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Validation of a standardized MRI method for liver fat and T2* quantification

PURPOSE: Several studies have demonstrated the accuracy, precision, and reproducibility of proton density fat fraction (PDFF) quantification using vendor-specific image acquisition protocols and PDFF estimation methods. The purpose of this work is to validate a confounder-corrected, cross-vendor, cr...

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Autores principales: Hutton, Chloe, Gyngell, Michael L., Milanesi, Matteo, Bagur, Alexandre, Brady, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6147490/
https://www.ncbi.nlm.nih.gov/pubmed/30235288
http://dx.doi.org/10.1371/journal.pone.0204175
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author Hutton, Chloe
Gyngell, Michael L.
Milanesi, Matteo
Bagur, Alexandre
Brady, Michael
author_facet Hutton, Chloe
Gyngell, Michael L.
Milanesi, Matteo
Bagur, Alexandre
Brady, Michael
author_sort Hutton, Chloe
collection PubMed
description PURPOSE: Several studies have demonstrated the accuracy, precision, and reproducibility of proton density fat fraction (PDFF) quantification using vendor-specific image acquisition protocols and PDFF estimation methods. The purpose of this work is to validate a confounder-corrected, cross-vendor, cross field-strength, in-house variant LMS IDEAL of the IDEAL method licensed from the University of Wisconsin, which has been developed for routine clinical use. METHODS: LMS IDEAL is implemented using a combination of patented and/or published acquisition and some novel model fitting methods required to correct confounds which result from the imaging and estimation processes, including: water-fat ambiguity; T2* relaxation; multi-peak fat modelling; main field inhomogeneity; T1 and noise bias; bipolar readout gradients; and eddy currents. LMS IDEAL has been designed to use image acquisition protocols that can be installed on most MRI scanners and cloud-based image processing to provide fast, standardized clinical results. Publicly available phantom data were used to validate LMS IDEAL PDFF calculations against results from originally published IDEAL methodology. LMS PDFF and T2* measurements were also compared with an independent technique in human volunteer data (n = 179) acquired as part of the UK Biobank study. RESULTS: We demonstrate excellent agreement of LMS IDEAL across vendors, field strengths, and over a wide range of PDFF and T2* values in the phantom study. The performance of LMS IDEAL was then assessed in vivo against widely accepted PDFF and T2* estimation methods (LMS Dixon and LMS T2*, respectively), demonstrating the robustness of LMS IDEAL to potential sources of error. CONCLUSION: The development and clinical validation of the LMS IDEAL algorithm as a chemical shift-encoded MRI method for PDFF and T2* estimation contributes towards robust, unbiased applications for quantification of hepatic steatosis and iron overload, which are key features of chronic liver disease.
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spelling pubmed-61474902018-10-08 Validation of a standardized MRI method for liver fat and T2* quantification Hutton, Chloe Gyngell, Michael L. Milanesi, Matteo Bagur, Alexandre Brady, Michael PLoS One Research Article PURPOSE: Several studies have demonstrated the accuracy, precision, and reproducibility of proton density fat fraction (PDFF) quantification using vendor-specific image acquisition protocols and PDFF estimation methods. The purpose of this work is to validate a confounder-corrected, cross-vendor, cross field-strength, in-house variant LMS IDEAL of the IDEAL method licensed from the University of Wisconsin, which has been developed for routine clinical use. METHODS: LMS IDEAL is implemented using a combination of patented and/or published acquisition and some novel model fitting methods required to correct confounds which result from the imaging and estimation processes, including: water-fat ambiguity; T2* relaxation; multi-peak fat modelling; main field inhomogeneity; T1 and noise bias; bipolar readout gradients; and eddy currents. LMS IDEAL has been designed to use image acquisition protocols that can be installed on most MRI scanners and cloud-based image processing to provide fast, standardized clinical results. Publicly available phantom data were used to validate LMS IDEAL PDFF calculations against results from originally published IDEAL methodology. LMS PDFF and T2* measurements were also compared with an independent technique in human volunteer data (n = 179) acquired as part of the UK Biobank study. RESULTS: We demonstrate excellent agreement of LMS IDEAL across vendors, field strengths, and over a wide range of PDFF and T2* values in the phantom study. The performance of LMS IDEAL was then assessed in vivo against widely accepted PDFF and T2* estimation methods (LMS Dixon and LMS T2*, respectively), demonstrating the robustness of LMS IDEAL to potential sources of error. CONCLUSION: The development and clinical validation of the LMS IDEAL algorithm as a chemical shift-encoded MRI method for PDFF and T2* estimation contributes towards robust, unbiased applications for quantification of hepatic steatosis and iron overload, which are key features of chronic liver disease. Public Library of Science 2018-09-20 /pmc/articles/PMC6147490/ /pubmed/30235288 http://dx.doi.org/10.1371/journal.pone.0204175 Text en © 2018 Hutton et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Hutton, Chloe
Gyngell, Michael L.
Milanesi, Matteo
Bagur, Alexandre
Brady, Michael
Validation of a standardized MRI method for liver fat and T2* quantification
title Validation of a standardized MRI method for liver fat and T2* quantification
title_full Validation of a standardized MRI method for liver fat and T2* quantification
title_fullStr Validation of a standardized MRI method for liver fat and T2* quantification
title_full_unstemmed Validation of a standardized MRI method for liver fat and T2* quantification
title_short Validation of a standardized MRI method for liver fat and T2* quantification
title_sort validation of a standardized mri method for liver fat and t2* quantification
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6147490/
https://www.ncbi.nlm.nih.gov/pubmed/30235288
http://dx.doi.org/10.1371/journal.pone.0204175
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