Hyperpolarized 13C metabolic imaging of the human abdomen with spatiotemporal denoising

Purpose: Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) C-13 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-13]pyruvate dynamics at different noise levels to determine optimal k(global) and k(local) parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-C-13]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients).Results: The parameterization of k(global) = 0.2 and k(local) = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The k(PX) (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 (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1-C-13]pyruvate, [1-C-13]lactate, and [1-C-13]alanine apparent SNRAUC. The improvement in metabolite SNR enabled a more robust quantification of k(PL) and k(PA). 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(PL) and k(PA) quantification maps.Conclusion: Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-C-13]alanine and quantification of [1-C-13]pyruvate metabolism in large FOV HP C-13 MRI studies of the human abdomen.