{"doi":"10.1002/mrm.30156","title":"Diffusion tensor brain imaging at 0.55T: A feasibility study","abstract":"PURPOSE: To investigate the feasibility of diffusion tensor brain imaging at 0.55T with comparisons against 3T. METHODS: Diffusion tensor imaging data with 2 mm isotropic resolution was acquired on a cohort of five healthy subjects using both 0.55T and 3T scanners. The signal-to-noise ratio (SNR) of the 0.55T data was improved using a previous SNR-enhancing joint reconstruction method that jointly reconstructs the entire set of diffusion weighted images from k-space using shared-edge constraints. Quantitative diffusion tensor parameters were estimated and compared across field strengths. We also performed a test-retest assessment of repeatability at each field strength. RESULTS: ) with those obtained from 3T data. Test-retest analysis showed that SNR-enhancing reconstruction improved the repeatability of the 0.55T diffusion tensor parameters. CONCLUSION: High-resolution in vivo diffusion MRI of the human brain is feasible at 0.55T when appropriate noise-mitigation strategies are applied.","journal":"Magnetic Resonance in Medicine","year":2024,"id":471012,"datarank":0.18116831485167206,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.016376471551455607,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.016376471551455607,"corpus_percentile":33.80521389340141,"corpus_rank":8558,"citation_count":2,"citer_count":1,"citers_with_citation_signal":1,"citers_with_endowment":1,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.5453,"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":1287468,"name":"Sophia Cui","orcid":"0000-0002-5133-4903","position":1,"is_corresponding":false},{"id":336390,"name":"Jonas Kaplan","orcid":"0000-0003-0226-909X","position":2,"is_corresponding":false},{"id":364410,"name":"Anand A. Joshi","orcid":"0000-0002-9582-3848","position":3,"is_corresponding":false},{"id":330856,"name":"Richard M. Leahy","orcid":"0000-0002-7278-5471","position":4,"is_corresponding":false},{"id":280605,"name":"Krishna S. Nayak","orcid":"0000-0001-5735-3550","position":5,"is_corresponding":false},{"id":479662,"name":"Justin P. Haldar","orcid":"0000-0002-1838-0211","position":6,"is_corresponding":false},{"id":1305643,"name":"H. Kung","orcid":"0009-0006-0941-7613","position":0,"is_corresponding":true}],"reference_count":49,"raw_metadata":null,"created_at":"2026-07-19T02:05:44.736405Z","pmid":"38725132","pmcid":"PMC12732710","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":[]}