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Abstract #1719

Deep Learning off-resonance correction for faster free-breathing contrast-enhanced conical ultrashort echo time (UTE) MRI of the pelvis

Signy Holmes1, David Zeng2, Joseph Y Cheng1, Marcus T Alley1, Michael Carl3, Dwight Nishimura2, Preeti A Sukerkar1, Vipul R Sheth1, Ryan Brunsing1, and Shreyas S Vasanawala1

1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States, 3Applied Science Laboratory, GE Healthcare, San Diego, CA, United States

MRI sequences with 3D cones k-space trajectories allow decreased motion artifacts while achieving ultrashort echo times (UTE). Extending readout durations allows decreased scan times but lead to worsening off-resonance artifacts. We assessed the performance of extended-readout, free-breathing UTE 3D cones MRI with and without a deep learning off-resonance correction in the evaluation of the adult pelvis. UTE imaging performed significantly better than 3D Cartesian spoiled gradient echo (SPGR) in noise, and after off-resonance correction also performed significantly better in artifact reduction.

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