Viceconti, M. orcid.org/0000-0002-2293-1530, Qasim, M., Bhattacharya, P. et al. (1 more author) (2018) Are CT-Based Finite Element Model Predictions of Femoral Bone Strengthening Clinically Useful? Current Osteoporosis Reports, 16 (3). pp. 216-223. ISSN 1544-1873
Abstract
PURPOSE OF REVIEW: This study reviews the available literature to compare the accuracy of areal bone mineral density derived from dual X-ray absorptiometry (DXA-aBMD) and of subject-specific finite element models derived from quantitative computed tomography (QCT-SSFE) in predicting bone strength measured experimentally on cadaver bones, as well as their clinical accuracy both in terms of discrimination and prediction. Based on this information, some basic cost-effectiveness calculations are performed to explore the use of QCT-SSFE instead of DXA-aBMD in (a) clinical studies with femoral strength as endpoint, (b) predictor of the risk of hip fracture in low bone mass patients. RECENT FINDINGS: Recent improvements involving the use of smooth-boundary meshes, better anatomical referencing for proximal-only scans, multiple side-fall directions, and refined boundary conditions increase the predictive accuracy of QCT-SSFE. If these improvements are adopted, QCT-SSFE is always preferable over DXA-aBMD in clinical studies with femoral strength as the endpoint, while it is not yet cost-effective as a hip fracture risk predictor, although pathways that combine both QCT-SSFE and DXA-aBMD are promising.
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Copyright, Publisher and Additional Information: | © 2018 The Authors. This 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. | ||||||||
Keywords: | Computed tomography; Cost-benefit; Hip fracture; Subject-specific finite element models | ||||||||
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Institution: | The University of Sheffield | ||||||||
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Mechanical Engineering (Sheffield) | ||||||||
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Depositing User: | Symplectic Sheffield | ||||||||
Date Deposited: | 24 Apr 2018 11:03 | ||||||||
Last Modified: | 03 Aug 2020 09:56 | ||||||||
Status: | Published | ||||||||
Publisher: | Springer Nature | ||||||||
Refereed: | Yes | ||||||||
Identification Number: | https://doi.org/10.1007/s11914-018-0438-8 | ||||||||
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