| Title |
Are CT-Based Finite Element Model Predictions of Femoral Bone Strengthening Clinically Useful?
|
|---|---|
| Published in |
Current Osteoporosis Reports, April 2018
|
| DOI | 10.1007/s11914-018-0438-8 |
| Pubmed ID | |
| Authors |
Marco Viceconti, Muhammad Qasim, Pinaki Bhattacharya, Xinshan Li |
| Abstract |
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 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Netherlands | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 122 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 27 | 22% |
| Student > Ph. D. Student | 25 | 20% |
| Student > Bachelor | 12 | 10% |
| Researcher | 11 | 9% |
| Student > Doctoral Student | 7 | 6% |
| Other | 13 | 11% |
| Unknown | 27 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 57 | 47% |
| Medicine and Dentistry | 11 | 9% |
| Nursing and Health Professions | 3 | 2% |
| Computer Science | 3 | 2% |
| Biochemistry, Genetics and Molecular Biology | 2 | 2% |
| Other | 8 | 7% |
| Unknown | 38 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 April 2018.
All research outputs
#20,481,952
of 23,043,346 outputs
Outputs from Current Osteoporosis Reports
#473
of 550 outputs
Outputs of similar age
#288,941
of 327,682 outputs
Outputs of similar age from Current Osteoporosis Reports
#14
of 17 outputs
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