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Evaluation of non‐Gaussian diffusion in cardiac MRI
PURPOSE: The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Ga...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366286/ https://www.ncbi.nlm.nih.gov/pubmed/27670633 http://dx.doi.org/10.1002/mrm.26466 |
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author | McClymont, Darryl Teh, Irvin Carruth, Eric Omens, Jeffrey McCulloch, Andrew Whittington, Hannah J. Kohl, Peter Grau, Vicente Schneider, Jürgen E. |
author_facet | McClymont, Darryl Teh, Irvin Carruth, Eric Omens, Jeffrey McCulloch, Andrew Whittington, Hannah J. Kohl, Peter Grau, Vicente Schneider, Jürgen E. |
author_sort | McClymont, Darryl |
collection | PubMed |
description | PURPOSE: The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Gaussian modeling. The aim of this study was to investigate non‐Gaussian diffusion in healthy and hypertrophic hearts. METHODS: Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion‐weighted images were acquired at b‐values up to 10,000 s/mm(2). Models of diffusion were fit to the data and ranked based on the Akaike information criterion. RESULTS: The diffusion tensor was ranked best at b‐values up to 2000 s/mm(2) but reflected the signal poorly in the high b‐value regime, in which the best model was a non‐Gaussian “beta distribution” model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet‐normal directions. CONCLUSION: Non‐Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174–1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. |
format | Online Article Text |
id | pubmed-5366286 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-53662862017-09-15 Evaluation of non‐Gaussian diffusion in cardiac MRI McClymont, Darryl Teh, Irvin Carruth, Eric Omens, Jeffrey McCulloch, Andrew Whittington, Hannah J. Kohl, Peter Grau, Vicente Schneider, Jürgen E. Magn Reson Med Full Papers—Computer Processing and Modeling PURPOSE: The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Gaussian modeling. The aim of this study was to investigate non‐Gaussian diffusion in healthy and hypertrophic hearts. METHODS: Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion‐weighted images were acquired at b‐values up to 10,000 s/mm(2). Models of diffusion were fit to the data and ranked based on the Akaike information criterion. RESULTS: The diffusion tensor was ranked best at b‐values up to 2000 s/mm(2) but reflected the signal poorly in the high b‐value regime, in which the best model was a non‐Gaussian “beta distribution” model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet‐normal directions. CONCLUSION: Non‐Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart. Magn Reson Med 78:1174–1186, 2017. © 2016 International Society for Magnetic Resonance in Medicine. John Wiley and Sons Inc. 2016-09-26 2017-09 /pmc/articles/PMC5366286/ /pubmed/27670633 http://dx.doi.org/10.1002/mrm.26466 Text en © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Full Papers—Computer Processing and Modeling McClymont, Darryl Teh, Irvin Carruth, Eric Omens, Jeffrey McCulloch, Andrew Whittington, Hannah J. Kohl, Peter Grau, Vicente Schneider, Jürgen E. Evaluation of non‐Gaussian diffusion in cardiac MRI |
title | Evaluation of non‐Gaussian diffusion in cardiac MRI |
title_full | Evaluation of non‐Gaussian diffusion in cardiac MRI |
title_fullStr | Evaluation of non‐Gaussian diffusion in cardiac MRI |
title_full_unstemmed | Evaluation of non‐Gaussian diffusion in cardiac MRI |
title_short | Evaluation of non‐Gaussian diffusion in cardiac MRI |
title_sort | evaluation of non‐gaussian diffusion in cardiac mri |
topic | Full Papers—Computer Processing and Modeling |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5366286/ https://www.ncbi.nlm.nih.gov/pubmed/27670633 http://dx.doi.org/10.1002/mrm.26466 |
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