{"doi":"10.1002/mrm.29365","title":"Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla","abstract":"<jats:sec>\n                    <jats:title>Purpose</jats:title>\n                    <jats:p>To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods</jats:title>\n                    <jats:p>Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests).</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Results</jats:title>\n                    <jats:p>Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of  and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion</jats:title>\n                    <jats:p>For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.</jats:p>\n                  </jats:sec>","journal":"Magnetic Resonance in Medicine","year":2022,"id":619057,"datarank":0.3958585994422889,"base_score":2.639057329615259,"endowment":2.639057329615259,"self_citation_contribution":0.3958585994422889,"citation_network_contribution":0.0,"self_endowment_contribution":0.3958585994422889,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":13,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1597398,"name":"Anita Karsa","orcid":"0000-0002-8648-3853","position":1,"is_corresponding":false},{"id":273942,"name":"Francesco Grussu","orcid":"0000-0002-0945-3909","position":2,"is_corresponding":false},{"id":356549,"name":"Marco Battiston","orcid":"0000-0003-2231-2251","position":3,"is_corresponding":false},{"id":628031,"name":"Marios Yiannakas","orcid":"0000-0003-4986-446X","position":4,"is_corresponding":false},{"id":12944,"name":"David L. Thomas","orcid":"0000-0003-1491-1641","position":5,"is_corresponding":false},{"id":1161227,"name":"Karin Shmueli","orcid":"0000-0001-7520-2975","position":6,"is_corresponding":false},{"id":1030781,"name":"Emma Biondetti","orcid":"0000-0001-6727-0935","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Multi‐echo quantitative susceptibility mapping: how to combine echoes for accuracy and precision at 3 Tesla","abstract":"<jats:sec>\n                    <jats:title>Purpose</jats:title>\n                    <jats:p>To compare different multi‐echo combination methods for MRI QSM. Given the current lack of consensus, we aimed to elucidate how to optimally combine multi‐echo gradient‐recalled echo signal phase information, either before or after applying Laplacian‐base methods (LBMs) for phase unwrapping or background field removal.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods</jats:title>\n                    <jats:p>Multi‐echo gradient‐recalled echo data were simulated in a numerical head phantom, and multi‐echo gradient‐recalled echo images were acquired at 3 Tesla in 10 healthy volunteers. To enable image‐based estimation of gradient‐recalled echo signal noise, 5 volunteers were scanned twice in the same session without repositioning. Five QSM processing pipelines were designed: 1 applied nonlinear phase fitting over TEs before LBMs; 2 applied LBMs to the TE‐dependent phase and then combined multiple TEs via either TE‐weighted or SNR‐weighted averaging; and 2 calculated TE‐dependent susceptibility maps via either multi‐step or single‐step QSM and then combined multiple TEs via magnitude‐weighted averaging. Results from different pipelines were compared using visual inspection; summary statistics of susceptibility in deep gray matter, white matter, and venous regions; phase noise maps (error propagation theory); and, in the healthy volunteers, regional fixed bias analysis (Bland–Altman) and regional differences between the means (nonparametric tests).</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Results</jats:title>\n                    <jats:p>Nonlinearly fitting the multi‐echo phase over TEs before applying LBMs provided the highest regional accuracy of  and the lowest phase noise propagation compared to averaging the LBM‐processed TE‐dependent phase. This result was especially pertinent in high‐susceptibility venous regions.</jats:p>\n                  </jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion</jats:title>\n                    <jats:p>For multi‐echo QSM, we recommend combining the signal phase by nonlinear fitting before applying LBMs.</jats:p>\n                  </jats:sec>","is_dataset_classified":null,"base_score":2.639057329615259,"endowment":2.639057329615259,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"35766450","pmcid":"PMC9545116","openalex_id":"https://openalex.org/W4283719622","authors":[],"funders":[{"funder_name":"Government of Catalonia","grant_id":"2020 BP 00117","title":null},{"funder_name":"UK Research and Innovation","grant_id":"EP/L016478/1","title":"EPSRC Centre for Doctoral Training in Medical Imaging"},{"funder_name":"European Commission","grant_id":"770939","title":"Developing Integrated Susceptibility and Conductivity MRI for Next Generation Structural and Functional Neuroimaging"}],"total_grants":3,"fwci":1.4317,"citation_percentile":0.80027927,"influential_citations":0,"citation_trend":[{"year":2022,"count":1},{"year":2023,"count":2},{"year":2024,"count":4},{"year":2025,"count":4},{"year":2026,"count":2}],"oa_status":"hybrid","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.1002/mrm.29365","host_type":"journal"},{"url":"https://doi.org/10.1002/mrm.29365","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.29365","host_type":"publisher"},{"url":"https://onlinelibrary.wiley.com/doi/full-xml/10.1002/mrm.29365","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/35766450","host_type":"repository"},{"url":"https://discovery.ucl.ac.uk/id/eprint/10151363/","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/9545116","host_type":"repository"},{"url":"https://europepmc.org/articles/PMC9545116","host_type":"Europe_PMC"},{"url":"https://europepmc.org/articles/PMC9545116?pdf=render","host_type":"Europe_PMC"},{"url":"https://doi.org/10.1101/2021.06.14.448385","host_type":""},{"url":"https://www.biorxiv.org/content/biorxiv/early/2021/06/14/2021.06.14.448385.full.pdf","host_type":""},{"url":"http://dx.doi.org/10.1002/mrm.29365","host_type":""},{"url":"https://hdl.handle.net/11351/8177","host_type":""},{"url":"https://hdl.handle.net/11564/798313","host_type":""},{"url":"https://onlinelibrary.wiley.com/doi/10.1002/mrm.29365","host_type":""},{"url":"http://hdl.handle.net/11351/8177","host_type":""},{"url":"https://discovery-pp.ucl.ac.uk/id/eprint/10151363/","host_type":""}],"fields_of_study":["Advanced MRI Techniques and Applications","Functional Brain Connectivity Studies","Advanced Neuroimaging Techniques and Applications","03 medical and health sciences","0302 clinical medicine","Brain","Brain Mapping","Humans","Image Processing, Computer-Assisted","Magnetic Resonance Imaging","Phantoms, Imaging","White Matter"],"mesh_terms":["Brain","Brain Mapping","Humans","Image Processing, Computer-Assisted","Magnetic Resonance Imaging","Phantoms, Imaging","White Matter"],"keywords":["Quantitative susceptibility mapping","Echo (communications protocol)","Imaging phantom","Gradient echo","Nuclear magnetic resonance","Computer science","Physics","Nuclear medicine","Magnetic resonance imaging","Medicine","Radiology","MRI","Multi-echo Qsm","Brain Mapping","Phantoms, Imaging","Otros calificadores::Otros calificadores::Otros calificadores::/diagnóstico por imagen","Other subheadings::Other subheadings::Other subheadings::/diagnostic imaging","TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::tomografía::imagen por resonancia magnética","Brain","Cervell - Imatgeria","White Matter","Cartografia cerebral","ANATOMY::Nervous System::Central Nervous System::Brain","TÉCNICAS Y EQUIPOS ANALÍTICOS, DIAGNÓSTICOS Y TERAPÉUTICOS::diagnóstico::técnicas y procedimientos diagnósticos::diagnóstico por imagen::neuroimágenes::neuroimágenes funcionales::mapeo encefálico","MRI; 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