{"doi":"10.1002/mrm.30445","title":"A data‐driven approach for improved quantification of in vivo metabolic conversion rates of hyperpolarized [1‐ <scp> <sup>13</sup> C </scp> ]pyruvate","abstract":"Abstract Purpose Accurate quantification of metabolism in hyperpolarized (HP) 13 C MRI is essential for clinical applications. However, kinetic model parameters are often confounded by uncertainties in radiofrequency flip angles and other model parameters. Methods A data‐driven kinetic fitting approach for HP 13 C‐pyruvate MRI was proposed that compensates for uncertainties in the B 1 + field. We hypothesized that introducing a scaling factor to the flip angle to minimize fit residuals would allow more accurate determination of the pyruvate‐to‐lactate conversion rate ( k PL ). Numerical simulations were performed under different conditions (flip angle, k PL , and T 1 relaxation), with further testing using HP 13 C‐pyruvate MRI of rat liver and kidneys. Results Simulations showed that the proposed method reduced k PL error from 60% to 1% when the prescribed and actual flip angles differed by 60%. The method also showed robustness to T 1 uncertainties, achieving median k PL errors within ±3% even when the assumed T 1 was incorrect by up to a factor of 2. In rat studies, better‐quality fitting for lactate signals (a 1.4‐fold decrease in root mean square error [RMSE] for lactate fit) and tighter k PL distributions (an average of 3.1‐fold decrease in k PL standard deviation) were achieved using the proposed method compared with when no correction was applied. Conclusion The proposed data‐driven kinetic fitting approach provided a method to accurately quantify HP 13 C‐pyruvate metabolism in the presence of B 1 + inhomogeneity. This model may also be used to correct for other error sources, such as T 1 relaxation and flow, and may prove to be clinically valuable in improving tumor staging or assessing treatment response.","journal":"Magnetic Resonance in Medicine","year":2025,"id":562252,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9459,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":884983,"name":"Tanner Nickles","orcid":"0000-0003-4322-2431","position":1,"is_corresponding":false},{"id":755983,"name":"Philip Lee","orcid":"0000-0002-5783-1599","position":2,"is_corresponding":false},{"id":345505,"name":"Robert Bok","orcid":"0000-0003-1737-9056","position":3,"is_corresponding":false},{"id":345502,"name":"Jeremy W. Gordon","orcid":"0000-0003-2760-4886","position":4,"is_corresponding":false},{"id":313995,"name":"Peder E. Z. Larson","orcid":"0000-0003-4183-3634","position":5,"is_corresponding":false},{"id":345507,"name":"Daniel B. Vigneron","orcid":"0000-0001-5795-8699","position":6,"is_corresponding":false},{"id":401767,"name":"Cornelius von Morze","orcid":"0000-0002-3992-1793","position":7,"is_corresponding":false},{"id":535118,"name":"Michael A. Ohliger","orcid":"0000-0001-6878-8189","position":8,"is_corresponding":false},{"id":495583,"name":"Yaewon Kim","orcid":"0000-0003-1016-1572","position":0,"is_corresponding":true}],"reference_count":34,"raw_metadata":null,"created_at":"2026-07-19T02:56:05.550545Z","pmid":"39963732","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}