White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance

Luca Melazzini¹, Clare E Mackay², Valentina Bordin³, Sana Suri⁴, Enikő Zsoldos⁵, Nicola Filippini⁶, Abda Mahmood⁷, Vaanathi Sundaresan⁸, Marina Codari⁹, Eugene Duff¹⁰, Archana Singh-Manoux¹¹, Mika Kivimäki¹², Klaus P Ebmeier⁷, Mark Jenkinson⁸, Francesco Sardanelli¹³, Ludovica Griffanti¹⁴

Affiliations

¹ Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. Electronic address: luca.melazzini@unimi.it.
² Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK.
³ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
⁴ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁵ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁶ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.
⁷ Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁸ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
⁹ Department of Radiology, Stanford University School of Medicine, Stanford, USA.
¹⁰ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Paediatrics, University of Oxford, Oxford, UK.
¹¹ INSERM U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Paris, France; Department of Epidemiology and Public Health, University College London, London, UK.
¹² Department of Epidemiology and Public Health, University College London, London, UK.
¹³ Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Department of Radiology, IRCCS Policlinico San Donato, Milan, Italy.
¹⁴ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.

PMID: 33743476
PMCID: PMC7995650
DOI: 10.1016/j.nicl.2021.102616

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance

Luca Melazzini et al. Neuroimage Clin. 2021.

. 2021:30:102616.

doi: 10.1016/j.nicl.2021.102616. Epub 2021 Mar 7.

Authors

Affiliations

¹ Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK. Electronic address: luca.melazzini@unimi.it.
² Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK.
³ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.
⁴ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁵ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK; Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁶ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.
⁷ Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK.
⁸ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
⁹ Department of Radiology, Stanford University School of Medicine, Stanford, USA.
¹⁰ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Paediatrics, University of Oxford, Oxford, UK.
¹¹ INSERM U1153, Epidemiology of Ageing and Neurodegenerative Diseases, Université de Paris, Paris, France; Department of Epidemiology and Public Health, University College London, London, UK.
¹² Department of Epidemiology and Public Health, University College London, London, UK.
¹³ Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy; Department of Radiology, IRCCS Policlinico San Donato, Milan, Italy.
¹⁴ Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Oxford, UK.

PMID: 33743476
PMCID: PMC7995650
DOI: 10.1016/j.nicl.2021.102616

Abstract

White matter hyperintensities (WMHs) on T₂-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T₁-weighted images (T₁w) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and T₁w-hypointense/nonT₁w-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular T₁w-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in T₁w reveals specific associations with cognitive performance.

Keywords: Aging; Cerebral small vessel diseases; Cognition; Magnetic resonance imaging; White matter.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

**Fig. 1**
The left panel shows the native images (FLAIR and T₁-weighted) and image processing outputs (WMH total and WMH sub-classes) for a subject drawn from the study sample. The right panel shows a colour-coded detailed view of the four sub-classes of WMHs.

**Fig. 2**
Diagram representing the potential evolution of WMHs over time. WMHs, white matter hyperintensity.

See this image and copyright information in PMC

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White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance

Affiliations

White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Medical

Research Materials