Hyperpolarized C metabolic imaging of the human abdomen with spatiotemporal denoising.

Purpose: Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach.

Methods: Denoising performance was first evaluated using the simulated [1- C]pyruvate dynamics at different noise levels to determine optimal k and k parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1- C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients).

Results: The parameterization of k  = 0.2 and k  = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The k (conversion rate of pyruvate-to-metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground-truth metabolic conversion rates when there is adequate SNR (SNR  > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1- C]pyruvate, [1- C]lactate, and [1- C]alanine apparent SNR . The improvement in metabolite SNR enabled a more robust quantification of k and k . After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5-fold increase in the number of voxels reliably fit across abdominal FOVs for k and k quantification maps.

Conclusion: Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1- C]alanine and quantification of [1- C]pyruvate metabolism in large FOV HP C MRI studies of the human abdomen.