{"doi":"10.1002/mrm.28187","title":"Non‐contrast‐enhanced abdominal MRA at 3 T using velocity‐selective pulse trains","abstract":"PURPOSE: Most existing non-contrast-enhanced methods for abdominal MR arteriography rely on a spatially selective inversion (SSI) pulse with a delay to null both static tissue and venous blood, and are limited to small spatial coverage due to the sensitivity to slow arterial inflow. Velocity-selective inversion (VSI) based approach has been shown to preserve the arterial blood inside the imaging volume at 1.5 T. Recently, velocity-selective saturation (VSS) pulse trains were applied to suppress the static tissue and have been combined with SSI pulses for cerebral MR arteriography at 3 T. The aim of this study is to construct an abdominal MRA protocol with large spatial coverage at 3 T using advanced velocity-selective pulse trains. METHODS: Multiple velocity-selective MRA protocols with different sequence modules and 3D acquisition methods were evaluated. Sequences using VSS only as well as SSI+VSS and VSI+VSS preparations were then compared among a group of healthy young and middle-aged volunteers. Using MRA without any preparations as reference, relative signal ratios and relative contrast ratios of different vascular segments were quantitatively analyzed. RESULTS: Both SSI+VSS and VSI+VSS arteriograms achieved high artery-to-tissue and artery-to-vein relative contrast ratios above aortic bifurcation. The SSI+VSS sequence yielded lower signal at the bilateral iliac arteries than VSI+VSS, reflecting the benefit of the VSI preparation for imaging the distal branches. CONCLUSION: The feasibility of noncontrast 3D MR abdominal arteriography was demonstrated on healthy volunteers using a combination of VSS pulse trains and SSI or VSI pulse.","journal":"Magnetic Resonance in Medicine","year":2020,"id":102098,"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":26,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.955,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":344982,"name":"Wenbo Li","orcid":"0000-0002-0199-1534","position":1,"is_corresponding":false},{"id":444971,"name":"Dapeng Liu","orcid":"0000-0001-9202-3303","position":2,"is_corresponding":false},{"id":429880,"name":"Guanshu Liu","orcid":"0000-0002-8188-4332","position":3,"is_corresponding":false},{"id":500111,"name":"Yigang Pei","orcid":null,"position":4,"is_corresponding":false},{"id":499120,"name":"Taehoon Shin","orcid":"0000-0003-1780-573X","position":5,"is_corresponding":false},{"id":499121,"name":"Farzad Sedaghat","orcid":"0000-0002-9067-3684","position":6,"is_corresponding":false},{"id":271394,"name":"Qin Qin","orcid":"0000-0002-6432-2944","position":7,"is_corresponding":false},{"id":409992,"name":"Dan Zhu","orcid":"0000-0002-0940-1519","position":0,"is_corresponding":true}],"reference_count":53,"raw_metadata":null,"created_at":"2026-07-18T22:40:51.552773Z","pmid":"32017173","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":[]}