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Medical-image Analysis and Statistical Interpretation Lab

Synthesized b0 for diffusion distortion correction (Synb0-DisCo).

Posted by on Monday, December 16, 2019 in News.

Kurt G Schilling, Yuankai Huo, Allen Newton, Colin Hansen, Vishwesh Nath, Andrea T. Shafer, Owen Williams, Susan M. Resnick, Baxter Rogers, Adam W Anderson, Bennett A Landman. “Synthesized b0 for diffusion distortion correction (Synb0-DisCo).” Magnetic Resonance Imaging. 2019 May 7. pii: S0730-725X(18)30617-9. doi: 10.1016/j.mri.2019.05.008

Full text: https://www.ncbi.nlm.nih.gov/pubmed/?term=Synthesized+b0+for+diffusion+distortion+correction+(Synb0-DisCo).

Abstract

Diffusion magnetic resonance images typically suffer from spatial distortions due to susceptibility induced off-resonance fields, which may affect the geometric fidelity of the reconstructed volume and cause mismatches with anatomical images. State-of-the art susceptibility correction (for example, FSL’s TOPUP algorithm) typically requires data acquired twice with reverse phase encoding directions, referred to as blip-up blip-down acquisitions, in order to estimate an undistorted volume. Unfortunately, not all imaging protocols include a blip-up blip-down acquisition, and cannot take advantage of the state-of-the art susceptibility and motion correctioncapabilities. In this study, we aim to enable TOPUP-like processing with historical and/or limited diffusion imaging data that include only a structural image and single blip diffusion image. We utilize deep learning to synthesize an undistorted non-diffusion weighted image from the structural image, and use the non-distorted synthetic image as an anatomical target for distortion correction. We evaluate the efficacy of this approach (named Synb0-DisCo) and show that our distortion correction process results in better matching of the geometry of undistorted anatomical images, reduces variation in diffusion modeling, and is practically equivalent to having both blip-up and blip-down non-diffusion weighted images.

Fig. 2. Distortion and correction in diffusion MRI. (A) EPI susceptibility distortion occurs along the phase encode direction, with phase encoding in the posterior (PE-P) direction leading to displacements of identical distance but opposite direction of that in the anterior (PE-A) direction. (B) State of the art distortion correction (topup) typically uses distortions in two opposite directions to iteratively estimate the undistorted image. (C) The proposed method uses an undistorted T1-weighted image to synthesize an undistorted volume with b0 contrast, which can be used to correct the distorted (in this case, PE-P) image without requiring an additional phase encoding acquisition. The blue circles highlight areas of observable signal distortion. Yellow arrows indicate phase encode direction. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2. Distortion and correction in diffusion MRI. (A) EPI susceptibility distortion occurs along the phase encode direction, with phase encoding in the posterior (PE-P) direction leading to displacements of identical distance but opposite direction of that in the anterior (PE-A) direction. (B) State of the art distortion correction (topup) typically uses distortions in two opposite directions to iteratively estimate the undistorted image. (C) The proposed method uses an undistorted T1-weighted image to synthesize an undistorted volume with b0 contrast, which can be used to correct the distorted (in this case, PE-P) image without requiring an additional phase encoding acquisition. The blue circles highlight areas of observable signal distortion. Yellow arrows indicate phase encode direction. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)