{"doi":"10.1002/mrm.30612","title":"Detection of transient tissue displacement using wavelet <scp>MR elastography</scp>: Phantom validation and in vivo human brain repeatability study","abstract":"Abstract Purpose While standard MR elastography (MRE) uses harmonic mechanical waves, there are some applications in which imaging and analysis of transient mechanical motion are of interest. Wavelet MRE has been developed for detecting broadband motion from transient excitation. The goal of this study was to evaluate the accuracy and efficiency of wavelet MRE for transient displacement detection in brain MRE applications. Methods Transient motion was induced in a gel phantom, while MRE images were acquired using bipolar motion‐encoding gradient (MEG) at multiple frequencies (20–200 Hz). Displacements were estimated using (1) combinations of multiple MEGs forming the wavelet MRE and (2) deconvolution from a single MEG. These estimated displacements were used to calculate the MRE phase for each MEG. Correlation ( r 2 ) between the calculated and acquired phases was evaluated. Three healthy volunteers were scanned twice in a clinical scanner using wavelet MRE with an occipital impact. Time‐resolved brain translation, rotation, and maximal principal strain were calculated. Repeatability was assessed both qualitatively and through Pearson correlation. Results Wavelet MRE outperformed standard MRE in displacement estimation, showing higher correlations between calculated and acquired phase, even with fewer phase offsets. In the volunteer study, consistent temporal motion dynamics and spatial maximal principal strain distributions across repeated scans demonstrated the repeatability of wavelet MRE. Conclusion This study validated the accuracy and efficiency of wavelet MRE for broadband motion detection and demonstrated its feasibility and repeatability in vivo. This technique shows promise for advancing our understanding of the injury risks and mechanisms associated with sports‐related head trauma.","journal":"Magnetic Resonance in Medicine","year":2025,"id":568766,"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":0.96,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1112505,"name":"Xiang Shan","orcid":"0009-0005-8606-798X","position":1,"is_corresponding":false},{"id":509704,"name":"Kevin J. Glaser","orcid":"0000-0002-7464-5042","position":2,"is_corresponding":false},{"id":1231457,"name":"Jun Chen","orcid":"0000-0003-4849-4946","position":3,"is_corresponding":false},{"id":545878,"name":"Phillip J. Rossman","orcid":"0000-0002-3245-4934","position":4,"is_corresponding":false},{"id":729547,"name":"Yi Sui","orcid":"0000-0002-8177-1661","position":5,"is_corresponding":false},{"id":253785,"name":"Armando Manduca","orcid":"0000-0002-9411-5671","position":6,"is_corresponding":false},{"id":381140,"name":"John Huston","orcid":"0000-0003-0584-9460","position":7,"is_corresponding":false},{"id":275036,"name":"Richard L. Ehman","orcid":"0000-0001-7041-5074","position":8,"is_corresponding":false},{"id":675121,"name":"Ziying Yin","orcid":"0000-0003-3235-966X","position":9,"is_corresponding":false},{"id":1123241,"name":"Yuan Le","orcid":"0000-0002-1444-8792","position":0,"is_corresponding":true}],"reference_count":20,"raw_metadata":null,"created_at":"2026-07-19T02:56:55.795846Z","pmid":"40534286","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":[]}