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.
ASJC Scopus subject areas
- Cognitive Neuroscience
Hsu, J. L., Van Hecke, W., Bai, C. H., Lee, C. H., Tsai, Y. F., Chiu, H. C., Jaw, F. S., Hsu, C. Y., Leu, J. G., Chen, W. H., & Leemans, A. (2010). Microstructural white matter changes in normal aging: A diffusion tensor imaging study with higher-order polynomial regression models. NeuroImage, 49(1), 32-43. https://doi.org/10.1016/j.neuroimage.2009.08.031