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Neurobiol Aging. 2018 Oct;70:265-275. doi: 10.1016/j.neurobiolaging.2018.07.006. Epub 2018 Jul 17.

Modeling white matter tract integrity in aging with diffusional kurtosis imaging.

Author information

1
Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA. Electronic address: benitez@musc.edu.
2
Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.
3
Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
4
Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA; Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA.

Abstract

Myelin breakdown and neural fiber loss occur in aging. This study used white matter tract integrity metrics derived from biophysical modeling using Diffusional Kurtosis Imaging to assess loss of myelin (i.e., extraaxonal diffusivity, radial direction, De,⊥) and axonal density (i.e., axonal water fraction) in cognitively unimpaired older adults. Tract-based spatial statistics and region of interest analyses sought to identify ontogenic differences and age-related changes in white matter tracts using cross-sectional and longitudinal data analyzed with general linear and mixed-effects models. In addition to pure diffusion parameters (i.e., fractional anisotropy, mean diffusivity, mean kurtosis), we found that white matter tract integrity metrics significantly differentiated early- from late-myelinating tracts, correlated with age in spatially distinct regions, and identified primarily extraaxonal changes over time. Percent metric changes were |0.3-0.9|% and |0.0-1.9|% per year using cross-sectional data and longitudinal data, respectively. There was accelerated decline in some late- versus early-myelinating tracts in older age. These results demonstrate that these metrics may inform further study of the transition from age-related changes to neurodegenerative decline.

KEYWORDS:

Aging; Diffusion MRI; Diffusional kurtosis imaging; White matter; White matter tract integrity

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