Share：
Share this content in WeChat
X
[Chinese][PDF]61436
• Clinical Article •
Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multimodal MRI
WANG Xiaohua  DING Shuang  CHEN Xiaoya  ZENG Chun  YIN Feiyue  LI Yongmei 

Cite this article as: Wang XH, Ding S, Chen XY, et al. Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multimodal MRI[J]. Chin J Magn Reson Imaging, 2022, 13(5): 23-27. DOI:10.12015/issn.1674-8034.2022.05.005.


[Abstract] Objective To quantify the deep gray matter changes at the relatively early course of relapsing-remitting multiple sclerosis (RRMS) patients by multimodal MRI, and explore its correlation with white matter lesion and clinical disability.Materials and Methods 3D-T1 weighted imaging, 3D-fluid attenuated inversion recovery, quantitative sensitivity mapping and diffusion tensor imaging scans were performed on 40 patients with RRMS and 32 healthy controls (HC) to obtain gray matter nucleus volume, quantitative susceptibility value (QSV), fractional anisotropy (FA) and mean diffusivity (MD) values and white matter lesion volume (WM-LV). The independent sample t-test was used to compare the differences in the gray matter nucleus volume, QSV, FA and MD values between groups, and correlation analysis was used to assess the relationship between the indicators and the Extended Disability Scale (EDSS) score and WM-LV.Results Compared with the control group, the volume of each nucleus in the RRMS group was reduced (all P＜0.05), and the QSV of the thalamus was reduced (P＜0.05); the FA value of the caudate nucleus and thalamus were reduced, and the MD value were increased (P＜0.05). Correlation analysis showed the volume of each nucleus and the FA value of the caudate nucleus were negatively correlated with WM-LV (r=-0.315, r=-0.531, r=-0.563, r=-0.635, r=-0.543, all P＜0.05), and the MD values of the caudate nucleus, putamen and thalamus were positively correlated with WM-LV (r=0.620, r=0.671, r=0.558, all P＜0.01), the FA and MD values of the remaining nuclei and the QSV of each nucleus were not significantly correlated with WM-LV (all P＞0.05); the EDSS score was significantly negatively correlated with QSV of the thalamus (rs=-0.370, P=0.019).Conclusions In relatively early RRMS, the deep gray matter is significantly atrophy, accompanied by microstructure damage and iron disorders, which partly independent of the focal demyelination of white matter; the involvement of the thalamus is an essential feature of RRMS and its iron concentration may be a marker of disease severity in MS to monitor disease progression.
[Keywords] relapsing-remitting multiple sclerosis；deep gray matter；multimodal magnetic resonance imaging；quantitative susceptibility mapping；diffusion tensor imaging

WANG Xiaohua   DING Shuang   CHEN Xiaoya   ZENG Chun   YIN Feiyue   LI Yongmei*  

Department of Radiology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, China

Li YM, E-mail: lymzhang70@aliyun.com

Conflicts of interest   None.

ACKNOWLEDGMENTS Joint Project of Chongqing Health Commission and Science and Technology Bureau (No. 2018QNXM004).
Received  2021-12-15
Accepted  2022-04-01
DOI: 10.12015/issn.1674-8034.2022.05.005
Cite this article as: Wang XH, Ding S, Chen XY, et al. Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multimodal MRI[J]. Chin J Magn Reson Imaging, 2022, 13(5): 23-27. DOI:10.12015/issn.1674-8034.2022.05.005.

[1]
Koch-Henriksen N, Magyari M. Apparent changes in the epidemiology and severity of multiple sclerosis[J]. Nat Rev Neurol, 2021, 17(11): 676-688. DOI: 10.1038/s41582-021-00556-y.
[2]
Thompson AJ, Baranzini SE, Geurts J, et al. Multiple sclerosis[J]. Lancet, 2018, 391(10130): 1622-1636. DOI: 10.1016/S0140-6736(18)30481-1.
[3]
Bergsland N, Horakova D, Dwyer MG, et al. Gray matter atrophy patterns in multiple sclerosis: A 10-year source-based morphometry study[J]. Neuroimage Clin, 2018, 17: 444-451. DOI: 10.1016/j.nicl.2017.11.002.
[4]
Bodini B, Chard D, Altmann DR, et al. White and gray matter damage in primary progressive MS: The chicken or the egg?[J]. Neurology, 2016, 86(2): 170-176. DOI: 10.1212/WNL.0000000000002237.
[5]
Andravizou A, Dardiotis E, Artemiadis A, et al. Brain atrophy in multiple sclerosis: mechanisms, clinical relevance and treatment options[J]. Auto Immun Highlights, 2019, 10(1): 7. DOI: 10.1186/s13317-019-0117-5.
[6]
Zivadinov R, Tavazzi E, Bergsland N, et al. Brain Iron at Quantitative MRI Is Associated with Disability in Multiple Sclerosis[J]. Radiology, 2018, 289(2): 487-496. DOI: 10.1148/radiol.2018180136.
[7]
Al-Radaideh A, Athamneh I, Alabadi H, et al. Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multi-parametric, high-resolution magnetic resonance imaging (MRI)[J]. Eur Radiol, 2021, 31(2): 706-715. DOI: 10.1007/s00330-020-07199-5.
[8]
Chen QL, Ye HQ, Chen WW. The pathogenesis of iron and oxidative stress in multiple sclerosis and advances in MRI[J]. Chin J Magn Reson Imaging, 2021, 12(1): 89-92. DOI: 10.12015/issn.1674-8034.2021.01.020.
[9]
Correale J, Gaitan MI, Ysrraelit MC, et al. Progressive multiple sclerosis: from pathogenic mechanisms to treatment[J]. Brain, 2017, 140(3): 527-546. DOI: 10.1093/brain/aww258.
[10]
Ruetten P, Gillard JH, Graves MJ. Introduction to Quantitative Susceptibility Mapping and Susceptibility Weighted Imaging[J]. Br J Radiol, 2019, 92(1101): 20181016. DOI: 10.1259/bjr.20181016.
[11]
Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria[J]. Lancet Neurol, 2018, 17(2): 162-173. DOI: 10.1016/S1474-4422(17)30470-2.
[12]
Ide S, Kakeda S, Korogi Y. Anatomy of the Thalamus[J]. Brain Nerve, 2015, 67(12): 1459-1469. DOI: 10.11477/mf.1416200323.
[13]
Gu Y, Li YM, Han YL, et al. Correlation between volume and perfusion changes of deep gray matter nuclei and clinical score in patients with relapsing-remitting multiple sclerosis[J]. Chin J Med Imaging Technol, 2019, 35(2): 181-185. DOI: 10.13929/j.1003-3289.201805113.
[14]
Kawachi I, Lassmann H. Neurodegeneration in multiple sclerosis and neuromyelitis optica[J]. J Neurol Neurosurg Psychiatry, 2017, 88(2): 137-145. DOI: 10.1136/jnnp-2016-313300.
[15]
Geurts JJ, Calabrese M, Fisher E, et al. Measurement and clinical effect of grey matter pathology in multiple sclerosis[J]. Lancet Neurol, 2012, 11(12): 1082-1092. DOI: 10.1016/S1474-4422(12)70230-2.
[16]
Al-Radaideh A, Athamneh I, Alabadi H, et al. Cortical and Subcortical Morphometric and Iron Changes in Relapsing-Remitting Multiple Sclerosis and Their Association with White Matter T2 Lesion Load : A 3-Tesla Magnetic Resonance Imaging Study[J]. Clin Neuroradiol, 2019, 29(1): 51-64. DOI: 10.1007/s00062-017-0654-0.
[17]
Cappellani R, Bergsland N, Weinstock-Guttman B, et al. Subcortical deep gray matter pathology in patients with multiple sclerosis is associated with white matter lesion burden and atrophy but not with cortical atrophy: a diffusion tensor MRI study[J]. AJNR Am J Neuroradiol, 2014, 35(5): 912-919. DOI: 10.3174/ajnr.A3788.
[18]
Eshaghi A, Prados F, Brownlee WJ, et al. Deep gray matter volume loss drives disability worsening in multiple sclerosis[J]. Ann Neurol, 2018, 83(2): 210-222. DOI: 10.1002/ana.25145.
[19]
Ruano L, Portaccio E, Goretti B, et al. Age and disability drive cognitive impairment in multiple sclerosis across disease subtypes[J]. Mult Scler, 2017, 23(9): 1258-1267. DOI: 10.1177/1352458516674367.
[20]
Zhang J, Giorgio A, Vinciguerra C, et al. Gray matter atrophy cannot be fully explained by white matter damage in patients with MS[J]. Mult Scler, 2021, 27(1): 39-51. DOI: 10.1177/1352458519900972.
[21]
Choi SR, Howell OW, Carassiti D, et al. Meningeal inflammation plays a role in the pathology of primary progressive multiple sclerosis[J]. Brain, 2012, 135(Pt 10): 2925-2937. DOI: 10.1093/brain/aws189.
[22]
Jiang W, Wu Q, Zhou C, et al. Gray matter nuclei damage in acute carbon monoxide intoxication assessed in vivo using diffusion tensor MR imaging[J]. Radiol Med, 2020, 125(1): 80-86. DOI: 10.1007/s11547-019-01078-w.
[23]
Xiong H, Li YM, Hou HX, et al. Longitudinal quantitative study of brain deep nuclei in patients with multiple sclerosis by using diffusion tensor imaging[J]. Chin J Clin Radiol, 2015, 34(1): 2-6. DOI: 10.13437/j.cnki.jcr.2015.01.003.
[24]
Schweser F, Raffaini DMA, Hagemeier J, et al. Mapping of thalamic magnetic susceptibility in multiple sclerosis indicates decreasing iron with disease duration: A proposed mechanistic relationship between inflammation and oligodendrocyte vitality[J]. Neuroimage, 2018, 167: 438-452. DOI: 10.1016/j.neuroimage.2017.10.063.
[25]
Burgetova A, Dusek P, Vaneckova M, et al. Thalamic Iron Differentiates Primary-Progressive and Relapsing-Remitting Multiple Sclerosis[J]. AJNR Am J Neuroradiol, 2017, 38(6): 1079-1086. DOI: 10.3174/ajnr.A5166.
[26]
Bergsland N, Tavazzi E, Lagana MM, et al. White Matter Tract Injury is Associated with Deep Gray Matter Iron Deposition in Multiple Sclerosis[J]. J Neuroimaging, 2017, 27(1): 107-113. DOI: 10.1111/jon.12364.
[27]
Schweser F, Hagemeier J, Dwyer MG, et al. Decreasing brain iron in multiple sclerosis: The difference between concentration and content in iron MRI[J]. Hum Brain Mapp, 2021, 42(5): 1463-1474. DOI: 10.1002/hbm.25306.
[28]
Filippi M, Rocca MA, Barkhof F, et al. Association between pathological and MRI findings in multiple sclerosis[J]. Lancet Neurol, 2012, 11(4): 349-360. DOI: 10.1016/S1474-4422(12)70003-0.

PREV Susceptibility-weighted imaging joint deep learning to explore the potential association between superficial cerebral veins and deep white matter lesions
NEXT Application value of DKI in distinguishing recurrence and pseudoprogression of glioma
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn