Speeding up Dynamic Spiral Chemical Shift Imaging with Incoherent Sampling and Low-Rank Matrix Completion: Application in Hyperpolarized 13 C Metabolic Imaging

While hyperpolarized 13C metabolic imaging permits real-time investigation of metabolism in vivo, it requires fast acquisition schemes. We implemented an iterative reconstruction algorithm based on low-rank matrix completion that exploits spatiotemporal correlations in incoherently undersampled, time-resolved data. The algorithm was applied to both retro- and prospectively undersampled dynamic spiral chemical shift imaging (spCSI) data by pseudo-randomly omitting spatial interleaves and the results were compared to conventional reconstruction. The presented data demonstrate that LRMC reconstruction in combination with incoherent undersampling permits substantial reduction in minimum acquisition time of dynamic spCSI without significantly compromising image quality.

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