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Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography
PURPOSE: To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness. METHODS: First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postp...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3847077/ https://www.ncbi.nlm.nih.gov/pubmed/24312570 http://dx.doi.org/10.1371/journal.pone.0081668 |
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author | Murphy, Matthew C. Huston, John Jack, Clifford R. Glaser, Kevin J. Senjem, Matthew L. Chen, Jun Manduca, Armando Felmlee, Joel P. Ehman, Richard L. |
author_facet | Murphy, Matthew C. Huston, John Jack, Clifford R. Glaser, Kevin J. Senjem, Matthew L. Chen, Jun Manduca, Armando Felmlee, Joel P. Ehman, Richard L. |
author_sort | Murphy, Matthew C. |
collection | PubMed |
description | PURPOSE: To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness. METHODS: First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects. RESULTS: This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual. CONCLUSION: The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain’s mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases. |
format | Online Article Text |
id | pubmed-3847077 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-38470772013-12-05 Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography Murphy, Matthew C. Huston, John Jack, Clifford R. Glaser, Kevin J. Senjem, Matthew L. Chen, Jun Manduca, Armando Felmlee, Joel P. Ehman, Richard L. PLoS One Research Article PURPOSE: To develop a reliable magnetic resonance elastography (MRE)-based method for measuring regional brain stiffness. METHODS: First, simulation studies were used to demonstrate how stiffness measurements can be biased by changes in brain morphometry, such as those due to atrophy. Adaptive postprocessing methods were created that significantly reduce the spatial extent of edge artifacts and eliminate atrophy-related bias. Second, a pipeline for regional brain stiffness measurement was developed and evaluated for test-retest reliability in 10 healthy control subjects. RESULTS: This technique indicates high test-retest repeatability with a typical coefficient of variation of less than 1% for global brain stiffness and less than 2% for the lobes of the brain and the cerebellum. Furthermore, this study reveals that the brain possesses a characteristic topography of mechanical properties, and also that lobar stiffness measurements tend to correlate with one another within an individual. CONCLUSION: The methods presented in this work are resistant to noise- and edge-related biases that are common in the field of brain MRE, demonstrate high test-retest reliability, and provide independent regional stiffness measurements. This pipeline will allow future investigations to measure changes to the brain’s mechanical properties and how they relate to the characteristic topographies that are typical of many neurologic diseases. Public Library of Science 2013-12-02 /pmc/articles/PMC3847077/ /pubmed/24312570 http://dx.doi.org/10.1371/journal.pone.0081668 Text en © 2013 Murphy 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, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Murphy, Matthew C. Huston, John Jack, Clifford R. Glaser, Kevin J. Senjem, Matthew L. Chen, Jun Manduca, Armando Felmlee, Joel P. Ehman, Richard L. Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title | Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title_full | Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title_fullStr | Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title_full_unstemmed | Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title_short | Measuring the Characteristic Topography of Brain Stiffness with Magnetic Resonance Elastography |
title_sort | measuring the characteristic topography of brain stiffness with magnetic resonance elastography |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3847077/ https://www.ncbi.nlm.nih.gov/pubmed/24312570 http://dx.doi.org/10.1371/journal.pone.0081668 |
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