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bioRxiv · 10.1101/864108

Diffusion Weighted Image Co-registration: Investigation of Best Practices

Chen, D. Q.·Dell'Acqua, F.·Rokem, A.·Garyfallidis, E.·Hayes, D. J.·Zhong, J.·Hodaie, M.
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Abstract

1.The registration or alignment of diffusion weighted images (DWI) with other imaging modalities is a critical step in neuroimaging analysis. Within-subject T1-DWI co-registration is particularly instrumental. DWI-derived scalar images are commonly used as intermediates for T1-DWI co-registration, and the resulting registration transforms are applied to all other scalar images for analysis. The ideal registration intermediate should register well to T1 and other multimodal images and be practically easy to obtain. It is however, currently unclear which DWI-derived scalar image serves as the best intermediate. We aim to determine the best, practical, intermediate for image co-registration. T1 and DWI images were acquired from 20 healthy subjects. DWIs were acquired with 60 directions. Six DWI-derived scalar images were compared including: 1) fractional anisotropy (FA); 2) generalized FA (GFA); 3) B0 images; 4) mean DWIs with the B0 image (MDWI); 5) anisotropic power (AP) images. AP showed the smallest variability in registration improvements across all the tested DWI derived scalar images, and show the highest average percent changes with CC registration cost function (CC=1.2%, MI=15%). In contrast, the FA and GFA transforms resulted in significantly poorer registration across DWI types. The AP image was the DWI-derived scalar image that provided the most consistent registration to all other images. Practically, it is generated easily and so could be implemented in basic and clinical research pipelines currently using other intermediates. Given these findings, it is recommended that AP images be used for T1-DWI co-registration, and that FA and GFA images in particular be avoided.

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Chen, D. Q., Dell'Acqua, F., Rokem, A., Garyfallidis, E., Hayes, D. J., Zhong, J., Hodaie, M.. 2019-12-10. Diffusion Weighted Image Co-registration: Investigation of Best Practices. https://doi.org/10.1101/864108

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