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Deep microbleeds and periventricular white matter disintegrity are independent predictors of attention/executive dysfunction in non-dementia patients with small vessel disease

  • Wen-wei Cao (a1), Yao Wang (a2), Quan Dong (a1), Xue Chen (a2), Yan-sheng Li (a1), Yan Zhou (a2), Li Gao (a1), Ye Deng (a1) and Qun Xu (a1)...

Cerebral small vessel disease (SVD) is the common cause of cognitive decline in the old population. MRI can be used to clarify its mechanisms. However, the surrogate markers of MRI for early cognitive impairment in SVD remain uncertain to date. We investigated the cognitive impacts of cerebral microbleeds (CMBs), diffusion tensor imaging (DTI), and brain volumetric measurements in a cohort of post-stroke non-dementia SVD patients.


Fifty five non-dementia SVD patients were consecutively recruited and categorized into two groups as no cognitive impairment (NCI) (n = 23) or vascular mild cognitive impairment (VaMCI) (n = 32). Detailed neuropsychological assessment and multimodal MRI were completed.


The two groups differed significantly on Z scores of all cognitive domains (all p < 0.01) except for the language. There were more patients with hypertension (p = 0.038) or depression (p = 0.019) in the VaMCI than those in the NCI group. Multiple regression analysis of cognition showed periventricular mean diffusivity (MD) (β = −0.457, p < 0.01) and deep CMBs numbers (β = −0.352, p < 0.01) as the predictors of attention/executive function, which explained 45.2% of the total variance. Periventricular MD was the independent predictor for either memory (β = −0.314, p < 0.05) or visuo-spatial function (β = −0.375, p < 0.01); however, only small proportion of variance could be accounted for (9.8% and 12.4%, respectively). Language was not found to be correlated with any of the MRI parameters. No correlation was found between brain atrophic indices and any of the cognitive measures.


Arteriosclerotic CMBs and periventricular white matter disintegrity seem to be independent MRI surrogated markers in the early stage of cognitive impairment in SVD.

Corresponding author
Correspondence should be addressed to: Dr. Q Xu, MD, PhD in Neurology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160, Pujian Road, Shanghai 200127, China. Phone: 86-21-68383483. Email:
Dr. Y Zhou, MD, PhD in Radiology, RenJi Hospital, School of Medicine, Shanghai Jiao Tong University, No. 160, Pujian Road, Shanghai 200127, China. Email:
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American Psychiatric Association. (2000). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. Washington, DC: American Psychiatric Association.
Aribisala, B. S. et al. (2013). Brain atrophy associations with white matter lesions in the aging brain: the Lothian Birth Cohort 1936. European Radiology, 23, 10841092.
De Groot, J. C. et al. (2002). Periventricular cerebral white matter lesions predict rate of cognitive decline. Annals of Neurology, 52, 335341.
Fazekas, F., Chawluk, J. B., Alavi, A., Hurtig, H. I. and Zimmerman, R. A.(1987). MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. American Journal of Roentgenology, 149, 351356.
Gregoire, S. M. et al. (2009). The Microbleed Anatomical Rating Scale (MARS). Reliability of a tool to map brain microbleeds. Neurology, 73, 17591766.
Gregoire, S. M. et al. (2013). Strictly lobar microbleeds are associated with executive impairment in patients with ischemic stroke or transient ischemic attack. Stroke, 44, 12671272.
Guo, L. F., Wang, G., Zhu, X. Y., Liu, C. and Cui, L. (2013). Comparison of ESWAN, SWI-SPGR, and 2D T2*-weighted GRE sequence for depicting cerebral microbleeds. Clinical Neuroradiology, 23, 121127.
Guo, Q. H., Sun, Y. M., Yuan, J., Hong, Z. and Lu, C. Z. (2007). Application of eight executive tests in participants at Shanghai communities. Chinese Journal of Behavioral Medical Science, 16, 628631.
Huynh, T. J. et al. (2008). CT perfusion quantification of small-vessel ischemic severity. American Journal of Neuroradiology, 29, 18311836.
Lawrence, A. J. et al. (2013). Mechanisms of cognitive impairment in cerebral small vessel disease: multimodal MRI results from the St George's cognition and neuroimaging in stroke (SCANS) study. PLOS One, 8, e61014. doi:10.1371/annotation/bbde462e-c699-4c4d-9b61-050c7e6e5ce3.
Mungas, D. et al. (2001). MRI predictors of cognition in subcortical ischemic vascular disease and Alzheimer's disease. Neurology, 57, 22292235.
Pantoni, L. (2010). Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurology, 9, 689701.
Pantoni, L., Poggesi, A. and Inzitari, D. (2009). Cognitive decline and dementia related to cerebrovascular diseases: some evidence and concepts. Cerebrovascular Diseases, 27(Suppl. 1), 191196.
Patel, B. et al. (2013). Cerebral microbleeds and cognition in patients with symptomatic small vessel disease. Stroke, 44, 356361.
Pettersen, J. A. et al. (2008). Microbleed topography, leukoaraiosis, and cognition in probable Alzheimer disease from the Sunny brook dementia study. Archives of neurology, 65, 790795.
Poels, M. M. F. et al. (2010). Prevalence and risk factors of cerebral microbleeds: an update of the Rotterdam scan study. Stroke, 41, S103S106.
Ritchie, S. J. et al. (2015). Brain volumetric changes and cognitive aging during the eighth decade of life. Human Brain Mapping, 36, 49104925.
Seo, S. W. et al. (2007). Clinical significance of microbleeds in subcortical vascular dementia. Stroke, 38, 19491951.
Sheorajpanday, R. V. et al. (2013). EEG in silent small vessel disease: sLORETA mapping reveals cortical sources of vascular cognitive impairment no dementia in the default mode network. Journal of Clinical Neurophysiology, 30, 178187.
Smith, E. E. et al. (2010). Correlations between MRI white matter lesion location and executive function and episodic memory. Neurology, 76, 14921499.
Staals, J. et al. (2015). Total MRI load of cerebral small vessel disease and cognitive ability in older people. Neurobiology of Aging, 36, 28062811.
Tekin, S. and Cummings, J. F. (2002). Frontal–subcortical neuronal circuits and clinical neuropsychiatry. An update. Journal of Psychosomatic Research, 53, 647654.
van der Holst, H. M. et al. (2013). Microstructural integrity of the cingulum is related to verbal memory performance in elderly with cerebral small vessel disease: the RUN DMC study. Neuroimage, 65, 416423.
van Norden, A. G. W., van den Berg, H. A. C., de Laat, K. F., Gons, R. A. R., van Dijk, E. J. and de Leeuw, F. E. (2011). Frontal and temporal microbleeds are related to cognitive function. The Radboud university Nijmegen diffusion tensor and magnetic resonance cohort (RUN DMC) Study. Stroke, 42, 33823386.
Votaw, J. R. et al. (1999). A confrontational naming task produces congruent increases and decreases in PET and fMRI. Neuroimage, 10, 347356.
Wardlaw, J. M. et al. (2013). Neuroimaging standards for research into small vessel disease and its contribution to ageing and Neurodegeneration. Lancet Neurology, 12, 822838.
Werring, D. J. et al. (2004). Cognitive dysfunction in patients with cerebral microbleeds on T2*-weighted gradient-echo MRI. Brain, 127, 22652275.
Werring, D. J., Gregoire, S. M. and Cipolotti, L. (2010). Cerebral microbleeds and vascular cognitive impairment. Journal of the Neurological Sciences, 299, 131135.
Xu, Q. et al. (2010). Diffusion tensor imaging changes correlate with cognition better than conventional MRI findings in patients with subcortical ischemic vascular disease. Dementia and Geriatric Cognitive Disorders, 30, 317326.
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International Psychogeriatrics
  • ISSN: 1041-6102
  • EISSN: 1741-203X
  • URL: /core/journals/international-psychogeriatrics
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