{"doi":"10.1002/nbm.4589","title":"Volumetric coronary endothelial function assessment: a feasibility study exploiting stack‐of‐stars 3D cine MRI and image‐based respiratory self‐gating","abstract":"Abnormal coronary endothelial function (CEF), manifesting as depressed vasoreactive responses to endothelial-specific stressors, occurs early in atherosclerosis, independently predicts cardiovascular events, and responds to cardioprotective interventions. CEF is spatially heterogeneous along a coronary artery in patients with atherosclerosis, and thus recently developed and tested non-invasive 2D MRI techniques to measure CEF may not capture the extent of changes in CEF in a given coronary artery. The purpose of this study was to develop and test the first volumetric coronary 3D MRI cine method for assessing CEF along the proximal and mid-coronary arteries with isotropic spatial resolution and in free-breathing. This approach, called 3D-Stars, combines a 6 min continuous, untriggered golden-angle stack-of-stars acquisition with a novel image-based respiratory self-gating method and cardiac and respiratory motion-resolved reconstruction. The proposed respiratory self-gating method agreed well with respiratory bellows and center-of-k-space methods. In healthy subjects, 3D-Stars vessel sharpness was non-significantly different from that by conventional 2D radial in proximal segments, albeit lower in mid-portions. Importantly, 3D-Stars detected normal vasodilatation of the right coronary artery in response to endothelial-dependent isometric handgrip stress in healthy subjects. Coronary artery cross-sectional areas measured using 3D-Stars were similar to those from 2D radial MRI when similar thresholding was used. In conclusion, 3D-Stars offers good image quality and shows feasibility for non-invasively studying vasoreactivity-related lumen area changes along the proximal coronary artery in 3D during free-breathing.","journal":"NMR in Biomedicine","year":2021,"id":225851,"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":0.9602,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":271395,"name":"Robert G. Weiss","orcid":"0000-0002-1844-8677","position":1,"is_corresponding":false},{"id":326667,"name":"Davide Piccini","orcid":"0000-0003-4663-3244","position":2,"is_corresponding":false},{"id":326666,"name":"Jérôme Yerly","orcid":"0000-0003-4347-8613","position":3,"is_corresponding":false},{"id":666933,"name":"Sahar Soleimani","orcid":"0000-0003-0870-0768","position":4,"is_corresponding":false},{"id":478469,"name":"Li Pan","orcid":"0000-0002-4839-7057","position":5,"is_corresponding":false},{"id":383639,"name":"Xiaoming Bi","orcid":"0000-0001-6286-9172","position":6,"is_corresponding":false},{"id":497800,"name":"Allison G. Hays","orcid":"0000-0003-2138-1589","position":7,"is_corresponding":false},{"id":326672,"name":"Matthias Stuber","orcid":"0000-0001-9843-2028","position":8,"is_corresponding":false},{"id":271391,"name":"Michael Schär","orcid":"0000-0002-7044-9941","position":9,"is_corresponding":false},{"id":743736,"name":"Gabriele Bonanno","orcid":"0000-0002-7761-5308","position":0,"is_corresponding":true}],"reference_count":62,"raw_metadata":null,"created_at":"2026-07-18T23:54:30.292454Z","pmid":"34291517","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":[]}