Within Subject Averaging of Diffusion Tensor MRI Data Sets: A Test-Retest Reproducibility Evaluation

Nico Dario Papinutto¹, Jorge Jovicich¹

The accuracy and precision of a Diffusion tensor imaging (DTI) acquisition of in-vivo human brains depends on both the acquisition protocol and post-processing used for data analysis. In many cases multiple acquisitions from the same session are averaged to increase signal-to-noise ratio and reduce sensitivity to motion during the acquisition. The complexity of DTI datasets allows for several processing paths to complete eddy current correction, co-registration, averaging and tensor fitting. Here we assess the sensitivity of fractional anisotropy (FA) test-retest reproducibility to different methods for merging multiple within-subject DTI acquisitions.