Analysis of cerebral gray matter
structure in multiple sclerosis and neuromyelitis optica

doi:10.16098/j.issn.0529-1356.2024.01.003

Abstract

Abstract:

Objective The volume and cortical thickness of gray matter in patients with multiple sclerosis (MS) and neuromyelitis optica (NMO) were compared and analyzed by voxel based morphometry (VBM) and surface-based morphometry (SBM), and the differences in the structural changes of gray matter in the two diseases were discussed. Methods A total of 21 MS patients, 16 NMO patients and 19 healthy controls were scanned by routine MRI sequence. The data were processed and analyzed by VBM and SBM method based on the statistical parameter tool SPM12 of Matlab2014a platform and the small tool CAT12 under SPM12. Results Compared with the normal control group (NC), after Gaussian random field (GRF) correction, the gray matter volume in MS group was significantly reduced in left superior occipital, left cuneus, left calcarine, left precuneus, left postcentral, left central paracentral lobule, right cuneus, left middle frontal, left superior frontal and left superior medial frontal (P<0.05). After family wise error (FWE) correction, the thickness of left paracentral, left superiorfrontal and left precuneus cortex in MS group was significantly reduced (P<0.05). Compared with the NC group, after GRF correction, the gray matter volume in the left postcentral, left precentral, left inferior parietal, right precentral and right middle frontal in NMO group was significantly increased (P<0.05). In NMO group, the volume of gray matter in left middle occipital, left superior occipital, left inferior temporal, right middle occipital, left superior frontal orbital, right middle cingulum, left anterior cingulum, right angular and left precuneus were significantly decreased (P<0.05). Brain regions showed no significant differences in cortical thickness between NMO groups after FWE correction. Compared with the NMO group, after GRF correction, the gray matter volume in the right fusiform and right middle frontal in MS group was increased significantly(P<0.05). In MS group, the gray matter volume of left thalamus, left pallidum, left precentral, left middle frontal, left middle temporal, right pallidum, left inferior parietal and right superior parietal were significantly decreased (P<0.05). After FWE correction, the thickness of left inferiorparietal, left superiorparietal, left supramarginal, left paracentral, left superiorfrontal and left precuneus cortex in MS group decreased significantly (P<0.05). Conclusion The atrophy of brain gray matter structure in MS patients mainly involves the left parietal region, while NMO patients are not sensitive to the change of brain gray matter structure. The significant difference in brain gray matter volume between MS patients and NMO patients is mainly located in the deep cerebral nucleus mass.

Key words:

Multiple sclerosis, Neuromyelitis optica, Structure of brain, Morphological analysis based on voxel, Cerebral morphological analysis, Human

CLC Number:

R455.2

LIU Xiao-li XU Lin WU Ai-xue WEN Cai-yun LI Ru-hua WU An-ting CHEN Dai-qian CHEN Cheng-chun.

Analysis of cerebral gray matter structure in multiple sclerosis and neuromyelitis optica [J]. Acta Anatomica Sinica, 2024, 55(1): 17-24.

References

［1］Prasad S, Chen J. What You need to know about AQP4, MOG, and NMOSD［J］. Semin Neurol, 2019(39): 718-731.

［2］Azimian M, Arian M, Shojaei SF, et al. The effectiveness of group hope therapy training on the quality of life and meaning of life in patients with multiple sclerosis and their family caregivers［J］. Iran J Psychiatry 2021, 16(3): 260-270.

［3］Rocca MA, Battaglini M, Benedict RH, et al. Brain MRI atrophy quantification in MS from methods to clinical application［J］. Neurology, 2017, 88(24): 403-413.

［4］Matthews L, Marasco R, Jenkinson M, et al. Distinction of seropositive NMO spectrum disorder and MS brain lesion distribution［J］. Neurology, 2013,80(14): 1330-1337.

［5］Ashburner J, Friston KJ. Voxel-based morphometry-the methods［J］. Neuroimage, 2000, 11(6pt 1): 805-821.

［6］Li RCh, Tang J, Yang YF, et al. Volume changes of cerebral gray matter in patients with obsessive-compulsive disorder ——morphological analysis based on voxel［J］. Acta Anatomica Sinica, 2021, 52(5): 692-697. (in Chinese)

李若川, 唐洁, 杨勇锋, 等. 强迫症患者大脑灰质体积变化 ———基于体素的形态学分析［J］. 解剖学报, 2021, 52(5): 692-697.

［7］Goto M, Abe O, Hagiwara A, et al. Advantages of using both voxel-and surface-based morphometry in cortical morphology analysis: a review of various applications［J］. Magn Reson Med Sci, 2022, 21(1): 41-57.

［8］Prinster A, Quarantelli M, Lanzillo R, et al. A voxel-based morphometry study of disease severity correlates in relapsing-remitting multiple sclerosis［J］. Mult Scler, 2010, 16(1): 45-54.

［9］Zhang X, Zhang F, Huang D, et al. Contribution of gray and white matter abnormalities to cognitive impairment in multiple sclerosis［J］. Int J Mol Sci, 2016, 18(1): 1-13.

［10］Eshaghi A, Marinescu RV, Young AL, et al. Progression of regional grey matter atrophy in multiple sclerosis［J］. Brain, 2018, 141(6): 1665-1677.

［11］Steenwijk MD, Geurts JJ, Daams M, et al. Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant［J］. Brain, 2016, 139(1): 115-126.

［12］Von Glehn F, Jarius S, Cavalcanti Lira RP, et al. Structural brain abnormalities are related to retinal nerve fiber layer thinning and disease duration in neuromyelitis optica spectrum disorders［J］. Mult Scler, 2014, 20(9): 1189-1197.

［13］Sanchez-Catasus CA, Cabrera-Gomez J, Almaguer Melian W, et al. The number of optic neuritis attacks is a potential confounder when comparing patients with NMO vs. controls by voxel-based neuroimaging analysis［J］. Acta Radiol, 2016, 57(8): 985-991.

［14］Calabrese M, Oh MS, Favaretto A, et al. No MRI evidence of cortical lesions in neuromyelitis optica［J］. Neurology, 2012, 79(16): 1671-1676.

［15］Pichiecchio A, Tavazzi E, Poloni G, et al. Advanced magnetic resonance imaging of neuromyelitis optica: a multiparametric approach［J］. Mult Scler, 2012, 18(6): 817-824.

［16］Wang T, Lian Z, Wu X, et al. Subcortical structural abnormalities in female neuromyelitis optica patients with neuropathic pain［J］. Mult Scler Relat Disord, 2020, 37: 101432.

［17］Liu Y, Xie T, He Y, et al. Cortical thinning correlates with cognitive change in multiple sclerosis but not in neuromyelitis optica［J］. Eur Radiol, 2014, 24(9): 2334-2343.

［18］Duan Y, Liu Y, Liang P, et al. Comparison of grey matter atrophy between patients with neuromyelitis optica and multiple sclerosis: a voxel-based morphometry study［J］. Eur J Radiol, 2012, 81(2): 110-114.

［19］Pudlac A, Burgetova A, Dusek P, et al. Deep gray matter iron content in neuromyelitis optica and multiple sclerosis［J］. Biomed Res Int, 2020, 2020: 6492786.

［20］Minagar A, Barnett MH, Benedict RH, et al. The thalamus and multiple sclerosis: modern views on pathologic, imaging, and clinical aspects［J］. Neurology, 2013, 80(2): 210-219.

［21］Schoonheim MM, Popescu V, Rueda Lopes FC, et al. Subcortical atrophy and cognition: sex effects in multiple sclerosis［J］. Neurology, 2012, 79(17): 1754-1761.

［22］Lansley J, Mataix-Cols D, Grau M, et al. Localized grey matter atrophy in multiple sclerosis: a meta-analysis of voxel-based morphometry studies and associations with functional disability［J］. Neurosci Biobehav Rev, 2013, 37(5): 819-830.

［23］Solana E, Martinez-Heras E, Montal V, et al. Regional grey matter microstructural changes and volume loss according to disease duration in multiple sclerosis patients［J］. Sci Rep, 2021, 11(1): 1-11.

［24］Benedict RH, Hulst HE, Bergsland N, et al. Clinical significance of atrophy and white matter mean diffusivity within the thalamus of multiple sclerosis patients［J］. Mult Scler, 2013, 19(11): 1478-1484.

［25］Magon S, Chakravarty MM, Amann M, et al. Label-fusion-segmentation and deformation-based shape analysis of deep gray matter in multiple sclerosis: the impact of thalamic subnuclei on disability［J］. Hum Brain Mapp, 2014, 35(8): 4193-4203.

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Analysis of cerebral gray matter structure in multiple sclerosis and neuromyelitis optica

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