Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.05.18.102558v1?rss=1 Authors: Hansen, C. B., Rogers, B. P., Schilling, K. G., Nath, V., Blaber, J. A., Irfanoglu, O., Barnett, A., Pierpaoli, C., Anderson, A. W., Landman, B. A. Abstract: Background: Achieving inter-site / inter-scanner reproducibility of diffusion weighted magnetic resonance imaging (DW-MRI) metrics has been challenging given differences in acquisition protocols, analysis models, and hardware factors. Purpose: Gradient fields impart scanner-dependent spatial variations in the applied diffusion weighting that can be corrected if the gradient non-linearities are known. However, retrieving manufacturer non-linearity specifications is not well supported and may introduce errors in interpretation of units or coordinate systems. We propose an empirical approach to mapping the gradient nonlinearities with sequences that are supported across the major scanner vendors. Study Type: Prospective observational study Subjects: Two diffusion phantoms (High Precision Devices diffusion phantom and a custom isotropic phantom), five human control volunteers. Field Strength/Sequence: 3T (three scanners). Stejskal-Tanner spin echo sequence with b-values of 1000, 2000 s/mm2 with 12 and 32 diffusion gradient directions per shell. Assessment: We compare the proposed correction with the prior approach using manufacturer specifications against typical diffusion pre-processing pipelines (i.e., ignoring spatial gradient non-linearities). In phantom data, we evaluate metrics against the ground truth. In human and phantom data, we evaluate reproducibility across scans, sessions, and hardware. Statistical Tests: Wilcoxon rank-sum test between uncorrected and corrected data. Results: In phantom data, our correction method reduces variation in metrics across sessions over uncorrected data (p<0.05). In human data, we show that this method can also reduce variation in mean diffusivity across scanners (p<0.05). Conclusion: Our method is relatively simple, fast, and can be applied retroactively. We advocate incorporating voxel-specific b-value and b-vector maps should be incorporated in DW-MRI harmonization preprocessing pipelines to improve quantitative accuracy of measured diffusion parameters. Keywords: Gradient Non-linearity, Field Estimation, Pre-processing, DW-MRI Copy rights belong to original authors. Visit the link for more info