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Abstract #0341

Fast High-Resolution 19F-MRSI of Perfluorocarbon Nanoemulsions for MRI Cell Tracking Using SPICE with Learned Subspaces

Yibo Zhao1,2, T. Kevin Hitchens3,4, Michele Herneisey5, Jelena M. Janjic5, Rong Guo1,2, Yudu Li1,2, and Zhi-Pei Liang1,2
1Department of Electrical and Computer Engineering, University of Illinois, Urbana-Champaign, Urbana, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois, Urbana-Champaign, Urbana, IL, United States, 3Animal Imaging Center, University of Pittsburgh, Pittsburgh, PA, United States, 4Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA, United States, 5Graduate School of Pharmaceutical Sciences, Duquesne University, Pittsburgh, PA, United States

19F-MRSI has the potential to track multiple perfluorocarbon nanoemulsions simultaneously, but existing 19F-MRSI schemes have been limited to CSI, which provides a poor tradeoff between resolution and scan time. In this work, a novel method is proposed to enable fast high-resolution 19F-MRSI. In the proposed method, (k,t)-space is sampled rapidly in EPSI trajectories; data processing is accomplished using a union-of-subspaces model with pre-learned spectral basis. The proposed method has been evaluated using simulation and experimental data, producing encouraging results. The proposed method may open up new opportunities for simultaneous tracking of different labeled cell populations in vivo.

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