{"doi":"10.1002/mrm.29918","title":"Distinguishing metabolic signals of liver tumors from surrounding liver cells using hyperpolarized <scp><sup>13</sup>C MRI</scp> and gadoxetate","abstract":"Abstract Purpose To use the hepatocyte‐specific gadolinium‐based contrast agent gadoxetate combined with hyperpolarized (HP) [1‐ 13 C]pyruvate MRI to selectively suppress metabolic signals from normal hepatocytes while preserving the signals arising from tumors. Methods Simulations were performed to determine the expected changes in HP 13 C MR signal in liver and tumor under the influence of gadoxetate. CC531 colon cancer cells were implanted into the livers of five Wag/Rij rats. Liver and tumor metabolism were imaged at 3 T using HP [1‐ 13 C] pyruvate chemical shift imaging before and 15 min after injection of gadoxetate. Area under the curve for pyruvate and lactate were measured from voxels containing at least 75% of normal‐appearing liver or tumor. Results Numerical simulations predicted a 36% decrease in lactate‐to‐pyruvate (L/P) ratio in liver and 16% decrease in tumor. In vivo, baseline L/P ratio was 0.44 ± 0.25 in tumors versus 0.21 ± 0.08 in liver ( p = 0.09). Following administration of gadoxetate, mean L/P ratio decreased by an average of 0.11 ± 0.06 ( p &lt; 0.01) in normal‐appearing liver. In tumors, mean L/P ratio post‐gadoxetate did not show a statistically significant change from baseline. Compared to baseline levels, the relative decrease in L/P ratio was significantly greater in liver than in tumors (−0.52 ± 0.16 vs. −0.19 ± 0.25, p &lt; 0.05). Conclusions The intracellular hepatobiliary contrast agent showed a greater effect suppressing HP 13 C MRI metabolic signals (through T 1 shortening) in normal‐appearing liver when compared to tumors. The combined use of HP MRI with selective gadolinium contrast agents may allow more selective imaging in HP 13 C MRI.","journal":"Magnetic Resonance in Medicine","year":2024,"id":493619,"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":0.9608,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":345502,"name":"Jeremy W. Gordon","orcid":"0000-0003-2760-4886","position":1,"is_corresponding":false},{"id":345505,"name":"Robert Bok","orcid":"0000-0003-1737-9056","position":2,"is_corresponding":false},{"id":401767,"name":"Cornelius von Morze","orcid":"0000-0002-3992-1793","position":3,"is_corresponding":false},{"id":345507,"name":"Daniel B. Vigneron","orcid":"0000-0001-5795-8699","position":4,"is_corresponding":false},{"id":460832,"name":"John Kurhanewicz","orcid":"0000-0002-3544-5339","position":5,"is_corresponding":false},{"id":535118,"name":"Michael A. Ohliger","orcid":"0000-0001-6878-8189","position":6,"is_corresponding":false},{"id":435912,"name":"Shubhangi Agarwal","orcid":"0000-0001-7564-3826","position":0,"is_corresponding":true}],"reference_count":40,"raw_metadata":null,"created_at":"2026-07-19T02:09:03.883685Z","pmid":"38270193","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":[]}