Share:
Share this content in WeChat
X
Clinical Article
The effects of cerebral small vessel disease total burden severity on cortical and subcortical structure and function
ZHANG Qin  WANG Jie  LI Yunfei  FENG Tianyuyi  WANG Meimei  ZHAO Xiaohu 

DOI:10.12015/issn.1674-8034.2026.02.006.


[Abstract] Objective This study employed structural and resting-state functional MRI techniques to investigate the effects of cerebral small vessel disease (CSVD) total burden severity on the structure and function of cortical regions and subcortical nuclei, and their relationship with cognitive function.Materials and Methods A total of 120 CSVD patients underwent brain MRI scans, including T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), fluid attenuated inversion recovery (FLAIR), susceptibility-weighted imaging (SWI), and resting-state functional MRI (rs-fMRI). Cognitive function was assessed using neuropsychological scales. Four CSVD imaging markers — white matter hyperintensities (WMH), enlarged perivascular spaces (ePVS), lacunes, and cerebral microbleeds (CMBs) — were evaluated on corresponding MRI sequences. A total CSVD burden score (ranging from 0 to 4) was calculated for each patient, who was then divided into four groups (scores 1 to 4). For structural analysis, voxel-based morphometry (VBM) was employed, and region of interest (ROI) were defined using the Schaefer-400 atlas (400 cortical parcels) and the Tian subcortical atlas (32 subcortical nuclei). For functional analysis, regional homogeneity (ReHo) values were computed voxel-wise across the whole brain to assess local neural activity. Analysis of covariance (ANCOVA) was used to compare differences in ROI gray matter volume and ReHo values among the four groups. Spearman's rank correlation analysis was performed to evaluate the association between significant brain regions and cognitive scores.Results Structural MRI analysis revealed a region-specific atrophy pattern, with progressively reduced gray matter volume in the left thalamus (anterior and posterior dorsal nuclei) and left sensorimotor cortices (e.g., precentral gyrus, superior parietal lobule) in higher CSVD burden groups (F values ranged from 7.533 to 9.643, all P values remained statistically significant after Bonferroni correction). Notably, the highest burden group (CSVD 4) exhibited the most severe GMV loss. Concurrently, functional MRI analysis showed significantly increased ReHo values in the left thalamus and left temporal pole in high CSVD burden groups (specifically CSVD 4 > CSVD 2 and CSVD 4 > CSVD 3; all P values remained statistically significant after FDR correction). However, no significant correlations were observed between these structural or functional metrics and cognitive scores (Mini-Mental State Examination, Montreal Cognitive Assessment) after multiple comparison correction.Conclusions Our findings indicate that increased CSVD total score is accompanied by dual-pattern alterations: "thalamic-somatomotor network structural atrophy" and "active local functional compensation". These findings provide novel neuroimaging biomarkers for understanding the mechanisms of CSVD-related cognitive impairment; however, the direct correlation with cognitive performance requires further validation through larger sample sizes and longitudinal studies.
[Keywords] cerebral small vessel disease;total score;magnetic resonance imaging;structural magnetic resonance imaging;functional magnetic resonance imaging;thalamus;cognitive impairment

ZHANG Qin   WANG Jie   LI Yunfei   FENG Tianyuyi   WANG Meimei   ZHAO Xiaohu*  

Department of Radiology, the Fifth People's Hospital of Shanghai, Fudan University, Shanghai 200240, China

Corresponding author: ZHAO X H, E-mail: xhzhao999@263.net

Conflicts of interest   None.

Received  2025-10-27
Accepted  2026-01-08
DOI: 10.12015/issn.1674-8034.2026.02.006
DOI:10.12015/issn.1674-8034.2026.02.006.

[1]
ELAHI F M, WANG M M, MESCHIA J F. Cerebral Small Vessel Disease-Related Dementia: More Questions Than Answers[J]. Stroke, 2023, 54(3): 648-660. DOI: 10.1161/STROKEAHA.122.038265.
[2]
DUERING M, BIESSELS G J, BRODTMANN A, et al. Neuroimaging standards for research into small vessel disease-advances since 2013[J]. Lancet Neurol, 2023, 22(7): 602-618. DOI: 10.1016/S1474-4422(23)00131-X.
[3]
TRUIN L S, KÖHLER S, HEGER I S, et al. Associations of an individual's need for cognition with structural brain damage and cognitive functioning/impairment: cross-sectional population-based study[J]. Br J Psychiatry, 2024, 224(6): 189-197. DOI: 10.1192/bjp.2023.159.
[4]
LV Y, CHENG X, DONG Q. SGLT1 and SGLT2 inhibition, circulating metabolites, and cerebral small vessel disease: a mediation Mendelian Randomization study[J/OL]. Cardiovasc Diabetol, 2024, 23(1): 157 [2025-10-27]. https://doi.org/10.1186/s12933-024-02255-6. DOI: 10.1186/s12933-024-02255-6.
[5]
WARDLAW J M, SMITH C, DICHGANS M. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging[J]. Lancet Neurol, 2013, 12(5): 483-497. DOI: 10.1016/S1474-4422(13)70060-7.
[6]
LI H, CHENG M, GAO Y, et al. Does the Burden of CSVD Modify the Efficacy of Dual Antiplatelet Therapy?: A Post Hoc Analysis of the INSPIRES Trial[J]. Stroke, 2025, 56(6): 1376-1387. DOI: 10.1161/STROKEAHA.124.049826.
[7]
YING Y, LI Y, YAO T, et al. Heterogeneous blood-brain barrier dysfunction in cerebral small vessel diseases[J]. Alzheimers Dement, 2024, 20(7): 4527-4539. DOI: 10.1002/alz.13874.
[8]
TULADHAR A M, VAN NORDEN A G W, DE LAAT K F, et al. White matter integrity in small vessel disease is related to cognition[J]. Neuroimage Clin, 2015, 7: 518-524. DOI: 10.1016/j.nicl.2015.02.003.
[9]
CHEN F, CHEN Q, ZHU Y, et al. Alterations in Dynamic Functional Connectivity in Patients with Cerebral Small Vessel Disease[J]. Transl Stroke Res, 2024, 15(3): 580-590. DOI: 10.1007/s12975-023-01148-2.
[10]
HWANG K, BERTOLERO M A, LIU W B, et al. The Human Thalamus Is an Integrative Hub for Functional Brain Networks[J]. J Neurosci, 2017, 37(23): 5594-5607. DOI: 10.1523/JNEUROSCI.0067-17.2017.
[11]
FANG Z, DANG Y, PING A, et al. Human high-order thalamic nuclei gate conscious perception through the thalamofrontal loop[J/OL]. Science, 2025, 388(6742): eadr3675 [2025-10-27]. https://doi.org/10.1126/science.adr3675. DOI: 10.1126/science.adr3675.
[12]
SCHAEFER A, KONG R, GORDON E M, et al. Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI[J]. Cereb Cortex, 2018, 28(9): 3095-3114. DOI: 10.1093/cercor/bhx179.
[13]
TIAN Y, MARGULIES D S, BREAKSPEAR M, et al. Topographic organization of the human subcortex unveiled with functional connectivity gradients[J]. Nat Neurosci, 2020, 23(11): 1421-1432. DOI: 10.1038/s41593-020-00711-6.
[14]
STAALS J, MAKIN S D J, DOUBAL F N, et al. Stroke subtype, vascular risk factors, and total MRI brain small-vessel disease burden[J]. Neurology, 2014, 83(14): 1228-1234. DOI: 10.1212/WNL.0000000000000837.
[15]
FAZEKAS F, CHAWLUK J B, ALAVI A, et al. MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging[J]. AJR Am J Roentgenol, 1987, 149(2): 351-356. DOI: 10.2214/ajr.149.2.351.
[16]
ASHBURNER J, FRISTON K J. Unified segmentation[J]. NeuroImage, 2005, 26(3): 839-851. DOI: 10.1016/j.neuroimage.2005.02.018.
[17]
YAN C G, WANG X D, ZUO X N, et al. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging[J]. Neuroinformatics, 2016, 14(3): 339-351. DOI: 10.1007/s12021-016-9299-4.
[18]
ROSEBOROUGH A D, SAAD L, GOODMAN M, et al. White matter hyperintensities and longitudinal cognitive decline in cognitively normal populations and across diagnostic categories: A meta-analysis, systematic review, and recommendations for future study harmonization[J]. Alzheimers Dement, 2023, 19(1): 194-207. DOI: 10.1002/alz.12642.
[19]
YEO B T T, KRIENEN F M, SEPULCRE J, et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity[J]. J Neurophysiol, 2011, 106(3): 1125-1165. DOI: 10.1152/jn.00338.2011.
[20]
CSIK B, NYÚL-TÓTH Á, GULEJ R, et al. Senescent Endothelial Cells in Cerebral Microcirculation Are Key Drivers of Age-Related Blood-Brain Barrier Disruption, Microvascular Rarefaction, and Neurovascular Coupling Impairment in Mice[J/OL]. Aging Cell, 2025, 24(7): e70048 [2025-10-27]. https://doi.org/10.1111/acel.70048. DOI: 10.1111/acel.70048.
[21]
MARKUS H S, JOUTEL A. The pathogenesis of cerebral small vessel disease and vascular cognitive impairment[J]. Physiol Rev, 2025, 105(3): 1075-1171. DOI: 10.1152/physrev.00028.2024.
[22]
LIU R, WU W, YE Q, et al. Distinctive and Pervasive Alterations of Functional Brain Networks in Cerebral Small Vessel Disease with and without Cognitive Impairment[J]. Dement Geriatr Cogn Disord, 2019, 47(1-2): 55-67. DOI: 10.1159/000496455.
[23]
CHENG Z, LI M, LI J, et al. Long-term impact of white matter hyperintensities and amyloid beta on thalamic subregions in cerebral small vessel disease: A prospective cohort study[J/OL]. Alzheimers Dement, 2025, 21(8): e70553 [2025-10-27]. https://doi.org/10.1002/alz.70553. DOI: 10.1002/alz.70553.
[24]
DUERING M, RIGHART R, WOLLENWEBER F A, et al. Acute infarcts cause focal thinning in remote cortex via degeneration of connecting fiber tracts[J]. Neurology, 2015, 84(16): 1685-1692. DOI: 10.1212/WNL.0000000000001502.
[25]
KROHN S, VON SCHWANENFLUG N, WASCHKE L, et al. A spatiotemporal complexity architecture of human brain activity[J/OL]. Sci Adv, 2023, 9(5): eabq3851 [2025-10-27]. https://doi.org/10.1126/sciadv.abq3851. DOI: 10.1126/sciadv.abq3851.
[26]
HONEY C J, SPORNS O. Dynamical consequences of lesions in cortical networks[J]. Hum Brain Mapp, 2008, 29(7): 802-809. DOI: 10.1002/hbm.20579.
[27]
NORTHOFF G, WOLMAN A, ZHANG J. Brain dynamics shape cognition-Spatiotemporal Neuroscience[J]. Phys Life Rev, 2025, 54: 173-201. DOI: 10.1016/j.plrev.2025.07.009.
[28]
KESKIN K, CATAL Y, WOLMAN A, et al. The brain's internal echo: Longer timescales, stronger recurrent connections and higher neural excitation in self regions[J/OL]. NeuroImage, 2025, 312: 121221 [2025-10-27]. https://doi.org/10.1016/j.neuroimage.2025.121221. DOI: 10.1016/j.neuroimage.2025.121221.
[29]
HALASSA M M, SHERMAN S M. Thalamocortical circuit motifs: a general framework[J]. Neuron, 2019, 103(5): 762-770. DOI: 10.1016/j.neuron.2019.06.005.
[30]
OUHAZ Z, FLEMING H, MITCHELL A S. Cognitive functions and neurodevelopmental disorders involving the prefrontal cortex and mediodorsal thalamus[J/OL]. Front Neurosci, 2018, 12: 33 [2025-10-27]. https://doi.org/10.3389/fnins.2018.00033. DOI: 10.3389/fnins.2018.00033.
[31]
ZHANG J, JIA X, WANG Q, et al. Age-related alterations in regional cerebrovascular reactivity: mediation by grey matter atrophy and association with cognitive performance[J/OL]. Age Ageing, 2025, 54(12): afaf353 [2025-10-27]. https://doi.org/10.1093/ageing/afaf353. DOI: 10.1093/ageing/afaf353.

PREV MRI based subcortical structure and function changes in patients with chronic heart failure
NEXT Associations between plasma chitinase-3-like protein 1 levels and white matter microstructure in patients with amnestic mild cognitive impairment: A DTI study
  



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