes in Long-Standing Multiple Sclerosis Revealed by Longitudinal Structural Network Analysis Using Diffusion Tensor Imaging
American Journal of Neuroradiology Mar 2024, 45 (3) 305-311; DOI: 10.3174/ajnr.A8115

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Longitudinal Structural Network Analysis in MS
Hui-Qin Zhang, Jacky Chi-Yan Lee, Lu Wang, Peng Cao, Koon-Ho Chan, Henry Ka-Fung Mak
American Journal of Neuroradiology Mar 2024, 45 (3) 305-311; DOI: 10.3174/ajnr.A8115
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