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The effect of image pre-processing pipelines on age associations of diffusion and kurtosis in white matter
Jenny Chen1, Benjamin Ades-aron1, Hong-Hsi Lee1, Durga Kullakanda1, Saurabh Maithani1, Dmitry S. Novikov1, Jelle Veraart1, and Els Fieremans1
1Radiology, NYU School Of Medicine, New York, NY, United States
Diffusion MRI is prone to various artifacts such as noise, eddy current artifacts, and Gibbs ringing. This study compares diffusion tensor imaging (DTI) and diffusional kurtosis imaging (DKI) parameter estimates among healthy subjects in their 20s to 80s using a minimal diffusion pre-processing approach from Human Connectome Project (HCP) and two DESIGNER (Diffusion parameter EStImation with Gibbs and NoisE Removal) pipelines, which corrects for additional imaging artifacts HCP pipeline does not account for. Our results show that preprocessing quantitatively impacts parameter estimation as well as alters observed age correlations. 
Figure 2. AK, MK, and RK maps of 27-year-old male derived from HCP, DV1.0, and DV2.0 pipeline.
Figure 1. Diffusion pre-processing flowchart for HCP, DV1.0 and DV2.0 pipeline.