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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