{"doi":"10.1101/2020.06.22.20137638","title":"Closed-loop control of k-space sampling via physiologic feedback for cine MRI","abstract":"Abstract Background Segmented cine cardiac MRI combines data from multiple heartbeats to achieve high spatiotemporal resolution cardiac images, yet predefined k-space segmentation trajectories can lead to suboptimal k-space sampling. In this work, we developed and evaluated an autonomous and closed-loop control system for radial k-space sampling to increase sampling uniformity. Methods The closed-loop system autonomously selects radial k-space sampling trajectory during live segmented cine MRI and attempts to optimize angular sampling uniformity by selecting views in regions of k-space that were not previously well-sampled. Sampling uniformity and robustness to arrhythmias was assessed using ECG data acquired from 10 normal subjects in an MRI scanner. The approach was then implemented with a fast gradient echo sequence on a whole-body clinical MRI scanner and imaging was performed in 4 healthy volunteers. The closed-loop k-space trajectory was compared to random, uniformly distributed and golden angle view trajectories via measurement of k-space uniformity and the point spread function. Lastly, an arrhythmic dataset was used to evaluate a potential application of the approach. Results The autonomous trajectory increased k-space sampling uniformity by 13±7%, main lobe point spread function (PSF) signal intensity by 14±6%, and reduced ringing relative to golden angle sampling. When implemented, the autonomous pulse sequence prescribed radial view angles faster than the scan TR (0.98 ± 0.02 ms, maximum = 1.38 ms) and increased k-space sampling mean uniformity by 5±12%, decreased uniformity variability by 45±14%, and increased PSF signal ratio by 5±5% relative to golden angle sampling. Conclusion The closed-loop approach enables near-uniform radial sampling in a segmented acquisition approach which was higher than predetermined golden-angle radial sampling. This can be utilized to increase the sampling or decrease the temporal footprint of an acquisition and the closed-loop framework has the potential to be applied to patients with complex heart rhythms.","journal":"medRxiv","year":2020,"id":126964,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9557,"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":329908,"name":"Yuchi Han","orcid":"0000-0001-7582-1848","position":1,"is_corresponding":false},{"id":329893,"name":"Srikant Kamesh Iyer","orcid":"0000-0001-6873-0294","position":2,"is_corresponding":false},{"id":328469,"name":"Peter Kellman","orcid":"0000-0002-9875-6070","position":3,"is_corresponding":false},{"id":537209,"name":"Gene Gualtieri","orcid":null,"position":4,"is_corresponding":false},{"id":275710,"name":"Mark A. Elliott","orcid":"0000-0003-4191-5509","position":5,"is_corresponding":false},{"id":536590,"name":"Sebastian Berisha","orcid":"0000-0003-2232-624X","position":6,"is_corresponding":false},{"id":330554,"name":"Joseph H. Gorman","orcid":null,"position":7,"is_corresponding":false},{"id":330555,"name":"Robert C. Gorman","orcid":null,"position":8,"is_corresponding":false},{"id":329903,"name":"James J. Pilla","orcid":"0000-0002-7631-5231","position":9,"is_corresponding":false},{"id":329911,"name":"Walter R. Witschey","orcid":"0000-0003-1669-2120","position":10,"is_corresponding":false},{"id":365029,"name":"Francisco Contijoch","orcid":"0000-0001-9616-3274","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-18T23:15:27.226519Z","pmid":null,"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":[]}