Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/29989
Title: Relationships between femoral strength evaluated by nonlinear finite element analysis and BMD, material distribution and geometric morphology
Authors: Gong, H
Zhang, M 
Fan, Y
Kwok, WL
Leung, PC
Keywords: Geometric morphology
Material distribution
Nonlinear finite element analysis
Proximal femur
Strength
Issue Date: 2012
Publisher: Springer
Source: Annals of biomedical engineering, 2012, v. 40, no. 7, p. 1575-1585 How to cite?
Journal: Annals of Biomedical Engineering 
Abstract: Precise quantification of femur strength and accurate assessment of hip fracture risk would help physicians to identify individuals with high risk and encourage them to take preventive interventions. A major contributing factor of hip fracture is the reduction of hip strength, determined by the bone quality. Bone mineral density (BMD) alone cannot determine bone strength accurately. In this paper, subject-specific quantitative computer tomography (QCT) image-based finite element analyses were conducted to identify the quantitative relationships between femoral strength and BMD, material distribution and geometric morphology. Sixty-six subjects with QCT data of hip region were selected fromtheMrOS cohorts in Hong Kong. Subject-specific nonlinear finite element models were developed to predict strengths of proximal femurs. The models took non-linear elasto-plasticity and heterogeneity of bone tissues into consideration and derived bone strengths with proper bone failure criteria.Fromfinite element analysis (FEA), relationships between femoral strength and BMD, material distribution, and geometric parameters were determined. Results showed that FEA-predicted femoral strength was highly correlated with BMD, material distribution, height, weight, diameters of femoral head (HD), and femoral neck (ND), as well as the moment arm for femoral neck bending- offset (OFF). Through principal components analysis, three independent principal components (PCs) were extracted. PC1 was the component of bonematerial quality. PC2 included height, weight, HD, and ND. PC3 mainly represented OFF. Multivariate linear regression showed that the PCs were strongly predictive of the FEA-predicted strength. This study provided quantitative information regarding the contributing factors of proximal femur strength and showed that such a biomechanical approach may have clinical potential in noninvasive assessment of hip fracture risk.
URI: http://hdl.handle.net/10397/29989
DOI: 10.1007/s10439-012-0514-7
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