European Radiology

, Volume 29, Issue 12, pp 7027–7036 | Cite as

Structural and functional MRI correlates of T2 hyperintensities of brain white matter in young neurologically asymptomatic adults

  • Miloš KeřkovskýEmail author
  • Jakub Stulík
  • Marek Dostál
  • Matyáš Kuhn
  • Jan Lošák
  • Petra Praksová
  • Monika Hulová
  • Josef Bednařík
  • Andrea Šprláková-Puková
  • Marek Mechl



Although white matter hyperintensities (WMHs) are quite commonly found incidentally, their aetiology, structural characteristics, and functional consequences are not entirely known. The purpose of this study was to quantify WMHs in a sample of young, neurologically asymptomatic adults and evaluate the structural and functional correlations of lesion load with changes in brain volume, diffusivity, and functional connectivity.


MRI brain scan using multimodal protocol was performed in 60 neurologically asymptomatic volunteers (21 men, 39 women, mean age 34.5 years). WMHs were manually segmented in 3D FLAIR images and counted automatically. The number and volume of WMHs were correlated with brain volume, resting-state functional MRI (rs-fMRI), and diffusion tensor imaging (DTI) data. Diffusion parameters measured within WMHs and normally appearing white matter (NAWM) were compared.


At least 1 lesion was found in 40 (67%) subjects, median incidence was 1 lesion (interquartile range [IQR] = 4.5), and median volume was 86.82 (IQR = 227.23) mm3. Neither number nor volume of WMHs correlated significantly with total brain volume or volumes of white and grey matter. Mean diffusivity values within WMHs were significantly higher compared with those for NAWM, but none of the diffusion parameters of NAWM were significantly correlated with WMH load. Both the number and volume of WMHs were correlated with the changes of functional connectivity between several regions of the brain, mostly decreased connectivity of the cerebellum.


WMHs are commonly found even in young, neurologically asymptomatic adults. Their presence is not associated with brain atrophy or global changes of diffusivity, but the increasing number and volume of these lesions correlate with changes of brain connectivity, and especially that of the cerebellum.

Key Points

White matter hyperintensities (WMHs) are commonly found in young, neurologically asymptomatic adults.

The presence of WMHs is not associated with brain atrophy or global changes of white matter diffusivity.

The increasing number and volume of WMHs correlate with changes of brain connectivity, and especially with that of the cerebellum.


White matter Healthy volunteers Diffusion tensor imaging Functional magnetic resonance imaging 



Axial diffusivity


Fractional anisotropy


Fast field echo


Fluid attenuation inversion recovery


Interclass correlation coefficient


Interquartile range


Mean diffusivity


Multiple sclerosis


Normally appearing white matter


Radial diffusivity


Resting-state functional MRI


Tract-based spatial statistics


Echo time


Repetition time


Turbo spin echo


White matter


White matter hyperintensities



This study was supported by grant project AZV-15-32133A of the Czech Health Research Council and by funds from the Faculty of Medicine MU to junior researcher (M. Keřkovský).


This study has received funding by the Czech Health Research Council and by the Faculty of Medicine MU.

Compliance with ethical standards


The scientific guarantor of this publication is Assoc. Prof. Marek Mechl, M.D., Ph.D., MBA.

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 obtained from all subjects in this study.

Ethical approval

Institutional Review Board approval was obtained.


• Prospective

• Cross-sectional study

• Performed at one institution

Supplementary material

330_2019_6268_MOESM1_ESM.docx (1.3 mb)
ESM 1 (DOCX 1350 kb)


  1. 1.
    Longstreth WT Jr, Manolio TA, Arnold A et al (1996) Clinical correlates of white matter findings on cranial magnetic resonance imaging of 3301 elderly people. The Cardiovascular Health Study. Stroke 27:1274–1282CrossRefGoogle Scholar
  2. 2.
    Katzman GL, Dagher AP, Patronas NJ (1999) Incidental findings on brain magnetic resonance imaging from 1000 asymptomatic volunteers. JAMA 282:36–39CrossRefGoogle Scholar
  3. 3.
    de Groot JC, de Leeuw FE, Oudkerk M, Hofman A, Jolles J, Breteler MM (2001) Cerebral white matter lesions and subjective cognitive dysfunction: the Rotterdam Scan Study. Neurology 56:1539–1545CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Hopkins RO, Beck CJ, Burnett DL, Weaver LK, Victoroff J, Bigler ED (2006) Prevalence of white matter hyperintensities in a young healthy population. J Neuroimaging 16:243–251CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Fazekas F (1989) Magnetic resonance signal abnormalities in asymptomatic individuals: their incidence and functional correlates. Eur Neurol 29:164–168CrossRefGoogle Scholar
  6. 6.
    Enzinger C, Smith S, Fazekas F et al (2006) Lesion probability maps of white matter hyperintensities in elderly individuals: results of the Austrian stroke prevention study. J Neurol 253:1064–1070CrossRefGoogle Scholar
  7. 7.
    van Swieten JC, Geyskes GG, Derix MM et al (1991) Hypertension in the elderly is associated with white matter lesions and cognitive decline. Ann Neurol 30:825–830CrossRefGoogle Scholar
  8. 8.
    Hirono N, Kitagaki H, Kazui H, Hashimoto M, Mori E (2000) Impact of white matter changes on clinical manifestation of Alzheimer’s disease: a quantitative study. Stroke 31:2182–2188CrossRefGoogle Scholar
  9. 9.
    van den Berg E, Geerlings MI, Biessels GJ, Nederkoorn PJ, Kloppenborg RP (2018) White matter hyperintensities and cognition in mild cognitive impairment and Alzheimer’s disease: a domain-specific meta-analysis. J Alzheimers Dis.
  10. 10.
    Piccini P, Pavese N, Canapicchi R et al (1995) White matter hyperintensities in Parkinson’s disease. Clinical correlations. Arch Neurol 52:191–194CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Brown FW, Lewine RJ, Hudgins PA, Risch SC (1992) White matter hyperintensity signals in psychiatric and nonpsychiatric subjects. Am J Psychiatry 149:620–625CrossRefPubMedPubMedCentralGoogle Scholar
  12. 12.
    Thompson AJ, Banwell BL, Barkhof F et al (2017) Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 17:162–173CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Bartko JJ (1966) The intraclass correlation coefficient as a measure of reliability. Psychol Rep 19:3–11CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Smith SM, Zhang Y, Jenkinson M et al (2002) Accurate, robust and automated longitudinal and cross-sectional brain change analysis. Neuroimage 17:479–489CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Smith SM, Jenkinson M, Woolrich MW et al (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23:S208–S219CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Battaglini M, Jenkinson M, De Stefano N (2012) Evaluating and reducing the impact of white matter lesions on brain volume measurements. Hum Brain Mapp 33:2062–2071CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    Whitfield-Gabrieli S, Nieto-Castanon A (2012) Conn: a functional connectivity toolbox for correlated and anticorrelated brain networks. Brain Connect 2:125–141CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    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 70:9–14CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Wen W, Sachdev PS, Li JJ, Chen X, Anstey KJ (2009) White matter hyperintensities in the forties: their prevalence and topography in an epidemiological sample aged 44–48. Hum Brain Mapp 30:1155–1167CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Saba L, Lucatelli P, Anzidei M, di Martino M, Suri JS, Montisci R (2018) Volumetric distribution of the white matter hyper-intensities in subject with mild to severe carotid artery stenosis: does the side play a role? J Stroke Cerebrovasc Dis.
  21. 21.
    Ataç Uçar C, Güneş HN, Sencer Demircan C, Çokal BG, Keskin Güler S, Yoldaş TK (2017) Cardiovascular risk factors and white matter hyperintensities in patients with migraine without aura. Agri 29:157–161PubMedGoogle Scholar
  22. 22.
    Boutet C, Rouffiange-Leclair L, Schneider F, Camdessanché JP, Antoine JC, Barral FG (2016) Visual assessment of age-related white matter hyperintensities using FLAIR images at 3 T: inter- and intra-rater agreement. Neurodegener Dis 16:279–283CrossRefGoogle Scholar
  23. 23.
    Tully PJ, Qchiqach S, Pereira E, Debette S, Mazoyer B, Tzourio C (2017) Development and validation of a priori risk model for extensive white matter lesions in people age 65 years or older: the Dijon MRI study. BMJ Open 7:e018328CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Gramsch C, Nensa F, Kastrup O et al (2015) Diagnostic value of 3D fluid attenuated inversion recovery sequence in multiple sclerosis. Acta Radiol 56:622–627CrossRefPubMedPubMedCentralGoogle Scholar
  25. 25.
    Patzig M, Burke M, Brückmann H, Fesl G (2014) Comparison of 3D cube FLAIR with 2D FLAIR for multiple sclerosis imaging at 3 Tesla. Rofo 186:484–488PubMedGoogle Scholar
  26. 26.
    Paniagua Bravo Á, Sánchez Hernández JJ, Ibáñez Sanz L, Alba de Cáceres I, Crespo San José JL, García-Castaño Gandariaga B (2014) A comparative MRI study for white matter hyperintensities detection: 2D-FLAIR, FSE PD 2D, 3D-FLAIR and FLAIR MIP. Br J Radiol 87:20130360CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Wen W, Sachdev PS, Chen X, Anstey K (2006) Gray matter reduction is correlated with white matter hyperintensity volume: a voxel-based morphometric study in a large epidemiological sample. Neuroimage 29:1031–1039CrossRefGoogle Scholar
  28. 28.
    Tiehuis AM, Vincken KL, Mali WP et al (2008) Automated and visual scoring methods of cerebral white matter hyperintensities: relation with age and cognitive function. Cerebrovasc Dis 25:59–66CrossRefGoogle Scholar
  29. 29.
    Kim JH, Hwang KJ, Kim JH, Lee YH, Rhee HY, Park KC (2011) Regional white matter hyperintensities in normal aging, single domain amnestic mild cognitive impairment, and mild Alzheimer’s disease. J Clin Neurosci 18:1101–1106CrossRefGoogle Scholar
  30. 30.
    Awad IA, Spetzler RF, Hodak JA, Awad CA, Carey R (1986) Incidental subcortical lesions identified on magnetic resonance imaging in the elderly. I. Correlation with age and cerebrovascular risk factors. Stroke 17:1084–1089CrossRefGoogle Scholar
  31. 31.
    Habes M, Erus G, Toledo JB et al (2016) White matter hyperintensities and imaging patterns of brain ageing in the general population. Brain 139:1164–1179CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Okuda DT, Mowry EM, Beheshtian A et al (2009) Incidental MRI anomalies suggestive of multiple sclerosis: the radiologically isolated syndrome. Neurology 72:800–805CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Forslin Y, Granberg T, Jumah AA et al (2016) Incidence of radiologically isolated syndrome: a population-based study. AJNR Am J Neuroradiol 37:1017–1022CrossRefPubMedPubMedCentralGoogle Scholar
  34. 34.
    Maniega SM, Valdés Hernández MC, Clayden JD et al (2015) White matter hyperintensities and normal-appearing white matter integrity in the aging brain. Neurobiol Aging 36:909–918CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Fazekas F, Kleinert R, Offenbacher H et al (1993) Pathologic correlates of incidental MRI white matter signal hyperintensities. Neurology 43:1683–1689CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Gunning-Dixon FM, Brickman AM, Cheng JC, Alexopoulos GS (2009) Aging of cerebral white matter: a review of MRI findings. Int J Geriatr Psychiatry 24:109–117CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Godin O, Maillard P, Crivello F et al (2009) Association of white-matter lesions with brain atrophy markers: the three-city Dijon MRI study. Cerebrovasc Dis 28:177–184CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Glickstein M (1992) The cerebellum and motor learning. Curr Opin Neurobiol 2:802–806CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Daum I, Snitz BE, Ackermann H (2001) Neuropsychological deficits in cerebellar syndromes. Int Rev Psychiatry 13:268–275CrossRefGoogle Scholar
  40. 40.
    Bellebaum C, Daum I (2007) Cerebellar involvement in executive control. Cerebellum 6:184–192CrossRefPubMedPubMedCentralGoogle Scholar
  41. 41.
    Sachdev PS, Wen W, Christensen H, Jorm AF (2005) White matter hyperintensities are related to physical disability and poor motor function. J Neurol Neurosurg Psychiatry 76:362–367CrossRefPubMedPubMedCentralGoogle Scholar
  42. 42.
    Shi L, Miao X, Lou W et al (2017) The spatial associations of cerebral blood flow and spontaneous brain activities with white matter hyperintensities-an exploratory study using multimodal magnetic resonance imaging. Front Neurol 8:593CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    De Marco M, Manca R, Mitolo M, Venneri A (2017) White matter hyperintensity load modulates brain morphometry and brain connectivity in healthy adults: a neuroplastic mechanism? Neural Plast 2017:4050536CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Miloš Keřkovský
    • 1
    Email author
  • Jakub Stulík
    • 1
  • Marek Dostál
    • 1
    • 2
  • Matyáš Kuhn
    • 3
    • 4
  • Jan Lošák
    • 3
  • Petra Praksová
    • 5
  • Monika Hulová
    • 5
  • Josef Bednařík
    • 5
  • Andrea Šprláková-Puková
    • 1
  • Marek Mechl
    • 1
  1. 1.Department of Radiology and Nuclear MedicineThe University Hospital Brno and Masaryk UniversityBrnoCzech Republic
  2. 2.Department of BiophysicsMasaryk UniversityBrnoCzech Republic
  3. 3.Department of PsychiatryThe University Hospital Brno and Masaryk UniversityBrnoCzech Republic
  4. 4.Behavioural and Social NeuroscienceCEITEC MUBrnoCzech Republic
  5. 5.Department of NeurologyThe University Hospital Brno and Masaryk UniversityBrnoCzech Republic

Personalised recommendations