{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Nickles TM"],"funding":["NIBIB NIH HHS","NIDDK NIH HHS","NCI NIH HHS","National Institutes of Health","NIH HHS"],"pagination":["2153-2161"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10950515"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["91(5)"],"pubmed_abstract":["

Purpose

Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 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 [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients).

Results

The parameterization of kglobal  = 0.2 and klocal  = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (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 [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . 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 kPL and kPA quantification maps.

Conclusion

Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen."],"journal":["Magnetic resonance in medicine"],"pubmed_title":["Hyperpolarized <sup>13</sup> C metabolic imaging of the human abdomen with spatiotemporal denoising."],"pmcid":["PMC10950515"],"funding_grant_id":["U01 EB026412","P41 EB013598","R01 CA249909","R01 CA256740","R01 DK115987","R01DK115987","P41EB013598","U01EB026412"],"pubmed_authors":["Vigneron DB","Nickles TM","Gordon JW","Chen HY","Kim Y","Ohliger M","Bok RA","Wang ZJ","Larson PEZ","Lee PM"],"additional_accession":[]},"is_claimable":false,"name":"Hyperpolarized <sup>13</sup> C metabolic imaging of the human abdomen with spatiotemporal denoising.","description":"

Purpose

Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 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 [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients).

Results

The parameterization of kglobal  = 0.2 and klocal  = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (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 [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . 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 kPL and kPA quantification maps.

Conclusion

Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 May","modification":"2025-07-12T03:05:51.03Z","creation":"2025-07-12T03:05:51.03Z"},"accession":"S-EPMC10950515","cross_references":{"pubmed":["38193310"],"doi":["10.1002/mrm.29985"]}}