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Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue

PURPOSE: To investigate the sensitivity of diffusion‐MR signal to microstructural change in muscle tissue associated with pathology, and recommend optimal acquisition parameters. METHODS: We employ Monte‐Carlo simulation of diffusing spins in hierarchical tissue to generate synthetic diffusion‐weigh...

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Autores principales: Hall, Matt G., Clark, Chris A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6093262/
https://www.ncbi.nlm.nih.gov/pubmed/27667781
http://dx.doi.org/10.1002/mrm.26469
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author Hall, Matt G.
Clark, Chris A.
author_facet Hall, Matt G.
Clark, Chris A.
author_sort Hall, Matt G.
collection PubMed
description PURPOSE: To investigate the sensitivity of diffusion‐MR signal to microstructural change in muscle tissue associated with pathology, and recommend optimal acquisition parameters. METHODS: We employ Monte‐Carlo simulation of diffusing spins in hierarchical tissue to generate synthetic diffusion‐weighted signal curves over a wide range of scan parameters. Curves are analyzed using entropy—a measure of curve complexity. Entropy change between a baseline and various microstructural scenarios is investigated. We find acquisitions that optimize entropy difference in each scenario. RESULTS: Permeability changes have a large effect on the diffusion‐weighted signal curve. Muscle fiber atrophy is also important, although differentiating between mechanisms is challenging. Several acquisitions over a range of diffusion times is optimal for imaging microstructural change in muscle tissue. Sensitivity to permeability is optimized for high gradient strengths, but sensitivity to other scenarios is optimal at other values. CONCLUSIONS: The diffusion‐attenuated signal is sensitive to the microstructural changes, but the changes are subtle. Taking full advantage of the changes to the overall curve requires a set of acquisitions over a range of diffusion times. Permeability causes the largest changes, but even the very subtle changes associated with fiber radius distribution change the curves more than noise alone. Magn Reson Med 78:1187–1198, 2017. © 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‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
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spelling pubmed-60932622018-08-20 Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue Hall, Matt G. Clark, Chris A. Magn Reson Med Full Papers—Computer Processing and Modeling PURPOSE: To investigate the sensitivity of diffusion‐MR signal to microstructural change in muscle tissue associated with pathology, and recommend optimal acquisition parameters. METHODS: We employ Monte‐Carlo simulation of diffusing spins in hierarchical tissue to generate synthetic diffusion‐weighted signal curves over a wide range of scan parameters. Curves are analyzed using entropy—a measure of curve complexity. Entropy change between a baseline and various microstructural scenarios is investigated. We find acquisitions that optimize entropy difference in each scenario. RESULTS: Permeability changes have a large effect on the diffusion‐weighted signal curve. Muscle fiber atrophy is also important, although differentiating between mechanisms is challenging. Several acquisitions over a range of diffusion times is optimal for imaging microstructural change in muscle tissue. Sensitivity to permeability is optimized for high gradient strengths, but sensitivity to other scenarios is optimal at other values. CONCLUSIONS: The diffusion‐attenuated signal is sensitive to the microstructural changes, but the changes are subtle. Taking full advantage of the changes to the overall curve requires a set of acquisitions over a range of diffusion times. Permeability causes the largest changes, but even the very subtle changes associated with fiber radius distribution change the curves more than noise alone. Magn Reson Med 78:1187–1198, 2017. © 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‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. John Wiley and Sons Inc. 2016-09-25 2017-09 /pmc/articles/PMC6093262/ /pubmed/27667781 http://dx.doi.org/10.1002/mrm.26469 Text en © 2016 International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Full Papers—Computer Processing and Modeling
Hall, Matt G.
Clark, Chris A.
Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title_full Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title_fullStr Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title_full_unstemmed Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title_short Diffusion in hierarchical systems: A simulation study in models of healthy and diseased muscle tissue
title_sort diffusion in hierarchical systems: a simulation study in models of healthy and diseased muscle tissue
topic Full Papers—Computer Processing and Modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6093262/
https://www.ncbi.nlm.nih.gov/pubmed/27667781
http://dx.doi.org/10.1002/mrm.26469
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