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Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk
High-resolution peripheral quantitative computed tomography (HRpQCT) is increasingly used for exploring associations between bone microarchitectural and finite element analysis (FEA) parameters and fracture. We hypothesised that combining bone microarchitectural parameters, geometry, BMD and FEA est...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694037/ https://www.ncbi.nlm.nih.gov/pubmed/31187198 http://dx.doi.org/10.1007/s00223-019-00564-7 |
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author | Westbury, Leo D. Shere, Clare Edwards, Mark H. Cooper, Cyrus Dennison, Elaine M. Ward, Kate A. |
author_facet | Westbury, Leo D. Shere, Clare Edwards, Mark H. Cooper, Cyrus Dennison, Elaine M. Ward, Kate A. |
author_sort | Westbury, Leo D. |
collection | PubMed |
description | High-resolution peripheral quantitative computed tomography (HRpQCT) is increasingly used for exploring associations between bone microarchitectural and finite element analysis (FEA) parameters and fracture. We hypothesised that combining bone microarchitectural parameters, geometry, BMD and FEA estimates of bone strength from HRpQCT may improve discrimination of fragility fractures. The analysis sample comprised of 359 participants (aged 72–81 years) from the Hertfordshire Cohort Study. Fracture history was determined by self-report and vertebral fracture assessment. Participants underwent HRpQCT scans of the distal radius and DXA scans of the proximal femur and lateral spine. Poisson regression with robust variance estimation was used to derive relative risks for the relationship between individual bone microarchitectural and FEA parameters and previous fracture. Cluster analysis of these parameters was then performed to identify phenotypes associated with fracture prevalence. Receiver operating characteristic analysis suggested that bone microarchitectural parameters improved fracture discrimination compared to aBMD alone, whereas further inclusion of FEA parameters resulted in minimal improvements. Cluster analysis (k-means) identified four clusters. The first had lower Young modulus, cortical thickness, cortical volumetric density and Von Mises stresses compared to the wider sample; fracture rates were only significantly greater among women (relative risk [95%CI] compared to lowest risk cluster: 2.55 [1.28, 5.07], p = 0.008). The second cluster in women had greater trabecular separation, lower trabecular volumetric density and lower trabecular load with an increase in fracture rate compared to lowest risk cluster (1.93 [0.98, 3.78], p = 0.057). These findings may help inform intervention strategies for the prevention and management of osteoporosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00223-019-00564-7) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6694037 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-66940372019-08-27 Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk Westbury, Leo D. Shere, Clare Edwards, Mark H. Cooper, Cyrus Dennison, Elaine M. Ward, Kate A. Calcif Tissue Int Original Research High-resolution peripheral quantitative computed tomography (HRpQCT) is increasingly used for exploring associations between bone microarchitectural and finite element analysis (FEA) parameters and fracture. We hypothesised that combining bone microarchitectural parameters, geometry, BMD and FEA estimates of bone strength from HRpQCT may improve discrimination of fragility fractures. The analysis sample comprised of 359 participants (aged 72–81 years) from the Hertfordshire Cohort Study. Fracture history was determined by self-report and vertebral fracture assessment. Participants underwent HRpQCT scans of the distal radius and DXA scans of the proximal femur and lateral spine. Poisson regression with robust variance estimation was used to derive relative risks for the relationship between individual bone microarchitectural and FEA parameters and previous fracture. Cluster analysis of these parameters was then performed to identify phenotypes associated with fracture prevalence. Receiver operating characteristic analysis suggested that bone microarchitectural parameters improved fracture discrimination compared to aBMD alone, whereas further inclusion of FEA parameters resulted in minimal improvements. Cluster analysis (k-means) identified four clusters. The first had lower Young modulus, cortical thickness, cortical volumetric density and Von Mises stresses compared to the wider sample; fracture rates were only significantly greater among women (relative risk [95%CI] compared to lowest risk cluster: 2.55 [1.28, 5.07], p = 0.008). The second cluster in women had greater trabecular separation, lower trabecular volumetric density and lower trabecular load with an increase in fracture rate compared to lowest risk cluster (1.93 [0.98, 3.78], p = 0.057). These findings may help inform intervention strategies for the prevention and management of osteoporosis. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00223-019-00564-7) contains supplementary material, which is available to authorized users. Springer US 2019-06-11 2019 /pmc/articles/PMC6694037/ /pubmed/31187198 http://dx.doi.org/10.1007/s00223-019-00564-7 Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Research Westbury, Leo D. Shere, Clare Edwards, Mark H. Cooper, Cyrus Dennison, Elaine M. Ward, Kate A. Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title | Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title_full | Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title_fullStr | Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title_full_unstemmed | Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title_short | Cluster Analysis of Finite Element Analysis and Bone Microarchitectural Parameters Identifies Phenotypes with High Fracture Risk |
title_sort | cluster analysis of finite element analysis and bone microarchitectural parameters identifies phenotypes with high fracture risk |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6694037/ https://www.ncbi.nlm.nih.gov/pubmed/31187198 http://dx.doi.org/10.1007/s00223-019-00564-7 |
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