Studies of healthy brain aging have reported diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at the typical b-value (approximately 1000 s/mm2) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental changes by incorporating additional data at a higher b-value. In this study, using UK Biobank data (b values of 1000 and 2000 s/mm2), we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We find a general pattern of lower kurtosis alongside higher diffusivity among older adults. We also find differences between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion. This work highlights the utility of measuring diffusional kurtosis as a simple addition to conventional diffusion imaging of aging.
Differentiation of Low- and High-Grade Gliomas Using High b-Value Diffusion Imaging with a Non-Gaussian Diffusion Model