Journal
ANNALS OF BIOMEDICAL ENGINEERING
Volume 40, Issue 7, Pages 1575-1585Publisher
SPRINGER
DOI: 10.1007/s10439-012-0514-7
Keywords
Geometric morphology; Material distribution; Nonlinear finite element analysis; Proximal femur; Strength
Categories
Funding
- NIH USA [AR049439]
- Hong Kong Polytechnic University Research Grants [G-U701]
- National Natural Science Foundation of China [10972090, 10832012, 11120101001]
- Fundamental Research Funds for the Central Universities
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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 from the MrOS 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. From finite 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 bone material 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.
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