Translational Stroke Research

, Volume 11, Issue 1, pp 29–38 | Cite as

Strictly Lobar Cerebral Microbleeds Are Associated with Increased White Matter Volume

  • Pei-Ning Wang
  • Kun-Hsien Chou
  • Li-Ning Peng
  • Li-Kuo Liu
  • Wei-Ju Lee
  • Liang-Kung Chen
  • Ching-Po Lin
  • Chih-Ping ChungEmail author
Original Article


Cerebral small vessel diseases (CSVD), such as white matter hyperintensities (WMH), have been acknowledged as a cause of brain atrophy. However, the relationship between brain volumes and cerebral microbleeds (CMBs) has not yet been determined. We aimed to evaluate whether the presence and topography of CMBs are associated with altered volumes of gray matter (GMV) and white matter (WMV). Non-stroke and non-demented subjects were prospectively recruited from the I-Lan Longitudinal Aging Study. High-resolution 3-T MRI was performed to quantify total and regional WMV and GMV, including Alzheimer’s disease-susceptible areas. CMBs were assessed with susceptibility-weighted imaging. Six hundred and fifty-nine subjects (62.1 ± 8.3 years, 290 (44%) men) were included. Thirty-two (4.9%) subjects had strictly lobar CMBs (SL-CMBs) and 51 (7.7%) had deep or infratentorial CMBs (DI-CMBs). We observed an association between CMBs and WMV, independent of age, sex, and vascular risk factors; the direction of association depended on the location of the CMBs. The SL-CMB group had an increased total, frontal, and occipital WMV compared with the no-CMB group, which remained significant after adjusting for other CSVDs (WMH volumes and lacune numbers). In contrast, the DI-CMB group had a decreased occipital WMV compared to the no-CMB group. However, this significance disappeared after taking other CSVDs into consideration. Our results showed no relationship between CMBs and GMV. In conclusion, the increased WMV in non-stroke, non-demented subjects with SL-CMBs observed here provides insight into the early pathogenesis of SL-CMBs. This may be a result of increased water content or amyloid accumulation.


Cerebral microbleeds Brain volume White matter volume 



This study was funded by the Ministry of Science and Technology, Taiwan; the Taipei Veterans General Hospital, Taiwan; and the Veterans Affair Council of Taiwan (Chung: VGH V105C-055; MOST 104-2314-B-075-MY3; LK Chen: MOST 103-2633-B-400-002; MOST 105-3011-B-010-001; Veterans Affair Council of Taiwan 105-X2-2-1; Wang: NSC 101-2314-B-010; NSC 102-2314-B-010-051-MY2; Taipei VGH V104C-059).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional research committee (The Institutional Review Board of National Yang Ming University approved the present study) and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.


  1. 1.
    Wering DJ. Cerebral microbleeds: pathophysiology to clinical practice. 1st ed. Cambridge: Cambridge University Press; 2011.CrossRefGoogle Scholar
  2. 2.
    Yates PA, Villemagne VL, Ellis KA, Desmond PM, Masters CL, Rowe CC. Cerebral microbleeds: a review of clinical, genetic, and neuroimaging associations. Front Neurol. 2014;4:205.CrossRefGoogle Scholar
  3. 3.
    Wardlaw JM, Smith EE, Biessels GJ, Cordonnier C, Fazekas F, Frayne R, et al. Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol. 2013;12:822–38.CrossRefGoogle Scholar
  4. 4.
    Jokinen H, Lipsanen J, Schmidt R, Fazekas F, Gouw AA, van der Flier WM, et al. Brain atrophy accelerates cognitive decline in cerebral small vessel disease: the LADIS study. Neurology. 2012;78:1785–92.CrossRefGoogle Scholar
  5. 5.
    Nitkunan A, Lanfranconi S, Charlton RA, Barrick TR, Markus HS. Brain atrophy and cerebral small vessel disease: a prospective follow-up study. Stroke. 2011;42:133–8.CrossRefGoogle Scholar
  6. 6.
    Raji CA, Lopez OL, Kuller LH, Carmichael OT, Longstreth WT Jr, Gach HM, et al. White matter lesions and brain gray matter volume in cognitively normal elders. Neurobiol Aging. 2012;33:834.e7–16.CrossRefGoogle Scholar
  7. 7.
    Chung CP, Chou KH, Chen WT, Liu LK, Lee WJ, Chen LK, et al. Strictly lobar cerebral microbleeds are associated with cognitive impairment. Stroke. 2016;47:2497–502.CrossRefGoogle Scholar
  8. 8.
    Chung CP, Chou KH, Chen WT, Liu LK, Lee WJ, Chen LK, et al. Cerebral microbleeds are associated with physical frailty: a community-based study. Neurobiol Aging. 2016;44:143–50.CrossRefGoogle Scholar
  9. 9.
    Lee WJ, Liu LK, Peng LN, Lin MH, Chen LK, ILAS Research Group. Comparisons of sarcopenia defined by IWGS and EWGSOP criteria among older people: results from the I-Lan longitudinal aging study. J Am Med Dir Assoc. 2013;14:528.e1–7.Google Scholar
  10. 10.
    Liu HC, Lin KN, Teng EL, Wang SJ, Fuh JL, Guo NW, et al. Prevalence and subtypes of dementia in Taiwan: a community survey of 5297 individuals. J Am Geriatr Soc. 1995;43:144–9.CrossRefGoogle Scholar
  11. 11.
    Jones DW, Hall JE. Seventh report of the Joint National Committee on prevention, detection, evaluation, and treatment of high blood pressure and evidence from new hypertension trials. Hypertension. 2004;43:1–3.CrossRefGoogle Scholar
  12. 12.
    American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(Suppl 1):S62–9.CrossRefGoogle Scholar
  13. 13.
    Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2005;67:2089–100.CrossRefGoogle Scholar
  14. 14.
    Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage. 2007;38:95–113.CrossRefGoogle Scholar
  15. 15.
    Ashburner J, Friston KJ. Voxel-based morphometry--the methods. Neuroimage. 2000;11:805–21.CrossRefGoogle Scholar
  16. 16.
    Schmidt P, Gaser C, Arsic M, Buck D, Förschler A, Berthele A, et al. An automated tool for detection of FLAIR-hyperintense white-matter lesions in multiple sclerosis. Neuroimage. 2012;59:3774–83.CrossRefGoogle Scholar
  17. 17.
    Kim KW, MacFall JR, Payne ME. Classification of white matter lesions on magnetic resonance imaging in elderly persons. Biol Psychiatry. 2008;64:273–80.CrossRefGoogle Scholar
  18. 18.
    Greenberg SM, Vernooij MW, Cordonnier C, Viswanathan A, Al-Shahi Salman R, Warach S, et al. Cerebral microbleeds: a guide to detection and interpretation. Lancet Neurol. 2009;8:165–74.CrossRefGoogle Scholar
  19. 19.
    Gregoire SM, Chaudhary UJ, Brown MM, Yousry TA, Kallis C, Jäger HR, et al. The Microbleed Anatomical Rating Scale (MARS): reliability of a tool to map brain microbleeds. Neurology. 2009;73:1759–66.CrossRefGoogle Scholar
  20. 20.
    Stark DD, Bradley WG. Magnetic Resonance Imaging. 3rd ed. St. Louis: Mosby; 1999.Google Scholar
  21. 21.
    Jeerakathil T, Wolf PA, Beiser A, Hald JK, Au R, Kase CS, et al. Cerebral microbleeds: prevalence and associations with cardiovascular risk factors in the Framingham Study. Stroke. 2004;35:1831–5.CrossRefGoogle Scholar
  22. 22.
    Graff-Radford J, Simino J, Kantarci K, Mosley TH Jr, Griswold ME, Windham BG, et al. Neuroimaging correlates of cerebral microbleeds: the ARIC study (atherosclerosis risk in communities). Stroke. 2017;48:2964–72.CrossRefGoogle Scholar
  23. 23.
    Jellison BJ, Field AS, Medow J, Lazar M, Salamat MS, Alexander AL. Diffusion tensor imaging of cerebral white matter: a pictorial review of physics, fiber tract anatomy, and tumor imaging patterns. AJNR Am J Neuroradiol. 2004;25:356–69.PubMedGoogle Scholar
  24. 24.
    Wardlaw JM, Smith C, Dichgans M. Mechanisms of sporadic cerebral small vessel disease: insights from neuroimaging. Lancet Neurol. 2013;12:483–97.CrossRefGoogle Scholar
  25. 25.
    Farrall AJ, Wardlaw JM. Blood-brain barrier: ageing and microvascular disease--systematic review and meta-analysis. Neurobiol Aging. 2009;30:337–52.CrossRefGoogle Scholar
  26. 26.
    Martinez-Ramirez S, Pontes-Neto OM, Dumas AP, Auriel E, Halpin A, Quimby M, et al. Topography of dilated perivascular spaces in subjects from a memory clinic cohort. Neurology. 2013;80:1551–6.CrossRefGoogle Scholar
  27. 27.
    Poels MM, Vernooij MW, Ikram MA, Hofman A, Krestin GP, van der Lugt A, et al. Prevalence and risk factors of cerebral microbleeds: an update of the Rotterdam scan study. Stroke. 2010;41:S103–6.CrossRefGoogle Scholar
  28. 28.
    Yates PA, Sirisriro R, Villemagne VL, Farquharson S, Masters CL, Rowe CC, et al. Cerebral microhemorrhage and brain β-amyloid in aging and Alzheimer disease. Neurology. 2011;77:48–54.CrossRefGoogle Scholar
  29. 29.
    Tsai HH, Tsai LK, Chen YF, Tang SC, Lee BC, Yen RF, et al. Correlation of cerebral microbleed distribution to amyloid burden in patients with primary intracerebral hemorrhage. Sci Rep. 2017;7:44715.CrossRefGoogle Scholar
  30. 30.
    Yates PA, Desmond PM, Phal PM, Steward C, Szoeke C, Salvado O, et al. Incidence of cerebral microbleeds in preclinical Alzheimer disease. Neurology. 2014;82:1266–73.CrossRefGoogle Scholar
  31. 31.
    Taki Y, Thyreau B, Kinomura S, Sato K, Goto R, Kawashima R, et al. Correlations among brain gray matter volumes, age, gender, and hemisphere in healthy individuals. PLoS One. 2011;6:e22734.CrossRefGoogle Scholar
  32. 32.
    Beauchet O, Celle S, Roche F, Bartha R, Montero-Odasso M, Allali G, et al. Blood pressure levels and brain volume reduction: a systematic review and meta-analysis. J Hypertens. 2013;31:1502–16.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of NeurologyNational Yang Ming UniversityTaipeiTaiwan
  2. 2.Aging and Health Research CenterNational Yang Ming UniversityTaipeiTaiwan
  3. 3.Brain Research CenterNational Yang Ming UniversityTaipeiTaiwan
  4. 4.Department of Neurology, Neurological InstituteTaipei Veterans General HospitalTaipeiTaiwan
  5. 5.School of Medicine, Institute of NeuroscienceNational Yang Ming UniversityTaipeiTaiwan
  6. 6.Department of GerontologyNational Yang Ming UniversityTaipeiTaiwan
  7. 7.Center for Geriatric and GerontologyTaipei Veterans General HospitalTaipeiTaiwan
  8. 8.Institute of Public HealthNational Yang Ming UniversityTaipeiTaiwan
  9. 9.Department of Family MedicineTaipei Veterans General Hospital Yuanshan BranchYilanTaiwan
  10. 10.Department of NeurologyTaipei Veterans General HospitalTaipeiTaiwan

Personalised recommendations