A. Synek, Y. Chevalier, S.F. Baumbach, D. H. Pahr:
"The Influence of Bone Density and Anisotropy in Finite Element Models of Distal Radius Fracture Osteosynthesis: Evaluations and Comparison to Experiments";
Journal of Biomechanics, 48 (2015), 15; S. 4116 - 4123.

Kurzfassung englisch:
Continuum-level finite element (FE) models can be used to analyze and improve osteosynthesis procedures for distal radius fractures (DRF) from a biomechanical point of view. However, previous models oversimplified the bone material and lacked thorough experimental validation. The goal of this study was to assess the influence of local bone density and anisotropy in FE models of DRF osteosynthesis for predictions of axial stiffness, implant plate stresses, and screw loads. Experiments and FE analysis were conducted in 25 fresh frozen cadaveric radii with DRFs treated by volar locking plate osteosynthesis. Specimen specific geometries were captured using clinical quantitative CT (QCT) scans of the prepared samples. Local bone material properties were computed based on high resolution CT (HR-pQCT) scans of the intact radii. The axial stiffness and individual screw loads were evaluated in FE models, with (1) orthotropic inhomogeneous (OrthoInhom), (2) isotropic inhomogeneous (IsoInhom), and (3) isotropic homogeneous (IsoHom) bone material and compared to the experimental axial stiffness and screw-plate interface failures. FE simulated and experimental axial stiffness correlated significantly (p<0.0001) for all three model types. The coefficient of determination was similar for OrthoInhom R2=0.807 and IsoInhom R2=0.816 models but considerably lower for IsoHom models R2=0.500. The peak screw loads were in qualitative agreement with experimental screw-plate interface failure. Individual loads and implant plate stresses of IsoHom models differed significantly (p<0.05) from OrthoInhom and IsoInhom models. In conclusion, including local bone density in FE models of DRF osteosynthesis is essential whereas local bone anisotropy hardly effects the models׳ predictive abilities.

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