{"doi":"10.1002/mrm.70074","title":"Volumetric thermometry in moving tissues using stack‐of‐radial <scp>MRI</scp> and an image‐navigated multi‐baseline proton resonance frequency shift method","abstract":"PURPOSE: To develop and evaluate a volumetric proton resonance frequency shift (PRF)-based thermometry method for monitoring thermal ablation in moving tissues. METHODS: A golden-angle-ordered 3D stack-of-radial MRI sequence was combined with an image-navigated multi-baseline (iNAV-MB) PRF method to reconstruct motion-compensated 3D temperature maps with high spatiotemporal resolution and volumetric coverage. Two radial MRI reconstruction techniques, k-space weighted image contrast filter (KWIC) and golden-angle radial sparse parallel (GRASP) MRI, were implemented and compared within a sliding window reconstruction framework. Ex vivo motion phantom experiments were performed with high-intensity focused ultrasound ablation to evaluate motion tracking and temperature accuracy using input motion waveforms and temperature probe readings as references. In vivo non-heating swine experiments were conducted to assess temperature mapping stability in 3D liver regions of interest. RESULTS: , and effective temporal resolution of 0.98 s/volume. In ex vivo high-intensity focused ultrasound experiments, motion tracking achieved correlation coefficients of 0.951 and 0.973, and temporal mean absolute errors were 1.80°C and 1.44°C using KWIC and GRASP, respectively. In vivo experiments demonstrated improvements in voxel-wise temperature temporal SD from a median of 8.03 to 3.85°C (KWIC) and from a median of 7.23 to 2.37°C (GRASP), compared to single-baseline PRF. CONCLUSION: The proposed stack-of-radial iNAV-MB volumetric PRF thermometry framework can reliably track respiratory motion and map ablation-associated temperature change. This framework has the potential to improve MRI-guided thermal ablation in moving tissues.","journal":"Magnetic Resonance in Medicine","year":2025,"id":528831,"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":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9554,"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":736001,"name":"Shu‐Fu Shih","orcid":"0000-0002-3812-9091","position":1,"is_corresponding":false},{"id":1407566,"name":"Omar Curiel","orcid":null,"position":2,"is_corresponding":false},{"id":342028,"name":"Tsu‐Chin Tsao","orcid":"0000-0003-2087-6221","position":3,"is_corresponding":false},{"id":1023184,"name":"David Lu","orcid":"0000-0002-3263-4476","position":4,"is_corresponding":false},{"id":1407124,"name":"Jason Chiang","orcid":"0000-0002-4370-8063","position":5,"is_corresponding":false},{"id":449705,"name":"Holden H. Wu","orcid":"0000-0002-2585-5916","position":6,"is_corresponding":false},{"id":1407123,"name":"Qing Dai","orcid":"0000-0002-3800-1573","position":0,"is_corresponding":true}],"reference_count":66,"raw_metadata":null,"created_at":"2026-07-19T02:50:52.565868Z","pmid":"40931535","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":[]}