{"doi":"10.1002/jmri.28158","title":"Feasibility and Reproducibility of Multifrequency Magnetic Resonance Elastography in Healthy and Diseased Pancreases","abstract":"BACKGROUND: The feasibility and reproducibility of multifrequency MR elastography (MRE) for diagnosing pancreatic ductal adenocarcinoma (PDAC) have not been reported. PURPOSE: To determine the feasibility and reproducibility of multifrequency MRE for assessing pancreatic stiffness in healthy and diseased pancreases. STUDY TYPE: Prospective. SUBJECTS: A total of 40 healthy volunteers and 10 patients with PDAC were prospectively recruited between March 2018 and October 2021. FIELD STRENGTH/SEQUENCE: A 3.0-T pancreatic MRE at frequencies in the order of 30, 40, 60, 80, and 100 Hz. ASSESSMENT: Body mass index (BMI) and wave distance of the healthy pancreas and PDAC were measured. Image quality was assessed using the image quality score (IQS: 1-4, ≥3 were considered diagnostic quality). Three readers independently performed the pancreatic stiffness and IQS assessments to evaluate reproducibility. STATISTICAL TESTS: Logistic regression analyses were performed to determine variables that influenced IQS. Statistical significance was set at P <0.05. Levels of inter- and intrarater agreement were assessed using intraclass correlation coefficients (ICC) and Cohen's kappa coefficient (κ). Good reproducibility was set at ICC and κ ≥ 0.8. RESULTS: ), and lower frequency (30 and 40 Hz: OR = 170.01 and 96.02). In PDAC, frequency was the only independent factor for diagnostic IQS (30-60 Hz: OR = 46.18, 46.18, and 17.20, respectively) with 100 Hz as a reference. In healthy volunteers, good reproducibility was observed at 30 and 40 Hz. In PDAC, good reproducibility was observed at 30-60 Hz. DATA CONCLUSION: MRE at 30 and 40 Hz provides diagnostic wave images and reliable measurements of pancreatic stiffness in healthy volunteers. MRE at 30-60 Hz is acceptable for PDACs (IQS ≥ 3, ICC and κ ≥ 0.80). EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.","journal":"Journal of Magnetic Resonance Imaging","year":2022,"id":264018,"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":12,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6555,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":574410,"name":"Yu Shi","orcid":"0000-0003-1940-0074","position":1,"is_corresponding":false},{"id":921547,"name":"Feng Gao","orcid":"0000-0002-1000-385X","position":2,"is_corresponding":false},{"id":275037,"name":"Meng Yin","orcid":"0000-0001-6778-192X","position":3,"is_corresponding":false},{"id":104165,"name":"Rui Yang","orcid":"0000-0003-4427-2158","position":4,"is_corresponding":false},{"id":921548,"name":"Yuanyuan Liu","orcid":"0000-0002-2873-8854","position":5,"is_corresponding":false},{"id":922106,"name":"Shiling Zhong","orcid":null,"position":6,"is_corresponding":false},{"id":646723,"name":"Yang Hong","orcid":"0000-0001-7219-3241","position":7,"is_corresponding":false},{"id":921546,"name":"Qike Song","orcid":"0000-0003-3307-0411","position":0,"is_corresponding":true}],"reference_count":38,"raw_metadata":null,"created_at":"2026-07-19T00:26:37.567338Z","pmid":"35332973","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":[]}