Development of a parametric finite element model of the proximal femur using statistical shape and density modelling

Daniel Nicolella and Todd Bredbenner

Computer Methods in Biomechanics and Biomedical Engineering, 2012, vol. 15, issue 2, 101-110

Abstract: Skeletal fractures associated with bone mass loss are a major clinical problem and economic burden, and lead to significant morbidity and mortality in the ageing population. Clinical image-based measures of bone mass show only moderate correlative strength with bone strength. However, engineering models derived from clinical image data predict bone strength with significantly greater accuracy. Currently, image-based finite element (FE) models are time consuming to construct and are non-parametric. The goal of this study was to develop a parametric proximal femur FE model based on a statistical shape and density model (SSDM) derived from clinical image data. A small number of independent SSDM parameters described the shape and bone density distribution of a set of cadaver femurs and captured the variability affecting proximal femur FE strength predictions. Finally, a three-dimensional FE model of an ‘unknown’ femur was reconstructed from the SSDM with an average spatial error of 0.016 mm and an average bone density error of 0.037 g/cm3.

Date: 2012
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DOI: 10.1080/10255842.2010.515984

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