Diffusiontensordata

Diffusiontensordata, commonly referred to as diffusion tensor data or diffusion tensor imaging data, are measurements of the spatial distribution of water diffusion properties in biological tissue. In brain MRI, each voxel contains a diffusion tensor, a symmetric 3x3 matrix that characterizes directional water mobility. The tensor model assumes Gaussian diffusion and yields six unique components, which can be decomposed into eigenvalues and eigenvectors to describe principal diffusion directions and magnitudes.

From the tensor, scalar metrics are derived, such as fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD). FA measures directional restriction of diffusion, MD reflects overall diffusion, while AD and RD relate to diffusion along and perpendicular to the principal fiber direction. These metrics facilitate assessment of white matter integrity and microstructure.

Acquisition involves diffusion-weighted MRI with multiple gradient directions and b-values. Typical clinical protocols use b ~ 1000 s/mm^2 with 30–60 directions; advanced research may employ higher b-values and more directions. Preprocessing includes motion and eddy current correction, susceptibility distortion correction, and brain extraction. Tensor estimation is commonly performed by least-squares fitting.

Data are commonly stored as diffusion-weighted images (DWIs) plus gradient information (b-values and b-vectors) in formats such as NIfTI, with companion files. Tensor-derived maps (FA, MD, etc.) are separate NIfTI volumes. Popular software suites include FSL (dtifit), MRtrix, and DSI Studio; tractography based on the tensor model enables reconstruction of white matter pathways and whole-brain connectomes.

Limitations of diffusion tensor data include difficulty resolving crossing fibers and non-Gaussian diffusion; higher-order models (diffusion kurtosis, Q-ball, diffusion spectrum imaging) provide richer representations. Practical use requires careful QA and standardization across scanners and protocols. Diffusion tensor data underpin studies of development, aging, disease, and brain connectivity.