Microstructural white matter changes in normal aging: A diffusion tensor imaging study with higher-order polynomial regression models

Diffusion tensor imaging (DTI) has already proven to be a valuable tool when investigating both global and regional microstructural white matter (WM) brain changes in the human aging process. Although subject to many criticisms, voxel-based analysis is currently one of the most common and preferred approaches in such DTI aging studies. In this context, voxel-based DTI analyses have assumed a ‘linear’ correlation when finding the significant brain regions that relate age with a particular diffusion measure of interest. Recent literature, however, has clearly demonstrated ‘non-linear’ relationships between age and diffusion metrics by using region-of-interest and tractography-based approaches. In this work, we incorporated polynomial regression models in the voxel-based DTI analysis framework to assess age-related changes in WM diffusion properties (fractional anisotropy and axial, transverse, and mean diffusivity) in a large cohort of 346 subjects (25 to 81 years old). Our novel approach clearly demonstrates that voxel-based DTI analyses can greatly benefit from incorporating higher-order regression models when investigating potential relationships between aging and diffusion properties.