Age-related assessment of diffusion parameters in specific brain tracts correlated with cortical thinning.

The aging process is associated with many brain structural alterations. These changes are not associated with neuronal loss but can be due to cortical structural changes that may be related to white matter (WM) structural alterations. In this study, we evaluated age-related changes in WM and gray matter (GM) parameters and how they correlate for specific brain tracts in a cohort of 158 healthy individuals, aged between 18 and 83 years old. In the tract-cortical analysis, cortical regions connected by tracts demonstrated similar thinning patterns for the majority of tracts. Additionally, a significant relationship was found between mean cortical thinning rate with fractional anisotropy (FA) and mean diffusivity (MD) alteration rates. For all tracts, age was the main effect controlling diffusion parameter alterations. We found no direct correlations between cortical thickness and FA or MD, except for in the fornix, for which the subcallosal gyrus thickness was significantly correlated to FA and MD (p < 0.05 FDR corrected). Our findings lead to the conclusion that alterations in the WM diffusion parameters are explained by the aging process, also associated with cortical thickness changes. Also, the alteration rates of the structural parameters are correlated to the different brain tracts in the aging process.

Harmonization of Brain Diffusion MRI: Concepts and Methods.

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.