Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry
Background and Purpose. To evaluate the added value of MRI with respect to peripheral quantitative computed tomography (pQCT) and dual energy X-ray absorptiometry (DXA) for predicting femoral strength. Material and Methods. Bone mineral density (BMD) of eighteen femur specimens was assessed with pQC...
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Online Access: | http://dx.doi.org/10.1155/2015/801518 |
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doaj-efe308fa11fb423b8cba7734c4a252782020-11-24T22:14:39ZengHindawi LimitedBioMed Research International2314-61332314-61412015-01-01201510.1155/2015/801518801518Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone DensitometryOlivia Louis0Yves Fierens1Maria Strantza2Robert Luypaert3Johan de Mey4Erik Cattrysse5Department of Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussels, BelgiumDepartment of Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussels, BelgiumDepartment of Mechanics of Materials and Constructions, Vrije Universiteit Brussel, Pleinlaan 2, 1040 Brussels, BelgiumDepartment of Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussels, BelgiumDepartment of Radiology, UZ Brussel, Vrije Universiteit Brussel, Laarbeeklaan 101, 1090 Brussels, BelgiumDepartment of Experimental Anatomy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels, BelgiumBackground and Purpose. To evaluate the added value of MRI with respect to peripheral quantitative computed tomography (pQCT) and dual energy X-ray absorptiometry (DXA) for predicting femoral strength. Material and Methods. Bone mineral density (BMD) of eighteen femur specimens was assessed with pQCT, DXA, and MRI (using ultrashort echo times (UTE) and the MicroView software). Subsequently biomechanical testing was performed to assess failure load. Simple and multiple linear regression were used with failure load as the dependent variable. Results. Simple linear regression allowed a prediction of failure load with either pQCT, DXA, or MRI in an r2 range of 0.41–0.48. Multiple linear regression with pQCT, DXA, and MRI yielded the best prediction (r2=0.68). Conclusions. The accuracy of MRI, using UTE and MicroView software, to predict femoral strength compares well with that of pQCT or DXA. Furthermore, the inclusion of MRI in a multiple-regression model yields the best prediction.http://dx.doi.org/10.1155/2015/801518 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Olivia Louis Yves Fierens Maria Strantza Robert Luypaert Johan de Mey Erik Cattrysse |
spellingShingle |
Olivia Louis Yves Fierens Maria Strantza Robert Luypaert Johan de Mey Erik Cattrysse Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry BioMed Research International |
author_facet |
Olivia Louis Yves Fierens Maria Strantza Robert Luypaert Johan de Mey Erik Cattrysse |
author_sort |
Olivia Louis |
title |
Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry |
title_short |
Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry |
title_full |
Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry |
title_fullStr |
Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry |
title_full_unstemmed |
Using Magnetic Resonance for Predicting Femoral Strength: Added Value with respect to Bone Densitometry |
title_sort |
using magnetic resonance for predicting femoral strength: added value with respect to bone densitometry |
publisher |
Hindawi Limited |
series |
BioMed Research International |
issn |
2314-6133 2314-6141 |
publishDate |
2015-01-01 |
description |
Background and Purpose. To evaluate the added value of MRI with respect to peripheral quantitative computed tomography (pQCT) and dual energy X-ray absorptiometry (DXA) for predicting femoral strength. Material and Methods. Bone mineral density (BMD) of eighteen femur specimens was assessed with pQCT, DXA, and MRI (using ultrashort echo times (UTE) and the MicroView software). Subsequently biomechanical testing was performed to assess failure load. Simple and multiple linear regression were used with failure load as the dependent variable. Results. Simple linear regression allowed a prediction of failure load with either pQCT, DXA, or MRI in an r2 range of 0.41–0.48. Multiple linear regression with pQCT, DXA, and MRI yielded the best prediction (r2=0.68). Conclusions. The accuracy of MRI, using UTE and MicroView software, to predict femoral strength compares well with that of pQCT or DXA. Furthermore, the inclusion of MRI in a multiple-regression model yields the best prediction. |
url |
http://dx.doi.org/10.1155/2015/801518 |
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