Fluid-attenuated inversion recovery magnetic resonance imaging textural features as sensitive markers of white matter damage in midlife adults.
Ritchie, Craig W
Markus, Hugh S
Oxford University Press (OUP)
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Dounavi, M., Low, A., Muniz-Terrera, G., Ritchie, K., Ritchie, C. W., Su, L., Markus, H. S., & et al. (2022). Fluid-attenuated inversion recovery magnetic resonance imaging textural features as sensitive markers of white matter damage in midlife adults.. Brain Commun, 4 (3) https://doi.org/10.1093/braincomms/fcac116
White matter hyperintensities are common radiological findings in ageing and a typical manifestation of cerebral small vessel disease. White matter hyperintensity burden is evaluated by quantifying their volume; however, subtle changes in the white matter may not be captured by white matter hyperintensity volumetry. In this cross-sectional study, we investigated whether magnetic resonance imaging texture of both white matter hyperintensities and normal appearing white matter was associated with reaction time, white matter hyperintensity volume and dementia risk in a midlife cognitively normal population. Data from 183 cognitively healthy midlife adults from the PREVENT-Dementia study (mean age 51.9 ± 5.4; 70% females) were analysed. White matter hyperintensities were segmented from 3 Tesla fluid-attenuated inversion recovery scans using a semi-automated approach. The fluid-attenuated inversion recovery images were bias field corrected and textural features (intensity mean and standard deviation, contrast, energy, entropy, homogeneity) were calculated in white matter hyperintensities and normal appearing white matter based on generated textural maps. Textural features were analysed for associations with white matter hyperintensity volume, reaction time and the Cardiovascular Risk Factors, Aging and Dementia risk score using linear regression models adjusting for age and sex. The extent of normal appearing white matter surrounding white matter hyperintensities demonstrating similar textural associations to white matter hyperintensities was further investigated by defining layers surrounding white matter hyperintensities at increments of 0.86 mm thickness. Lower mean intensity within white matter hyperintensities was a significant predictor of longer reaction time (t = -3.77, P < 0.01). White matter hyperintensity volume was predicted by textural features within white matter hyperintensities and normal appearing white matter, albeit in opposite directions. A white matter area extending 2.5 - 3.5 mm further from the white matter hyperintensities demonstrated similar associations. White matter hyperintensity volume was not related to reaction time, although interaction analysis revealed that participants with high white matter hyperintensity burden and less homogeneous white matter hyperintensity texture demonstrated slower reaction time. Higher Cardiovascular Risk Factors, Aging, and Dementia score was associated with a heterogeneous normal appearing white matter intensity pattern. Overall, greater homogeneity within white matter hyperintensities and a more heterogeneous normal appearing white matter intensity profile were connected to a higher white matter hyperintensity burden, while heterogeneous intensity was related to prolonged reaction time (white matter hyperintensities of larger volume) and dementia risk (normal appearing white matter). Our results suggest that the quantified textural measures extracted from widely used clinical scans, might capture underlying microstructural damage and might be more sensitive to early pathological changes compared to white matter hyperintensity volumetry.
preclinical dementia, radiomics, small vessel disease, textural analysis, white matter hyperintensities
This work was funded by a grant for the PREVENT-Dementia program from the UK Alzheimer's Society (grant numbers 178 and 264), and the PREVENT-Dementia study is also supported by the US Alzheimer's Association (grant number TriBEKa-17–519007) and philanthropic donations. AL is supported by the Lee Kuan Yew Fitzwilliam PhD Scholarship and the Tan Kah Kee Postgraduate Scholarship. LS is supported by the Cambridge National Institute for Health Research Biomedical Research Center and Alzheimer's Research UK (ARUK-SRF2017B-1). HSM is supported by an National Institute for Health Research Senior Investigator award. JOB and HSM receive infrastructural support from the Cambridge National Institute for Health Research Biomedical Research Center.
Alzheimer's Society (264, 17, 178)
External DOI: https://doi.org/10.1093/braincomms/fcac116
This record's URL: https://www.repository.cam.ac.uk/handle/1810/338547
Attribution 4.0 International
Licence URL: https://creativecommons.org/licenses/by/4.0/
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