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Brain Imaging and Behavior

, Volume 11, Issue 2, pp 503–511 | Cite as

The relationship between microvasculature in white matter hyperintensities and cognitive function

  • Jianzhong Sun
  • Xinfeng Yu
  • Yerfan Jiaerken
  • Ruirui Song
  • Peiyu Huang
  • Chao Wang
  • Lixia Yuan
  • Yingying Mao
  • Yang Guo
  • Hualiang Yu
  • Minming Zhang
Original Research

Abstract

White matter hyperintensities (WMHs) are associated with cognitive decline, but less is known about pathophysiology of cognitive decline in patients with WMHs. We investigated microvasculature and microstructure in WMHs using intravoxel incoherent motion (IVIM) and their associations with cognitive function. Thirty-two subjects with WMHs were enrolled in our study. Fast diffusion coefficient (D*), perfusion fraction (f) and slow diffusion coefficient (D) from IVIM model were compared between regions of WMHs (periventricular WMHs, PWMHs and deep WMHs, DWMHs) and surrounding normal white matter. Multivariate linear model was used to determine the independent factors associated with cognitive function assessed by the Mini Mental State Examination (MMSE) and the standardized coefficient (β) of factors was estimated. D* was significantly lower (4.95 × 10−3 mm2/s versus 8.36 × 10−3 mm2/s in PWMHs and 5.04 × 10−3 mm2/s versus 8.67 × 10−3 mm2/s in DWMHs, both P < 0.001), and f (14.64 % versus 12.01 % in PWMHs and 14.26 % versus 11.31 % in DWMHs, both P < 0.001) and D (1.02 × 10−3 mm2/s versus 0.73 × 10−3 mm2/s in PWMHs and 0.86 × 10−3 mm2/s versus 0.70 × 10−3 mm2/s in DWMHs, both P < 0.001) were significantly higher in WMHs. Only f in PWMHs was independently associated with MMSE (β = 0.443, P = 0.016). The decreased D* and increased D in WMHs were similar to previous findings. The increased f in PWMHs relating with better cognition provides the pathophysiological basis in understanding cognitive decline in patients with WMHs.

Keywords

Intravoxel incoherent motion Magnetic resonance imaging Diffusion Perfusion Cerebral small vessel disease 

Notes

Compliance with ethical standards

Funding

This study was funded by Zhejiang Provincial Natural Science Foundation of China (grant number: LZ14H180001), National Natural Science Foundation of China (grant number: 81271530) and Health and Family Planning Commission of Zhejiang Province (grant number: 2016154942).

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 and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.”

Supplementary material

11682_2016_9531_MOESM1_ESM.docx (230 kb)
ESM 1 (DOCX 229 kb)

References

  1. Alosco, M. L., Brickman, A. M., Spitznagel, M. B., Garcia, S. L., Narkhede, A., Griffith, E. Y., et al. (2013). Cerebral perfusion is associated with white matter hyperintensities in older adults with heart failure. Congestive Heart Failure, 19(4), E29–E34.PubMedPubMedCentralCrossRefGoogle Scholar
  2. Au, R., Massaro, J. M., Wolf, P. A., Young, M. E., Beiser, A., Seshadri, S., et al. (2006). Association of white matter hyperintensity volume with decreased cognitive functioning: the Framingham Heart Study. Archives of Neurology, 63(2), 246–250.PubMedCrossRefGoogle Scholar
  3. Brickman, A. M., Zahra, A., Muraskin, J., Steffener, J., Holland, C. M., Habeck, C., et al. (2009). Reduction in cerebral blood flow in areas appearing as white matter hyperintensities on magnetic resonance imaging. Psychiatry Research, 172(2), 117–120.PubMedPubMedCentralCrossRefGoogle Scholar
  4. Brown, W. R., & Thore, C. R. (2011). Review: cerebral microvascular pathology in ageing and neurodegeneration. Neuropathology and Applied Neurobiology, 37(1), 56–74.PubMedPubMedCentralCrossRefGoogle Scholar
  5. Covarrubias, D. J., Rosen, B. R., & Lev, M. H. (2004). Dynamic magnetic resonance perfusion imaging of brain tumors. The Oncologist, 9(5), 528–537.PubMedCrossRefGoogle Scholar
  6. De Groot, J. C., De Leeuw, F. E., Oudkerk, M., Van Gijn, J., Hofman, A., Jolles, J., et al. (2002). Periventricular cerebral white matter lesions predict rate of cognitive decline. Annals of Neurology, 52(3), 335–341.PubMedCrossRefGoogle Scholar
  7. De Leeuw, F.-E., De Groot, J., Bots, M., Witteman, J., Oudkerk, M., Hofman, A., et al. (2000). Carotid atherosclerosis and cerebral white matter lesions in a population based magnetic resonance imaging study. Journal of Neurology, 247(4), 291–296.PubMedCrossRefGoogle Scholar
  8. Debette, S., & Markus, H. (2010). The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ, 341, c3666.PubMedPubMedCentralCrossRefGoogle Scholar
  9. Dufouil, C., Godin, O., Chalmers, J., Coskun, O., MacMahon, S., Tzourio-Mazoyer, N., et al. (2009). Severe cerebral white matter hyperintensities predict severe cognitive decline in patients with cerebrovascular disease history. Stroke, 40(6), 2219–2221.PubMedCrossRefGoogle Scholar
  10. Fazekas, F., Chawluk, J. B., Alavi, A., Hurtig, H., & Zimmerman, R. (1987). MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJNR. American Journal of Neuroradiology, 149(2), 351–356.Google Scholar
  11. Fazekas, F., Kleinert, R., Offenbacher, H., Schmidt, R., Kleinert, G., Payer, F., et al. (1993). Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology, 43(9), 1683–1689.PubMedCrossRefGoogle Scholar
  12. Federau, C., Maeder, P., O’Brien, K., Browaeys, P., Meuli, R., & Hagmann, P. (2012). Quantitative measurement of brain perfusion with intravoxel incoherent motion MR imaging. Radiology, 265(3), 874–881.PubMedCrossRefGoogle Scholar
  13. Federau, C., O’Brien, K., Meuli, R., Hagmann, P., & Maeder, P. (2014). Measuring brain perfusion with intravoxel incoherent motion (IVIM): initial clinical experience. Journal of Magnetic Resonance Imaging, 39(3), 624–632.PubMedCrossRefGoogle Scholar
  14. Filley, C. M. (1998). The behavioral neurology of cerebral white matter. Neurology, 50(6), 1535–1540.PubMedCrossRefGoogle Scholar
  15. Fritzsche, K. H., Neher, P. F., Reicht, I., van Bruggen, T., Goch, C., Reisert, M., et al. (2012). MITK diffusion imaging. Methods of Information in Medicine, 51(5), 441.PubMedCrossRefGoogle Scholar
  16. Grueter, B. E., & Schulz, U. G. (2012). Age-related cerebral white matter disease (leukoaraiosis): a review. Postgraduate Medical Journal, 88(1036), 79–87.PubMedCrossRefGoogle Scholar
  17. Haller, S., Kovari, E., Herrmann, F. R., Cuvinciuc, V., Tomm, A.-M., Zulian, G. B., et al. (2013). Do brain T2/FLAIR white matter hyperintensities correspond to myelin loss in normal aging? A radiologic-neuropathologic correlation study. Acta Neuropathologica Communications, 1(1), 14.PubMedPubMedCentralCrossRefGoogle Scholar
  18. Helenius, J., Soinne, L., Salonen, O., Kaste, M., & Tatlisumak, T. (2002). Leukoaraiosis, ischemic stroke, and normal white matter on diffusion-weighted MRI. Stroke, 33(1), 45–50.PubMedCrossRefGoogle Scholar
  19. Hu, Y.-C., Yan, L.-F., Wu, L., Du, P., Chen, B.-Y., Wang, L., et al. (2014). Intravoxel incoherent motion diffusion-weighted MR imaging of gliomas: efficacy in preoperative grading. Scientific Reports, 4, 7208.PubMedPubMedCentralCrossRefGoogle Scholar
  20. Kennedy, K. M., & Raz, N. (2009). Pattern of normal age-related regional differences in white matter microstructure is modified by vascular risk. Brain Research, 1297, 41–56.PubMedPubMedCentralCrossRefGoogle Scholar
  21. Le Bihan, D. (2008). Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology, 249(3), 748–752.PubMedCrossRefGoogle Scholar
  22. Le Bihan, D., & Turner, R. (1992). The capillary network: a link between IVIM and classical perfusion. Magnetic Resonance in Medicine, 27(1), 171–178.PubMedCrossRefGoogle Scholar
  23. Le Bihan, D., Breton, E., Lallemand, D., Aubin, M., Vignaud, J., & Laval-Jeantet, M. (1988). Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology, 168(2), 497–505.PubMedCrossRefGoogle Scholar
  24. Maniega, S. M., Hernández, M. C. V., Clayden, J. D., Royle, N. A., Murray, C., Morris, Z., et al. (2015). White matter hyperintensities and normal-appearing white matter integrity in the aging brain. Neurobiology of Aging, 36(2), 909–918.PubMedPubMedCentralCrossRefGoogle Scholar
  25. Markus, H., Lythgoe, D., Ostegaard, L., O’sullivan, M., & Williams, S. (2000). Reduced cerebral blood flow in white matter in ischaemic leukoaraiosis demonstrated using quantitative exogenous contrast based perfusion MRI. Journal of Neurology, Neurosurgery and Psychiatry, 69(1), 48–53.PubMedPubMedCentralCrossRefGoogle Scholar
  26. Marstrand, J., Garde, E., Rostrup, E., Ring, P., Rosenbaum, S., Mortensen, E. L., et al. (2002). Cerebral perfusion and cerebrovascular reactivity are reduced in white matter hyperintensities. Stroke, 33(4), 972–976.PubMedCrossRefGoogle Scholar
  27. Moody, D. M., Brown, W. R., Challa, V. R., & Anderson, R. L. (1995). Periventricular venous collagenosis: association with leukoaraiosis. Radiology, 194(2), 469–476.PubMedCrossRefGoogle Scholar
  28. Moody, D. M., Thore, C. R., Anstrom, J. A., Challa, V. R., Langefeld, C. D., & Brown, W. R. (2004). Quantification of afferent vessels shows reduced brain vascular density in subjects with leukoaraiosis. Radiology, 233(3), 883–890.PubMedCrossRefGoogle Scholar
  29. O’Sullivan, M., Jones, D. K., Summers, P., Morris, R., Williams, S., & Markus, H. (2001). Evidence for cortical “disconnection” as a mechanism of age-related cognitive decline. Neurology, 57(4), 632–638.PubMedCrossRefGoogle Scholar
  30. Pantoni, L. (2010). Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurology, 9(7), 689–701.PubMedCrossRefGoogle Scholar
  31. Powers, W. J., Grubb, R. L., & Raichle, M. E. (1984). Physiological responses to focal cerebral ischemia in humans. Annals of Neurology, 16(5), 546–552.PubMedCrossRefGoogle Scholar
  32. Prins, N. D., & Scheltens, P. (2015). White matter hyperintensities, cognitive impairment and dementia: an update. Nature Reviews Neurology, 11(3), 157–165.PubMedCrossRefGoogle Scholar
  33. Sabri, O., Ringelstein, E.-B., Hellwig, D., Schneider, R., Schreckenberger, M., Kaiser, H.-J., et al. (1999). Neuropsychological impairment correlates with hypoperfusion and hypometabolism but not with severity of white matter lesions on MRI in patients with cerebral microangiopathy. Stroke, 30(3), 556–566.PubMedCrossRefGoogle Scholar
  34. Schmidt, P., Gaser, C., Arsic, M., Buck, D., Förschler, A., Berthele, A., et al. (2012). An automated tool for detection of FLAIR-hyperintense white-matter lesions in multiple sclerosis. NeuroImage, 59(4), 3774–3783.PubMedCrossRefGoogle Scholar
  35. Taheri, S., Gasparovic, C., Huisa, B. N., Adair, J. C., Edmonds, E., Prestopnik, J., et al. (2011). Blood–brain barrier permeability abnormalities in vascular cognitive impairment. Stroke, 42(8), 2158–2163.PubMedPubMedCentralCrossRefGoogle Scholar
  36. Taylor, W. D., Payne, M. E., Krishnan, K. R. R., Wagner, H. R., Provenzale, J. M., Steffens, D. C., et al. (2001). Evidence of white matter tract disruption in MRI hyperintensities. Biological Psychiatry, 50(3), 179–183.PubMedCrossRefGoogle Scholar
  37. Tuladhar, A. M., Reid, A. T., Shumskaya, E., de Laat, K. F., van Norden, A. G., van Dijk, E. J., et al. (2015). Relationship between white matter hyperintensities, cortical thickness, and cognition. Stroke, 46(2), 425–432.PubMedCrossRefGoogle Scholar
  38. Wardlaw, J. M., Smith, E. E., Biessels, G. J., Cordonnier, C., Fazekas, F., Frayne, R., et al. (2013). Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurology, 12(8), 822–838.PubMedPubMedCentralCrossRefGoogle Scholar
  39. Wirestam, R., Borg, M., Brockstedt, S., Lindgren, A., Holtås, S., & Ståhlberg, F. (2001). Perfusion-related parameters in intravoxel incoherent motion MR imaging compared with CBV and CBF measured by dynamic susceptibility-contrast MR technique. Acta Radiologica, 42(2), 123–128.PubMedCrossRefGoogle Scholar
  40. Wu, W.-C., Chen, Y.-F., Tseng, H.-M., & Yang, S.-C. (2015). Caveat of measuring perfusion indexes using intravoxel incoherent motion magnetic resonance imaging in the human brain. European Radiology, 25(8), 2485–2492.PubMedPubMedCentralCrossRefGoogle Scholar
  41. Wurnig, M. C., Donati, O. F., Ulbrich, E., Filli, L., Kenkel, D., Thoeny, H. C., et al. (2015). Systematic analysis of the intravoxel incoherent motion threshold separating perfusion and diffusion effects: proposal of a standardized algorithm. Magnetic Resonance in Medicine, 74(5), 1414–1422.PubMedCrossRefGoogle Scholar
  42. Yamada, K., Sakai, K., Owada, K., Mineura, K., & Nishimura, T. (2010). Cerebral white matter lesions may be partially reversible in patients with carotid artery stenosis. AJNR. American Journal of Neuroradiology, 31(7), 1350–1352.PubMedCrossRefGoogle Scholar
  43. Yamaji, S., Ishii, K., Sasaki, M., Imamura, T., Kitagaki, H., Sakamoto, S., et al. (1997). Changes in cerebral blood flow and oxygen metabolism related to magnetic resonance imaging white matter hyperintensities in Alzheimer’s disease. Journal of Nuclear Medicine, 38(9), 1471–1474.PubMedGoogle Scholar
  44. Yan, S., Wan, J., Zhang, X., Tong, L., Zhao, S., Sun, J., et al. (2014). Increased visibility of deep medullary veins in leukoaraiosis: a 3-T MRI study. Frontiers in Aging Neuroscience, 6, 144.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Department of RadiologyThe 2nd Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
  2. 2.Department of Biomedical Engineering and Instrument Science, Key Laboratory for Biomedical Engineering of Education Ministry of ChinaZhejiang UniversityHangzhouChina
  3. 3.Department of NeurologyThe 2nd Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina
  4. 4.Department of PsychiatryThe 2nd Affiliated Hospital of Zhejiang University, School of MedicineHangzhouChina

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