Annals of biomedical engineering, 37(5):966-975, 2009
Annals of biomedical engineering
This paper presents an analysis of predicting the load-bearing capacities of human femurs using quantitative computer tomography (QCT)-based beam theory. Cross-sectional images of 12 human cadaver femurs (intact bones, age: 39-77 years; male = 8, female = 4) were scanned in conjunction with a calcium hydroxyapatite phantom which has five chambers of known densities. The apparent densities obtained from the scans were used to evaluate the Young's modulus (E) by applying the established empirical relationships. The fracture load of a configuration that simulated single-legged stance was measured experimentally and compared with the predicted failure load using a composite beam theory, plane stress model of the femur. In this model, the failure was assumed to occur at the weakest cross-section through the bone determined from QCT-based structural analysis. In contrast to the other experimental investigations, the setup used in this study considers the entire length of a human femur and also incorporates a novel mechanical jig to mimic the realistic physiological scenario. In one of our earlier studies, simulated lytic defects of varying size were created at the inter-trochanteric region of femurs and their load-bearing capacities were calculated based on their structural properties. Both the results obtained from the current study as well as the ones from our previous study were used to assess the viability of the methodology. A high degree of correlation was observed when the predicted failure loads obtained from the intact femurs and previously studied defective femurs were compared with the ex vivo fracture loads. The coefficients of determination (R(2)) of QCT-derived predicted loads with respect to the measured failure loads were 0.80 for the intact femurs and 0.87 for the defective femurs. The results suggest that the QCT-derived beam analysis provides a viable approach for the assessment of load-bearing capacity in various clinical scenarios.
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