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Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI.
- Source :
- Magma (New York, N.Y.); vol 33, iss 1, 177-195; 0968-5243
- Publication Year :
- 2020
-
Abstract
- ObjectivesStandardization 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 methodsReported 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.ResultsCorrelations 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.DiscussionThe 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.
Details
- Database :
- OAIster
- Journal :
- Magma (New York, N.Y.); vol 33, iss 1, 177-195; 0968-5243
- Notes :
- application/pdf, Magma (New York, N.Y.) vol 33, iss 1, 177-195 0968-5243
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1287290222
- Document Type :
- Electronic Resource