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MRI-derived bone porosity index correlates to bone composition and mechanical stiffness
The MRI-derived porosity index (PI) is a non-invasively obtained biomarker based on an ultrashort echo time sequence that images both bound and pore water protons in bone, corresponding to water bound to organic collagenous matrix and freely moving water, respectively. This measure is known to stron...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660551/ https://www.ncbi.nlm.nih.gov/pubmed/31372372 http://dx.doi.org/10.1016/j.bonr.2019.100213 |
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author | Hong, Abigail L. Ispiryan, Mikayel Padalkar, Mugdha V. Jones, Brandon C. Batzdorf, Alexandra S. Shetye, Snehal S. Pleshko, Nancy Rajapakse, Chamith S. |
author_facet | Hong, Abigail L. Ispiryan, Mikayel Padalkar, Mugdha V. Jones, Brandon C. Batzdorf, Alexandra S. Shetye, Snehal S. Pleshko, Nancy Rajapakse, Chamith S. |
author_sort | Hong, Abigail L. |
collection | PubMed |
description | The MRI-derived porosity index (PI) is a non-invasively obtained biomarker based on an ultrashort echo time sequence that images both bound and pore water protons in bone, corresponding to water bound to organic collagenous matrix and freely moving water, respectively. This measure is known to strongly correlate with the actual volumetric cortical bone porosity. However, it is unknown whether PI may also be able to directly quantify bone organic composition and/or mechanical properties. We investigated this in human cadaveric tibiae by comparing PI values to near infrared spectral imaging (NIRSI) compositional data and mechanical compression data. Data were obtained from a cohort of eighteen tibiae from male and female donors with a mean ± SD age of 70 ± 21 years. Biomechanical stiffness in compression and NIRSI-derived collagen and bound water content all had significant inverse correlations with PI (r = −0.79, −0.73, and −0.95 and p = 0.002, 0.007, and <0.001, respectively). The MRI-derived bone PI alone was a moderate predictor of bone stiffness (R(2) = 0.63, p = 0.002), and multivariate analyses showed that neither cortical bone cross-sectional area nor NIRSI values improved bone stiffness prediction compared to PI alone. However, NIRSI-obtained collagen and water data together were a moderate predictor of bone stiffness (R(2) = 0.52, p = 0.04). Our data validates the MRI-derived porosity index as a strong predictor of organic composition of bone and a moderate predictor of bone stiffness, and also provides preliminary evidence that NIRSI measures may be useful in future pre-clinical studies on bone pathology. |
format | Online Article Text |
id | pubmed-6660551 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-66605512019-08-01 MRI-derived bone porosity index correlates to bone composition and mechanical stiffness Hong, Abigail L. Ispiryan, Mikayel Padalkar, Mugdha V. Jones, Brandon C. Batzdorf, Alexandra S. Shetye, Snehal S. Pleshko, Nancy Rajapakse, Chamith S. Bone Rep Article The MRI-derived porosity index (PI) is a non-invasively obtained biomarker based on an ultrashort echo time sequence that images both bound and pore water protons in bone, corresponding to water bound to organic collagenous matrix and freely moving water, respectively. This measure is known to strongly correlate with the actual volumetric cortical bone porosity. However, it is unknown whether PI may also be able to directly quantify bone organic composition and/or mechanical properties. We investigated this in human cadaveric tibiae by comparing PI values to near infrared spectral imaging (NIRSI) compositional data and mechanical compression data. Data were obtained from a cohort of eighteen tibiae from male and female donors with a mean ± SD age of 70 ± 21 years. Biomechanical stiffness in compression and NIRSI-derived collagen and bound water content all had significant inverse correlations with PI (r = −0.79, −0.73, and −0.95 and p = 0.002, 0.007, and <0.001, respectively). The MRI-derived bone PI alone was a moderate predictor of bone stiffness (R(2) = 0.63, p = 0.002), and multivariate analyses showed that neither cortical bone cross-sectional area nor NIRSI values improved bone stiffness prediction compared to PI alone. However, NIRSI-obtained collagen and water data together were a moderate predictor of bone stiffness (R(2) = 0.52, p = 0.04). Our data validates the MRI-derived porosity index as a strong predictor of organic composition of bone and a moderate predictor of bone stiffness, and also provides preliminary evidence that NIRSI measures may be useful in future pre-clinical studies on bone pathology. Elsevier 2019-06-26 /pmc/articles/PMC6660551/ /pubmed/31372372 http://dx.doi.org/10.1016/j.bonr.2019.100213 Text en © 2019 The Author(s) http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Hong, Abigail L. Ispiryan, Mikayel Padalkar, Mugdha V. Jones, Brandon C. Batzdorf, Alexandra S. Shetye, Snehal S. Pleshko, Nancy Rajapakse, Chamith S. MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title | MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title_full | MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title_fullStr | MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title_full_unstemmed | MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title_short | MRI-derived bone porosity index correlates to bone composition and mechanical stiffness |
title_sort | mri-derived bone porosity index correlates to bone composition and mechanical stiffness |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6660551/ https://www.ncbi.nlm.nih.gov/pubmed/31372372 http://dx.doi.org/10.1016/j.bonr.2019.100213 |
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