Abstract

Diffusion tensor imaging is being performed as part of routine clinical neuroimaging and for research purposes, often involving multiple centers and different vendors. In order to perform comparatively quantitative analysis of tensor metrics, tensor data must be of high quality and reproducible which requires documentation of scanner stability, minimization of artifacts, and optimization and standardization of image parameters. We review various practical aspects of diffusion tensor imaging which impact quality of DTI with the focus on the quantification of diffusivities and fractional anisotropy.

Keywords: Diffusion tensor imaging, Image artifact, Multi-center, Neuroimaging, Quality assurance, Quality control.