Abstract #0341

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

Yibo Zhao^1,2, T. Kevin Hitchens^3,4, Michele Herneisey⁵, Jelena M. Janjic⁵, Rong Guo^1,2, Yudu Li^1,2, and Zhi-Pei Liang^1,2

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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