Skip to main content

Advertisement

SpringerLink
Log in

Myelin loss in white matter hyperintensities and normal-appearing white matter of cognitively impaired patients: a quantitative synthetic magnetic resonance imaging study

  • Neuro
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

White matter hyperintensities (WMHs) are implicated in the etiology of dementia. The underlying pathology of WMHs involves myelin and axonal loss due to chronic ischemia. We investigated myelin loss in WMHs and normal-appearing white matter (NAWM) in patients with various degrees of cognitive impairment using quantitative synthetic magnetic resonance imaging (MRI).

Methods

We studied 99 consecutive patients with cognitive complaints who underwent 3 T brain MRI between July 2016 and August 2017. Myelin partial volume maps were generated with synthetic MRI. Region-of-interest–based analysis was performed on these maps to compare the myelin partial volumes of NAWM and periventricular and deep WMHs. The effects of myelin partial volume of NAWMs on clinical cognitive function were evaluated using multivariate linear regression analysis.

Results

WMHs were present in 30.3% of patients. Myelin partial volume in NAWM was lower in patients with WMHs than in those without (37.5 ± 2.7% vs. 39.9 ± 2.4%, p < 0.001). In patients with WMHs, myelin partial volume was highest in NAWMs (median [interquartile range], 37.2% [35.5–39.0%]), followed by deep WMHs (7.2% [3.2–10.5%]) and periventricular WMHs (2.1% [1.1–3.9%], p < 0.001). After adjusting for sex and education years, myelin partial volume in NAWMs was associated with the Clinical Dementia Rating Scale Sum of Box (β = -0.189 [95% CI, -0.380 to -0.012], p = 0.031).

Conclusion

Myelin loss occurs in both NAWM and WMHs of cognitively impaired patients. Synthetic MRI-based myelin quantification may be a useful imaging marker of cognitive dysfunction in patients with cognitive complaints.

Key Points

• Quantitative synthetic MRI allows simultaneous acquisition of conventional MRI and myelin quantification without additional scanning time.

• Normal-appearing and hyperintense white matter demonstrate myelin loss in cognitively impaired patients.

• This myelin loss partially explains cognitive dysfunction in patients with cognitive complaints.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

Abbreviations

CDR-SB:

Clinical Dementia Rating Scale Sum of Boxes

GMF:

Gray matter fraction

ICV:

Intracranial volume

MMSE:

Mini-Mental Status Examination

NAWM:

Normal-appearing white matter

WMF:

White matter fraction

WMHs:

White matter hyperintensities

References

  1. de Leeuw FE, de Groot JC, Achten E et al (2001) Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam Scan Study. J Neurol Neurosurg Psychiatry 70:9–14

    Article  PubMed  PubMed Central  Google Scholar 

  2. Debette S, Markus HS (2010) The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and meta-analysis. BMJ 341:c3666

    Article  PubMed  PubMed Central  Google Scholar 

  3. Prins ND, Scheltens P (2015) White matter hyperintensities, cognitive impairment and dementia: an update. Nat Rev Neurol 11:157–165

    Article  PubMed  Google Scholar 

  4. Gouw AA, Seewann A, van der Flier WM et al (2011) Heterogeneity of small vessel disease: a systematic review of MRI and histopathology correlations. J Neurol Neurosurg Psychiatry 82:126–135

    Article  PubMed  Google Scholar 

  5. Fernando MS, O'Brien JT, Perry RH et al (2004) Comparison of the pathology of cerebral white matter with post-mortem magnetic resonance imaging (MRI) in the elderly brain. Neuropathol Appl Neurobiol 30:385–395

    Article  CAS  PubMed  Google Scholar 

  6. Bronge L, Bogdanovic N, Wahlund LO (2002) Postmortem MRI and histopathology of white matter changes in Alzheimer brains. A quantitative, comparative study. Dement Geriatr Cogn Disord 13:205–212

    Article  CAS  PubMed  Google Scholar 

  7. Bartzokis G (2004) Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer's disease. Neurobiol Aging 25:5–18 author reply 49-62

    Article  CAS  PubMed  Google Scholar 

  8. Dean DC 3rd, Hurley SA, Kecskemeti SR et al (2017) Association of amyloid pathology with myelin alteration in preclinical Alzheimer disease. JAMA Neurol 74:41–49

    Article  PubMed  PubMed Central  Google Scholar 

  9. Fazekas F, Ropele S, Enzinger C et al (2005) MTI of white matter hyperintensities. Brain 128:2926–2932

    Article  PubMed  Google Scholar 

  10. O'Sullivan M, Summers PE, Jones DK, Jarosz JM, Williams SC, Markus HS (2001) Normal-appearing white matter in ischemic leukoaraiosis: a diffusion tensor MRI study. Neurology 57:2307–2310

    Article  CAS  PubMed  Google Scholar 

  11. Kavroulakis E, Simos PG, Kalaitzakis G et al (2018) Myelin content changes in probable Alzheimer's disease and mild cognitive impairment: associations with age and severity of neuropsychiatric impairment. J Magn Reson Imaging 47:1359–1372

    Article  PubMed  Google Scholar 

  12. Warntjes JB, Leinhard OD, West J, Lundberg P (2008) Rapid magnetic resonance quantification on the brain: optimization for clinical usage. Magn Reson Med 60:320–329

    Article  CAS  PubMed  Google Scholar 

  13. Wardlaw JM, Smith EE, Biessels GJ et al (2013) Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurol 12:822–838

    Article  PubMed  PubMed Central  Google Scholar 

  14. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA (1987) MR signal abnormalities at 1.5 T in Alzheimer's dementia and normal aging. AJR Am J Roentgenol 149:351–356

    Article  CAS  PubMed  Google Scholar 

  15. Hagiwara A, Warntjes M, Hori M et al (2017) SyMRI of the brain: rapid quantification of relaxation rates and proton density, with synthetic MRI, automatic brain segmentation, and myelin measurement. Invest Radiol 52:647–657

    Article  PubMed  PubMed Central  Google Scholar 

  16. Warntjes M, Engström M, Tisell A, Lundberg P (2016) Modeling the presence of myelin and edema in the brain based on multi-parametric quantitative MRI. Front Neurol 7:16

    Article  PubMed  PubMed Central  Google Scholar 

  17. West J, Warntjes JB, Lundberg P (2012) Novel whole brain segmentation and volume estimation using quantitative MRI. Eur Radiol 22:998–1007

    Article  CAS  PubMed  Google Scholar 

  18. Pantoni L, Simoni M (2003) Pathophysiology of cerebral small vessels in vascular cognitive impairment. Int Psychogeriatr 15(Suppl 1):59–65

    Article  PubMed  Google Scholar 

  19. Fazekas F, Kleinert R, Offenbacher H et al (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43:1683–1689

    Article  CAS  PubMed  Google Scholar 

  20. Simpson JE, Ince PG, Higham CE et al (2007) Microglial activation in white matter lesions and nonlesional white matter of ageing brains. Neuropathol Appl Neurobiol 33:670–683

    Article  CAS  PubMed  Google Scholar 

  21. Maillard P, Fletcher E, Harvey D et al (2011) White matter hyperintensity penumbra. Stroke 42:1917–1922

    Article  PubMed  PubMed Central  Google Scholar 

  22. Vavasour IM, Laule C, Li DK, Traboulsee AL, MacKay AL (2011) Is the magnetization transfer ratio a marker for myelin in multiple sclerosis? J Magn Reson Imaging 33:713–718

    Article  PubMed  Google Scholar 

  23. Firbank MJ, Minett T, O'Brien JT (2003) Changes in DWI and MRS associated with white matter hyperintensities in elderly subjects. Neurology 61:950–954

    Article  CAS  PubMed  Google Scholar 

  24. Grueter BE, Schulz UG (2012) Age-related cerebral white matter disease (leukoaraiosis): a review. Postgrad Med J 88:79–87

    Article  PubMed  Google Scholar 

  25. Erten-Lyons D, Woltjer R, Kaye J et al (2013) Neuropathologic basis of white matter hyperintensity accumulation with advanced age. Neurology 81:977–983

    Article  PubMed  PubMed Central  Google Scholar 

  26. Muñoz Maniega S, Chappell FM, Valdés Hernández MC et al (2017) Integrity of normal-appearing white matter: influence of age, visible lesion burden and hypertension in patients with small-vessel disease. J Cereb Blood Flow Metab 37:644–656

  27. Gouw AA, Seewann A, Vrenken H et al (2008) Heterogeneity of white matter hyperintensities in Alzheimer's disease: post-mortem quantitative MRI and neuropathology. Brain 131:3286–3298

    Article  CAS  PubMed  Google Scholar 

  28. Wharton SB, Simpson JE, Brayne C, Ince PG (2015) Age-associated white matter lesions: the MRC cognitive function and ageing study. Brain Pathol 25:35–43

    Article  PubMed  Google Scholar 

  29. O'Sullivan M, Morris RG, Huckstep B, Jones DK, Williams SC, Markus HS (2004) Diffusion tensor MRI correlates with executive dysfunction in patients with ischaemic leukoaraiosis. J Neurol Neurosurg Psychiatry 75:441–447

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Snaidero N, Simons M (2014) Myelination at a glance. J Cell Sci 127:2999–3004

    Article  CAS  PubMed  Google Scholar 

  31. Sun J, Zhou H, Bai F, Zhang Z, Ren Q (2017) Remyelination: a potential therapeutic strategy for Alzheimer's disease? J Alzheimers Dis 58:597–612

    Article  CAS  PubMed  Google Scholar 

  32. Cha MY, Kwon YW, Ahn HS et al (2017) Protein-induced pluripotent stem cells ameliorate cognitive dysfunction and reduce Abeta deposition in a mouse model of Alzheimer's disease. Stem Cells Transl Med 6:293–305

    Article  CAS  PubMed  Google Scholar 

  33. Piao J, Major T, Auyeung G et al (2015) Human embryonic stem cell-derived oligodendrocyte progenitors remyelinate the brain and rescue behavioral deficits following radiation. Cell Stem Cell 16:198–210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Alonso-Ortiz E, Levesque IR, Pike GB (2015) MRI-based myelin water imaging: a technical review. Magn Reson Med 73:70–81

    Article  CAS  PubMed  Google Scholar 

  35. O'Bryant SE, Waring SC, Cullum CM et al (2008) Staging dementia using clinical dementia rating scale sum of boxes scores: a Texas Alzheimer's research consortium study. Arch Neurol 65:1091–1095

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

This research was presented as a scientific exhibit at the ECR 2018 (C-1637) and awarded a Certificate of Merit.

Funding

This research was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (no.2017R1A2B4010634) and a grant of the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number HI18C1038).

Author information

Authors and Affiliations

  1. Department of Radiology, Konkuk University Medical Center, Konkuk University School of Medicine, 120-1 Neungdong-ro, Gwangjin-gu, Seoul, 05030, Republic of Korea

    Mina Park & Won-Jin Moon

  2. Department of Radiology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Republic of Korea

    Mina Park

  3. Department of Neurology, Konkuk University Medical Center, Konkuk University School of Medicine, 120-1 Neungdong-ro, Gwangjin-gu, Seoul, 05030, Republic of Korea

    Yeonsil Moon & Seol-Heui Han

  4. Department of Radiology, School of Medicine, Daegu Catholic University, Gyeongsan, Gyeongsangbuk-do, South Korea

    Ho Kyun Kim

Authors
  1. Mina Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yeonsil Moon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seol-Heui Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ho Kyun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Won-Jin Moon
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Won-Jin Moon.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Won-Jin Moon.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Cross-sectional study

• Performed at one institution

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Electronic supplementary material

ESM 1

(DOCX 10194 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Park, M., Moon, Y., Han, SH. et al. Myelin loss in white matter hyperintensities and normal-appearing white matter of cognitively impaired patients: a quantitative synthetic magnetic resonance imaging study. Eur Radiol 29, 4914–4921 (2019). https://doi.org/10.1007/s00330-018-5836-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-018-5836-x

Keywords

Search

Navigation