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Placenta microstructure and microcirculation imaging with diffusion MRI

PURPOSE: To assess which microstructural models best explain the diffusion‐weighted MRI signal in the human placenta. METHODS: The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models wer...

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Autores principales: Slator, Paddy J., Hutter, Jana, McCabe, Laura, Gomes, Ana Dos Santos, Price, Anthony N., Panagiotaki, Eleftheria, Rutherford, Mary A., Hajnal, Joseph V., Alexander, Daniel C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5947291/
https://www.ncbi.nlm.nih.gov/pubmed/29230859
http://dx.doi.org/10.1002/mrm.27036
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author Slator, Paddy J.
Hutter, Jana
McCabe, Laura
Gomes, Ana Dos Santos
Price, Anthony N.
Panagiotaki, Eleftheria
Rutherford, Mary A.
Hajnal, Joseph V.
Alexander, Daniel C.
author_facet Slator, Paddy J.
Hutter, Jana
McCabe, Laura
Gomes, Ana Dos Santos
Price, Anthony N.
Panagiotaki, Eleftheria
Rutherford, Mary A.
Hajnal, Joseph V.
Alexander, Daniel C.
author_sort Slator, Paddy J.
collection PubMed
description PURPOSE: To assess which microstructural models best explain the diffusion‐weighted MRI signal in the human placenta. METHODS: The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models were fit to the data, and ranked using the Bayesian information criterion. RESULTS: Anisotropic extensions to the intravoxel incoherent motion model, which consider the effect of coherent orientation in both microvascular structure and tissue microstructure, consistently had the lowest Bayesian information criterion values. Model parameter maps and model selection results were consistent with the physiology of the placenta and surrounding tissue. CONCLUSION: Anisotropic intravoxel incoherent motion models explain the placental diffusion signal better than apparent diffusion coefficient, intravoxel incoherent motion, and diffusion tensor models, in information theoretic terms, when using this protocol. Future work will aim to determine if model‐derived parameters are sensitive to placental pathologies associated with disorders, such as fetal growth restriction and early‐onset pre‐eclampsia. Magn Reson Med 80:756–766, 2018. © 2017 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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spelling pubmed-59472912018-05-17 Placenta microstructure and microcirculation imaging with diffusion MRI Slator, Paddy J. Hutter, Jana McCabe, Laura Gomes, Ana Dos Santos Price, Anthony N. Panagiotaki, Eleftheria Rutherford, Mary A. Hajnal, Joseph V. Alexander, Daniel C. Magn Reson Med Full Papers—Computer Processing and Modeling PURPOSE: To assess which microstructural models best explain the diffusion‐weighted MRI signal in the human placenta. METHODS: The placentas of nine healthy pregnant subjects were scanned with a multishell, multidirectional diffusion protocol at 3T. A range of multicompartment biophysical models were fit to the data, and ranked using the Bayesian information criterion. RESULTS: Anisotropic extensions to the intravoxel incoherent motion model, which consider the effect of coherent orientation in both microvascular structure and tissue microstructure, consistently had the lowest Bayesian information criterion values. Model parameter maps and model selection results were consistent with the physiology of the placenta and surrounding tissue. CONCLUSION: Anisotropic intravoxel incoherent motion models explain the placental diffusion signal better than apparent diffusion coefficient, intravoxel incoherent motion, and diffusion tensor models, in information theoretic terms, when using this protocol. Future work will aim to determine if model‐derived parameters are sensitive to placental pathologies associated with disorders, such as fetal growth restriction and early‐onset pre‐eclampsia. Magn Reson Med 80:756–766, 2018. © 2017 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 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. John Wiley and Sons Inc. 2017-12-11 2018-08 /pmc/articles/PMC5947291/ /pubmed/29230859 http://dx.doi.org/10.1002/mrm.27036 Text en © 2017 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 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
Slator, Paddy J.
Hutter, Jana
McCabe, Laura
Gomes, Ana Dos Santos
Price, Anthony N.
Panagiotaki, Eleftheria
Rutherford, Mary A.
Hajnal, Joseph V.
Alexander, Daniel C.
Placenta microstructure and microcirculation imaging with diffusion MRI
title Placenta microstructure and microcirculation imaging with diffusion MRI
title_full Placenta microstructure and microcirculation imaging with diffusion MRI
title_fullStr Placenta microstructure and microcirculation imaging with diffusion MRI
title_full_unstemmed Placenta microstructure and microcirculation imaging with diffusion MRI
title_short Placenta microstructure and microcirculation imaging with diffusion MRI
title_sort placenta microstructure and microcirculation imaging with diffusion mri
topic Full Papers—Computer Processing and Modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5947291/
https://www.ncbi.nlm.nih.gov/pubmed/29230859
http://dx.doi.org/10.1002/mrm.27036
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