Deuterium metabolic imaging (DMI) is an emerging technique to spatially map metabolism in vivo through the intake of deuterium (i.e., 2H or D) labeled substrates such as [6,6′-2H2]-glucose. Although DMI has the potential to become a powerful tool to assess liver metabolism, it has limitations due to its long scan time, and low signal-to-noise ratio (SNR) for high spatial resolution in the human body. In this work, we demonstrated the feasibility of low-rank and subspace modeling (LRSM) reconstruction to increase SNR by reducing spectral noise, allowing high spatiotemporal resolution for 3D DMI of the human liver at 7T.
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