Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/25263
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dc.contributor.authorde Boer, Anneloes-
dc.contributor.authorVilla, Giulia-
dc.contributor.authorBane, Octavia-
dc.contributor.authorBock, Michael-
dc.contributor.authorCox, Eleanor F-
dc.contributor.authorDekkers, Ilona A-
dc.contributor.authorEckerbom, Per-
dc.contributor.authorFernández-Seara, Maria A-
dc.contributor.authorFrancis, Susan T-
dc.contributor.authorHaddock, Bryan-
dc.contributor.authorHall, Michael E-
dc.contributor.authorHall Barrientos, Pauline-
dc.contributor.authorHermann, Ingo-
dc.contributor.authorHockings, Paul D-
dc.contributor.authorLamb, Hildo J-
dc.contributor.authorLaustsen, Christoffer-
dc.contributor.authorLim, Ruth P-
dc.contributor.authorMorris, David M-
dc.contributor.authorRinggaard, Steffen-
dc.contributor.authorSerai, Suraj D-
dc.contributor.authorSharma, Kanishka-
dc.contributor.authorSourbron, Steven-
dc.contributor.authorTakehara, Yasuo-
dc.contributor.authorWentland, Andrew L-
dc.contributor.authorWolf, Marcos-
dc.contributor.authorZöllner, Frank G-
dc.contributor.authorNery, Fabio-
dc.contributor.authorCaroli, Anna-
dc.date2020-11-02-
dc.date.accessioned2020-11-10T03:07:39Z-
dc.date.available2020-11-10T03:07:39Z-
dc.date.issued2022-
dc.identifier.citationJournal of magnetic resonance imaging : JMRI 2022; 55(2): 323-335en
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/25263-
dc.description.abstractPhase-contrast (PC) MRI is a feasible and valid noninvasive technique to measure renal artery blood flow, showing potential to support diagnosis and monitoring of renal diseases. However, the variability in measured renal blood flow values across studies is large, most likely due to differences in PC-MRI acquisition and processing. Standardized acquisition and processing protocols are therefore needed to minimize this variability and maximize the potential of renal PC-MRI as a clinically useful tool. To build technical recommendations for the acquisition, processing, and analysis of renal 2D PC-MRI data in human subjects to promote standardization of renal blood flow measurements and facilitate the comparability of results across scanners and in multicenter clinical studies. Systematic consensus process using a modified Delphi method. Not applicable. Renal fast gradient echo-based 2D PC-MRI. An international panel of 27 experts from Europe, the USA, Australia, and Japan with 6 (interquartile range 4-10) years of experience in 2D PC-MRI formulated consensus statements on renal 2D PC-MRI in two rounds of surveys. Starting from a recently published systematic review article, literature-based and data-driven statements regarding patient preparation, hardware, acquisition protocol, analysis steps, and data reporting were formulated. Consensus was defined as ≥75% unanimity in response, and a clear preference was defined as 60-74% agreement among the experts. Among 60 statements, 57 (95%) achieved consensus after the second-round survey, while the remaining three showed a clear preference. Consensus statements resulted in specific recommendations for subject preparation, 2D renal PC-MRI data acquisition, processing, and reporting. These recommendations might promote a widespread adoption of renal PC-MRI, and may help foster the set-up of multicenter studies aimed at defining reference values and building larger and more definitive evidence, and will facilitate clinical translation of PC-MRI. 1 TECHNICAL EFFICACY STAGE: 1.en
dc.language.isoeng-
dc.subjectconsensusen
dc.subjectkidneyen
dc.subjectphase-contrast MRIen
dc.subjectrenal blood flowen
dc.subjectstandardizationen
dc.titleConsensus-Based Technical Recommendations for Clinical Translation of Renal Phase Contrast MRI.en
dc.typeJournal Articleen
dc.identifier.journaltitleJournal of Magnetic Resonance Imaging : JMRIen
dc.identifier.affiliationDepartment of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlandsen
dc.identifier.affiliationDepartment of Radiology, Austin Health, Heidelberg, Victoria, Australiaen
dc.identifier.affiliationDepartment of Bioengineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italyen
dc.identifier.affiliationDepartments of Radiology, Surgery and Medicine, The University of Melbourne, Parkville, Victoria, Australiaen
dc.identifier.affiliationBiomedical Engineering and Imaging Institute/Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USAen
dc.identifier.affiliationDepartment of Radiology - Medical Physics, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germanyen
dc.identifier.affiliationSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UKen
dc.identifier.affiliationDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlandsen
dc.identifier.affiliationDepartment of Surgical Sciences, Uppsala University, Uppsala, Swedenen
dc.identifier.affiliationDepartment of Radiology, Clínica Universidad de Navarra, Pamplona, Spainen
dc.identifier.affiliationSir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UKen
dc.identifier.affiliationDepartment of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmarken
dc.identifier.affiliationDepartment of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USAen
dc.identifier.affiliationDepartment of Clinical Physics and Bioengineering, NHS Greater Glasgow and Clyde, Glasgow, UKen
dc.identifier.affiliationComputer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germanyen
dc.identifier.affiliationAntaros Medical, BioVenture Hub, Mölndal, Swedenen
dc.identifier.affiliationDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlandsen
dc.identifier.affiliationDepartment of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmarken
dc.identifier.affiliationCentre for Inflammation Research, University of Edinburgh, Edinburgh Bioquarter, Edinburgh, UKen
dc.identifier.affiliationDepartment of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmarken
dc.identifier.affiliationDepartment of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USAen
dc.identifier.affiliationDepartment of Imaging, Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UKen
dc.identifier.affiliationDepartment of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University, Graduate School of Medicine, Nagoya, Japanen
dc.identifier.affiliationDepartment of Radiology, Stanford University, Stanford, California, USAen
dc.identifier.affiliationHigh Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austriaen
dc.identifier.affiliationComputer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germanyen
dc.identifier.affiliationDevelopmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UKen
dc.identifier.affiliationDepartment of Bioengineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italyen
dc.identifier.doi10.1002/jmri.27419en
dc.type.contentTexten
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dc.identifier.pubmedid33140551-
local.name.researcherLim, Ruth P
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
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crisitem.author.deptRadiology-
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