Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI
Year: 2019
Type: article
Abstract: OBJECTIVES: Standardization is an important milestone in the validation of DWI-based parameters as imaging biomarkers for renal disease. Here, we propose technical recommendations on three variants of renal DWI, monoexponential DWI, IVIM and DTI, as well as associated MRI biomarkers (ADC, D, D*, f, FA and MD) to aid ongoing international efforts on methodological harmonization. MATERIALS AND METHODS: Reported DWI biomarkers from 194 prior renal DWI studies were extracted and Pearson correlations between diffusion biomarkers and protocol parameters were computed. Based on the literature review, surveys were designed for the consensus building. Survey data were collected via Delphi consensus process on renal DWI preparation, acquisition, analysis, and reporting. Consensus was defined as ≥ 75% agreement. RESULTS: Correlations were observed between reported diffusion biomarkers and protocol parameters. Out of 87 survey questions, 57 achieved consensus resolution, while many of the remaining questions were resolved by preference (65-74% agreement). Summary of the literature and survey data as well as recommendations for the preparation, acquisition, processing and reporting of renal DWI were provided. DISCUSSION: The consensus-based technical recommendations for renal DWI aim to facilitate inter-site harmonization and increase clinical impact of the technique on a larger scale by setting a framework for acquisition protocols for future renal DWI studies. We anticipate an iterative process with continuous updating of the recommendations according to progress in the field.
Authors: Alexandra Ljimani, Anna Caroli, Christoffer Laustsen, Susan Francis, Iosif Alexandru Mendichovszky, Octavia Bane, Fabio Nery, Kanishka Sharma, Andreas Pohlmann, Ilona A. Dekkers, Jean-Paul Vallee, Katja Derlin, Mike Notohamiprodjo, Ruth P. Lim, Stefano Palmucci, Suraj D. Serai, Joao Periquito, Zhen Jane Wang, Martijn Froeling, Harriet C. Thoeny, Pottumarthi Prasad, Moritz Schneider, Thoralf Niendorf, Pim Pullens, Steven Sourbron, Eric E. Sigmund
Institutions: Heinrich Heine University Düsseldorf, Mario Negri Institute for Pharmacological Research, Aarhus University, University of Nottingham, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Icahn School of Medicine at Mount Sinai, University College London, University of Leeds, Max Delbrück Center, Leiden University Medical Center, University of Geneva, University Hospital of Geneva, Medizinische Hochschule Hannover, Universitätsklinikum Tübingen, The University of Melbourne, Austin Hospital, Austin Health, University of Catania, Policlinico Universitario di Catania, Azienda Ospedaliero Universitaria Policlinico "G.Rodolico - San Marco", Children's Hospital of Philadelphia, University of California, San Francisco, University Medical Center Utrecht, University of Fribourg, HFR Freiburg Kantonsspital, Endeavor Health, LMU Klinikum, German Center for Lung Research, Ludwig-Maximilians-Universität München, Ghent University Hospital, Ghent University, NYU Langone Health, Center for Advanced Imaging Innovation and Research, New York University
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,140
Funders: European Federation of Pharmaceutical Industries and Associations, European Commission, European Cooperation in Science and Technology, Deutsche Forschungsgemeinschaft, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Bundesministerium für Bildung und Forschung, Bundesministerium für Forschung und Technologie, National Institutes of Health, Swiss Re Foundation, Medical Research Council, National Institute of Diabetes and Digestive and Kidney Diseases, H2020 European Research Council
Awards: G2437639666, G345564235, UK Renal Imaging Network (UKRIN): Enabling clinical translation of functional MRI for kidney disease, G4515678777, G5219346279, Biomarker Enterprise to Attack DKD - Sofia ref.: 115974, Quantification of Renal Perfusion, Diffusion and Hypoxia Using Advanced MRI Methods for Assessment of Renal Transplant Dysfunction, G57705007, G5866284900, G5866356714, Renal diffusion MRI in chronic kidney disease: a multi-centric approach, G7497174231, G7880812693, G8174659621, G8389278150
OpenAlex ID: W2985142004