ArticleAnnals of biomedical engineering2019
Optimizing Accuracy of Proximal Femur Elastic Modulus Equations.
Article in Annals of biomedical engineering, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Computational Assessment of Fracture Risk in Vertebral Bodies With Simulated Defects: The Role of Baseline Strength and Tumor Size.International journal for numerical methods in biomedical engineering · 2025Article
- Prediction of vertebral failure under general loadings of compression, flexion, extension, and side-bending.Journal of the mechanical behavior of biomedical materials · 2025Article
- Tissue stiffness heterogeneity in the jaw and temporomandibular joint: its impact on tumor metabolism and considerations forFrontiers in physiology · 2025Review
- Risk modeling of femoral neck fracture based on geometric parameters of the proximal epiphysis.World journal of orthopedics · 2022Article
- Single-level subject-specific finite element model can predict fracture outcomes in three-level spine segments under different loading rates.Computers in biology and medicine · 2021Article
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Authors and funding
5 authors.
Funding
Abstract
Quantitative computed tomography-based finite element analysis (QCT/FEA) is a promising tool to predict femoral properties. One of the modeling parameters required as input for QCT/FEA is the elastic modulus, which varies with the location-dependent bone mineral density (ash density). The aim of this study was to develop optimized equations for the femoral elastic modulus. An inverse QCT/FEA method was employed, using an optimization process to minimize the error between the predicted femoral stiffness values and experimental values. We determined optimal coefficients of an elastic modulus equation that was a function of ash density only, and also optimal coefficients for several other equations that included along with ash density combinations of the variables sex and age. All of the optimized models were found to be more accurate than models from the literature. It was found that the addition of the variables sex and age to ash density made very minor improvements in stiffness predictions compared to the model with ash density alone. Even though the addition of age did not remarkably improve the statistical metrics, the effect of age was reflected in the elastic modulus equations as a decline of about 9% over a 60-year interval.
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Registered trials
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