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Original article| Volume 70, 104516, February 2023

Structural covariance in subcortical regions in multiple sclerosis and neuromyelitis optica spectrum disorders: An MRI-based study with automated brain volumetry

  • Author Footnotes
    1 These authors contributed equally to this work.
    Yan Xie
    Footnotes
    1 These authors contributed equally to this work.
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Author Footnotes
    1 These authors contributed equally to this work.
    Yan Zhang
    Footnotes
    1 These authors contributed equally to this work.
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Yihao Yao
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Dong Liu
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Hongquan Zhu
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
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  • Chengxia Liu
    Correspondence
    Corresponding authors.
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Wenzhen Zhu
    Correspondence
    Corresponding authors.
    Affiliations
    Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Avenue, Wuhan 430030, China
    Search for articles by this author
  • Author Footnotes
    1 These authors contributed equally to this work.
Published:January 14, 2023DOI:https://doi.org/10.1016/j.msard.2023.104516

      Highlights

      • Multiple sclerosis patients exhibited extensive atrophy of subcortical regions.
      • Multiple sclerosis patients had more additional connections in structural covariance.
      • More missing connections were found in NMOSD patients.
      • The structural covariance can use multi-atlas-based anatomical segmentation method.

      Abstract

      Purpose

      This study aimed to investigate the alterations of brain volumetry and associated structural covariance in subcortical regions in multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD).

      Materials and methods

      Fourty MS patients, 35 NMOSD patients and 34 healthy controls (HC) underwent 3D T1-weighted image and 3D T2 FLAIR of MRI. The volume differences in subcortical regions were compared between the MS, NMOSD, and HC groups by automated brain volumetry. Structural covariance analysis was performed with each pair of these regions to investigate the alterations of anatomical connections in MS and NMOSD compared to HC.

      Results

      Compared with HC, MS patients presented significantly smaller volume in some subcortical and infratentorial regions (P<0.05), while NMOSD patients showed no significant difference of volumetry in any of the brain regions (P>0.05), although they had no significant difference in disease duration (MS 3.95±3.73 ys; NMOSD 3.11±4.61 ys; P>0.05). In addition, the structural covariance analyses revealed synergic volume alteration in subcortical regions both in the MS and NMOSD groups. More extensive additional connections compared with HC were found in MS patients and more extensive missing connections compared with HC were found in NMOSD patients.

      Conclusion

      This study revealed distinct patterns of brain structural damage and reorganization in MS and NMOSD, which could facilitate a better distinction between these two entities.

      Keywords

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      References

        • Abrigo J.
        • Shi L.
        • Luo Y.
        • et al.
        Standardization of hippocampus volumetry using automated brain structure volumetry tool for an initial Alzheimer's disease imaging biomarker.
        Acta Radiol. 2019; 60: 769-776
        • Alexander-Bloch A.
        • Giedd J.N.
        • Bullmore E.
        Imaging structural co-variance between human brain regions.
        Nat. Rev. Neurosci. 2013; 14: 322-336
        • Audoin B.
        • Zaaraoui W.
        • Reuter F.
        • et al.
        Atrophy mainly affects the limbic system and the deep grey matter at the first stage of multiple sclerosis.
        J. Neurol. Neurosurg. Psychiatry. 2010; 81: 690-695
        • Bernabeu-Sanz A.
        • Morales S.
        • Naranjo V.
        • Sempere A.P.
        Contribution of gray matter atrophy and white matter damage to cognitive impairment in mildly disabled relapsing-remitting multiple sclerosis patients.
        Diagnostics(Basel). 2021; 11: 578
        • Calabrese M.
        • Rinaldi F.
        • Grossi P.
        • et al.
        Basal ganglia and frontal/parietal cortical atrophy is associated with fatigue in relapsing-remitting multiple sclerosis.
        Mult. Scler. 2010; 16: 1220-1228
        • Chen X.
        • Fu J.
        • Luo Q.
        • et al.
        Altered volume and microstructural integrity of hippocampus in NMOSD.
        Mult. Scler. Relat. Disord. 2019; 28: 132-137
        • Cifelli A.
        • Arridge M.
        • Jezzard P.
        • Esiri M.M.
        • Palace J.
        • Matthews P.M.
        Thalamic neurodegeneration in multiple sclerosis.
        Ann. Neurol. 2002; 52: 650-653
        • Cummings J.L.
        Frontal-subcortical circuits and human behavior.
        Arch. Neurol. 1993; 50: 873-880
        • Duan Y.
        • Zhuo Z.
        • Li H.
        • et al.
        Brain structural alterations in MOG antibody diseases: a comparative study with AQP4 seropositive NMOSD and MS.
        J. Neurol. Neurosurg. Psychiatry. 2021; 92: 709-716
        • Dutra B.G.
        • da Rocha A.J.
        • Nunes R.H.
        • Maia A.C.M.J.
        Neuromyelitis optica spectrum disorders: spectrum of MR imaging findings and their differential diagnosis.
        Radiographics. 2018; 38: 169-193
        • Eshaghi A.
        • Marinescu R.V.
        • Young A.L.
        • et al.
        Progression of regional grey matter atrophy in multiple sclerosis.
        Brain. 2018; 141: 1665-1677
        • Filippi M.
        • Brück W.
        • Chard D.
        • et al.
        Association between pathological and MRI findings in multiple sclerosis.
        Lancet Neurol. 2019; 18: 198-210
        • Grothe M.
        • Lotze M.
        • Langner S.
        • Dressel A.
        The role of global and regional gray matter volume decrease in multiple sclerosis.
        J. Neurol. 2016; 263: 1137-1145
        • Haider L.
        • Simeonidou C.
        • Steinberger G.
        • et al.
        Multiple sclerosis deep grey matter: the relation between demyelination, neurodegeneration, inflammation and iron.
        J. Neurol. Neurosurg. Psychiatry. 2014; 85: 1386-1395
        • Houtchens M.K.
        • Benedict R.H.
        • Killiany R.
        • et al.
        Thalamic atrophy and cognition in multiple sclerosis.
        Neurology. 2007; 69: 1213-1223
        • Hyun J.W.
        • Park G.
        • Kwak K.
        • et al.
        Deep gray matter atrophy in neuromyelitis optica spectrum disorder and multiple sclerosis.
        Eur. J. Neurol. 2017; 24: 437-445
        • Kato S.
        • Hagiwara A.
        • Yokoyama K.
        • et al.
        Microstructural white matter abnormalities in multiple sclerosis and neuromyelitis optica spectrum disorders: evaluation by advanced diffusion imaging.
        J. Neurol. Sci. 2022; 436120205
        • Lee C.Y.
        • Mak H.K.
        • Chiu P.W.
        • Chang H.C.
        • Barkhof F.
        • Chan K.H.
        Differential brainstem atrophy patterns in multiple sclerosis and neuromyelitis optica spectrum disorders.
        J. Magn. Reson. Imaging. 2018; 47: 1601-1609
        • Liu C.
        • Zhao L.
        • Yang S.
        • et al.
        Structural changes in the lobar regions of brain in cerebral small-vessel disease patients with and without cognitive impairment: an MRI-based study with automated brain volumetry.
        Eur. J. Radiol. 2020; 126108967
        • Lorefice L.
        • Carta E.
        • Frau J.
        • et al.
        The impact of deep grey matter volume on cognition in multiple sclerosis.
        Mult. Scler. Relat. Disord. 2020; 45102351
        • Lorefice L.
        • Fenu G.
        • Carta E.
        • et al.
        Bipolar disorders and deep grey matter in multiple sclerosis: a preliminary quantitative MRI study.
        Mult. Scler. Relat. Disord. 2020; 46102564
        • Lorefice L.
        • Fenu G.
        • Mammoliti R.
        • et al.
        Event-related potentials and deep grey matter atrophy in multiple sclerosis: exploring the possible associations with cognition.
        Mult. Scler. Relat. Disord. 2021; 49102785
        • Luchetti S.
        • Fransen N.L.
        • van Eden C.G.
        • Ramaglia V.
        • Mason M.
        • Huitinga I.
        Progressive multiple sclerosis patients show substantial lesion activity that correlates with clinical disease severity and sex: a retrospective autopsy cohort analysis.
        Acta Neuropathol. 2018; 135: 511-528
        • Mai Y.
        • Yu Q.
        • Zhu F.
        • et al.
        AD resemblance atrophy index as a diagnostic biomarker for Alzheimer's disease: a retrospective clinical and biological validation.
        J. Alzheimers Dis. 2021; 79: 1023-1032
        • Mancuso R.
        • Hernis A.
        • Agostini S.
        • Rovaris M.
        • Caputo D.
        • Clerici M.
        MicroRNA-572 expression in multiple sclerosis patients with different patterns of clinical progression.
        J. Transl. Med. 2015; 13: 148
        • Mechelli A.
        • Friston K.J.
        • Frackowiak R.S.
        • Price C.J.
        Structural covariance in the human cortex.
        J. Neurosci. 2005; 25: 8303-8310
        • Mendez M.F.
        • Adams N.L.
        • Lewandowski K.S.
        Neurobehavioral changes associated with caudate lesions.
        Neurology. 1989; 39: 349-354
        • Minagar A.
        • Barnett M.H.
        • Benedict R.H.
        • et al.
        The thalamus and multiple sclerosis: modern views on pathologic, imaging, and clinical aspects.
        Neurology. 2013; 80: 210-219
        • Motl R.W.
        • Hubbard E.A.
        • Sreekumar N.
        • et al.
        Pallidal and caudate volumes correlate with walking function in multiple sclerosis.
        J. Neurol. Sci. 2015; 354: 33-36
        • Naess-Schmidt E.
        • Tietze A.
        • Blicher J.U.
        • et al.
        Automatic thalamus and hippocampus segmentation from MP2RAGE: comparison of publicly available methods and implications for DTI quantification.
        Int. J. Comput. Assist. Radiol. Surg. 2016; 11: 1979-1991
        • Pudlac A.
        • Burgetova A.
        • Dusek P.
        • et al.
        Deep gray matter iron content in neuromyelitis optica and multiple sclerosis.
        Biomed. Res. Int. 2020; 20206492786
        • Rueda-Lopes F.C.
        • Pessoa F.M.C.
        • Tukamoto G.
        • et al.
        Default-mode network and deep gray-matter analysis in neuromyelitis optica patients.
        J. Neuroradiol. 2018; 45: 256-260
        • Sacco R.
        • Bisecco A.
        • Corbo D.
        • et al.
        Cognitive impairment and memory disorders in relapsing-remitting multiple sclerosis: the role of white matter, gray matter and hippocampus.
        J. Neurol. 2015; 262: 1691-1697
        • Tewarie P.
        • Steenwijk M.D.
        • Tijms B.M.
        • et al.
        Disruption of structural and functional networks in long-standing multiple sclerosis.
        Hum. Brain Mapp. 2014; 35: 5946-5961
        • Tur C.
        • Eshaghi A.
        • Altmann D.R.
        • et al.
        Structural cortical network reorganization associated with early conversion to multiple sclerosis.
        Sci. Rep. 2018; 8: 10715
        • von Glehn F.
        • Jarius S.
        • Cavalcanti Lira R.P.
        • et al.
        Structural brain abnormalities are related to retinal nerve fiber layer thinning and disease duration in neuromyelitis optica spectrum disorders.
        Mult. Scler. J. 2014; 20: 1189-1197
        • Wang C.
        • Zhao L.
        • Luo Y.
        • et al.
        Structural covariance in subcortical stroke patients measured by automated MRI-based volumetry.
        Neuroimage Clin. 2019; 22101682
        • Wang Z.
        • Yu Z.
        • Wang Y.
        • et al.
        3D compressed convolutional neural network differentiates neuromyelitis optical spectrum disorders from multiple sclerosis using automated white matter hyperintensities segmentations.
        Front. Physiol. 2020; 11612928https://doi.org/10.3389/fphys.2020.612928
        • Zhang N.
        • Sun J.
        • Wang Q.
        • et al.
        Differentiate aquaporin-4 antibody negative neuromyelitis optica spectrum disorders from multiple sclerosis by multimodal advanced MRI techniques.
        Mult. Scler. Relat. Disord. 2020; 41102035
        • Zhao L.
        • Zhang X.
        • Luo Y.
        • et al.
        Automated detection of hippocampal sclerosis: comparison of a composite MRI-based index with conventional MRI measures.
        Epilepsy Res. 2021; 174106638
        • Zheng F.
        • Li Y.
        • Zhuo Z.
        • et al.
        Structural and functional hippocampal alterations in Multiple sclerosis and neuromyelitis optica spectrum disorder.
        Mult. Scler. 2021; https://doi.org/10.1177/13524585211032800:13524585211032800
        • Zielinski B.A.
        • Gennatas E.D.
        • Zhou J.
        • Seeley W.W.
        Network-level structural covariance in the developing brain.
        Proc. Natl. Acad. Sci. USA. 2010; 107: 18191-18196