Consensus-Based Technical Recommendations for Clinical Translation of Renal Phase Contrast MRI.


Journal

Journal of magnetic resonance imaging : JMRI
ISSN: 1522-2586
Titre abrégé: J Magn Reson Imaging
Pays: United States
ID NLM: 9105850

Informations de publication

Date de publication:
02 2022
Historique:
revised: 15 10 2020
received: 02 09 2020
accepted: 16 10 2020
pubmed: 4 11 2020
medline: 29 1 2022
entrez: 3 11 2020
Statut: ppublish

Résumé

Phase-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.

Sections du résumé

BACKGROUND
Phase-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.
PURPOSE
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.
STUDY TYPE
Systematic consensus process using a modified Delphi method.
POPULATION
Not applicable.
SEQUENCE FIELD/STRENGTH
Renal fast gradient echo-based 2D PC-MRI.
ASSESSMENT
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.
STATISTICAL TESTS
Consensus was defined as ≥75% unanimity in response, and a clear preference was defined as 60-74% agreement among the experts.
RESULTS
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.
DATA CONCLUSION
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.
LEVEL OF EVIDENCE
1 TECHNICAL EFFICACY STAGE: 1.

Identifiants

pubmed: 33140551
doi: 10.1002/jmri.27419
pmc: PMC9291014
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

323-335

Subventions

Organisme : NIDDK NIH HHS
ID : K08 DK099415
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK113272
Pays : United States
Organisme : Medical Research Council
ID : MR/R02264X/1
Pays : United Kingdom
Organisme : NIGMS NIH HHS
ID : U54 GM115428
Pays : United States
Organisme : NIDDK NIH HHS
ID : F32 DK109591
Pays : United States

Informations de copyright

© 2020 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC. on behalf of International Society for Magnetic Resonance in Medicine.

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Auteurs

Anneloes de Boer (A)

Department of Radiology, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.

Giulia Villa (G)

Department of Bioengineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy.

Octavia Bane (O)

Biomedical Engineering and Imaging Institute/Radiology, Icahn School of Medicine at Mount Sinai, New York, New York, USA.

Michael Bock (M)

Department of Radiology - Medical Physics, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.

Eleanor F Cox (EF)

Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.

Ilona A Dekkers (IA)

Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Per Eckerbom (P)

Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Maria A Fernández-Seara (MA)

Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain.

Susan T Francis (ST)

Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK.

Bryan Haddock (B)

Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

Michael E Hall (ME)

Department of Medicine, University of Mississippi Medical Center, Jackson, Mississippi, USA.

Pauline Hall Barrientos (P)

Department of Clinical Physics and Bioengineering, NHS Greater Glasgow and Clyde, Glasgow, UK.

Ingo Hermann (I)

Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Paul D Hockings (PD)

Antaros Medical, BioVenture Hub, Mölndal, Sweden.

Hildo J Lamb (HJ)

Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Christoffer Laustsen (C)

Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark.

Ruth P Lim (RP)

Departments of Radiology, Surgery and Medicine, The University of Melbourne, Parkville, Victoria, Australia.
Department of Radiology, Austin Health, Heidelberg, Victoria, Australia.

David M Morris (DM)

Centre for Inflammation Research, University of Edinburgh, Edinburgh Bioquarter, Edinburgh, UK.

Steffen Ringgaard (S)

Department of Clinical Medicine, MR Research Centre, Aarhus University, Aarhus, Denmark.

Suraj D Serai (SD)

Department of Radiology, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

Kanishka Sharma (K)

Department of Imaging, Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.

Steven Sourbron (S)

Department of Imaging, Infection, Immunity and Cardiovascular Disease, The University of Sheffield, Sheffield, UK.

Yasuo Takehara (Y)

Department of Fundamental Development for Advanced Low Invasive Diagnostic Imaging, Nagoya University, Graduate School of Medicine, Nagoya, Japan.

Andrew L Wentland (AL)

Department of Radiology, Stanford University, Stanford, California, USA.

Marcos Wolf (M)

High Field MR Center, Center for Medical Physics and Biomedical Engineering, Medical University of Vienna, Vienna, Austria.

Frank G Zöllner (FG)

Computer Assisted Clinical Medicine, Mannheim Institute for Intelligent Systems in Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.

Fabio Nery (F)

Developmental Imaging and Biophysics Section, UCL Great Ormond Street Institute of Child Health, London, UK.

Anna Caroli (A)

Department of Bioengineering, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Bergamo, Italy.

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