Abstract #1015

Stack-of-Stars Inversion-Recovery MRI for Free-Breathing T1 Mapping and IR-Prepared Fat/Water Separation

Li Feng¹, Kai Tobias Block², Thomas Benkert³, Ye Tian⁴, Chenyu Liu¹, Fang Liu^5,6, Zahi Fayad¹, and Yang Yang¹

¹Biomedical Engineering and Imaging Institute and Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, ²Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, NY, United States, ³MR Applications Development, Siemens Healthcare GmbH, Erlangen, Germany, ⁴Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, United States, ⁵Gordon Center for Medical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, United States, ⁶Department of Radiology, University of Wisconsin Madison, Madison, WI, United States

This work presents a framework for inversion-recovery (IR)-prepared stack-of-stars imaging and its applications for rapid free-breathing 3D liver MRI. Building upon a previously developed stack-of-stars 3D GRE sequence (RAVE: RAdial Volumetric Encoding), a non-selective 180^o IR pulse has been implemented that is periodically played-out to achieve IR preparation (IR-Prepped RAVE). The new sequence allows (1) single-echo acquisition in combination with GRASP-Pro (imProved Golden-angle RAdial Sparse Parallel) reconstruction for free-breathing volumetric T1 mapping of the liver, and (2) multi-echo acquisition in combination with dynamic model-based reconstruction for IR-prepped and contrast-resolved fat/water separation.

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