{"doi":"10.1002/mrm.28777","title":"Motion‐compensated 3D turbo spin‐echo for more robust MR intracranial vessel wall imaging","abstract":"PURPOSE: (1) To investigate the effect of internal localized movement on 3DMR intracranial vessel wall imaging and (2) to develop a novel motion-compensation approach combining volumetric navigator (vNav) and self-gating (SG) to simultaneously compensate for bulk and localized movements. METHODS: A 3D variable-flip-angle turbo spin-echo (ie, SPACE) sequence was modified to incorporate vNav and SG modules. The SG signals from the center k-space line are acquired at the beginning of each TR to detect localized motion-affected TRs. The vNavs from low-resolution 3D EPI are acquired to identify bulk head motion. Fifteen healthy subjects and 3 stroke patients were recruited in this study. Overall image quality (0-poor to 4-excellent) and vessel wall sharpness were compared among the scenarios with and without bulk and/or localized motion and/or the proposed compensation strategies. RESULTS: Localized motion reduced wall sharpness, which was significantly mitigated by SG (ie, outer boundary of basilar artery: 0.68 ± 0.27 vs 0.86 ± 0.17; P = .037). When motion occurred, the overall image quality and vessel wall sharpness obtained with vNav-SG SPACE were significantly higher than those obtained with conventional SPACE (ie, basilarartery outer boundary sharpness: 0.73 ± 0.24 vs 0.94 ± 0.24; P = .033), yet comparable to those obtained in motion-free scans (ie, basilarartery outer boundary sharpness: 0.94 ± 0.24 vs 0.96 ± 0.31; P = .815). CONCLUSION: Localized movements can induce considerable artifacts in intracranial vessel wall imaging. The vNav-SG approach is capable of compensating for both bulk and localized motions.","journal":"Magnetic Resonance in Medicine","year":2021,"id":198306,"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":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9635,"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":63232,"name":"André van der Kouwe","orcid":"0000-0002-2754-6594","position":1,"is_corresponding":false},{"id":383640,"name":"Fei Han","orcid":"0000-0002-1598-9048","position":2,"is_corresponding":false},{"id":266527,"name":"Jiayu Xiao","orcid":"0000-0001-7478-6534","position":3,"is_corresponding":false},{"id":772990,"name":"Junzhou Chen","orcid":"0000-0002-3388-3503","position":4,"is_corresponding":false},{"id":604766,"name":"Hui Han","orcid":"0000-0002-8890-4295","position":5,"is_corresponding":false},{"id":383639,"name":"Xiaoming Bi","orcid":"0000-0001-6286-9172","position":6,"is_corresponding":false},{"id":289229,"name":"Debiao Li","orcid":"0000-0001-8560-8231","position":7,"is_corresponding":false},{"id":266528,"name":"Zhaoyang Fan","orcid":"0000-0002-2693-0260","position":8,"is_corresponding":false},{"id":383635,"name":"Zhehao Hu","orcid":"0000-0002-5813-2925","position":0,"is_corresponding":true}],"reference_count":30,"raw_metadata":null,"created_at":"2026-07-18T23:50:27.616568Z","pmid":"33768617","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":[]}