Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI
Billiet,T. ; Vandenbulcke,M. ; Mädler,B. ; Peeters,R. ; Dhollander ,T. ; Zhang,H. ; Deprez,S. ; Van Den Bergh,B.R.H. ; Sunaert,S. ; Emsell,L.
Billiet,T.
Vandenbulcke,M.
Mädler,B.
Peeters,R.
Dhollander ,T.
Zhang,H.
Deprez,S.
Van Den Bergh,B.R.H.
Sunaert,S.
Emsell,L.
Abstract
Age-related microstructural differences have been detected using diffusion tensor imaging (DTI). Although DTI is sensitive to the effects of aging, it is not specific to any underlying biological mechanism, including demyelination. Combining multiexponential T2 relaxation (MET2) and multishell diffusion MRI (dMRI) techniques may elucidate such processes. Multishell dMRI and MET2 data were acquired from 59 healthy participants aged 17–70 years. Whole-brain and regional age-associated correlations of measures related to multiple dMRI models (DTI, diffusion kurtosis imaging [DKI], neurite orientation dispersion and density imaging [NODDI]) and myelin-sensitive MET2 metrics were assessed. DTI and NODDI revealed widespread increases in isotropic diffusivity with increasing age. In frontal white matter, fractional anisotropy linearly decreased with age, paralleled by increased “neurite” dispersion and no difference in myelin water fraction. DKI measures and neurite density correlated well with myelin water fraction and intracellular and extracellular water fraction. DTI estimates remain among the most sensitive markers for age-related alterations in white matter. NODDI, DKI, and MET2 indicate that the initial decrease in frontal fractional anisotropy may be due to increased axonal dispersion rather than demyelination. Keywords: Aging, Relaxometry, Myelin water imaging, Diffusion MRI, Healthy, Kurtosis
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2015
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Billiet, T, Vandenbulcke, M, Mädler, B, Peeters, R, Dhollander , T, Zhang, H, Deprez, S, Van Den Bergh, B R H, Sunaert, S & Emsell, L 2015, 'Age-related microstructural differences quantified using myelin water imaging and advanced diffusion MRI', Neurobiology of Aging, vol. 36, no. 6, pp. 2107–2121. https://doi.org/10.1016/j.neurobiolaging.2015.02.029
