Experimental Validation Of Finite Element Model For Proximal Composite Femur Using Optical Measurements
Författare
Summary, in English
Patient-specific finite element models have been used to predict femur strength and fracture risk in individuals. Validation of the adopted finite element modelling procedure against mechanical testing data is a crucial step when aiming for clinical applications.
The majority of the works available in literature used data from strain gages to validate the model, thus having up to 15 experimental measurements. Optical techniques, such as Digital Image Correlation, can help to improve the models by providing a continuous field of deformation data over a femoral surface. The main objective of this study was to validate finite element models of six composite femora against strain data from digital image correlation, obtained during fracture tests performed in quasi-axial loading configuration. The finite element models were obtained from CT scans, by means of a semi-automatic segmentation. The principal strains both during the elastic phase and close to the fracture were compared, and showed a correlation coefficient close to 0.9. In the linear region, the slope and intercept were close to zero and unity, while for the case when fracture load was simulated, the slope decreased somewhat. The accuracy of the obtained results is comparable with the state-of-the-art literature, with the significant improvement of having around 50000 data points for each femur. This large number of measurements allows a more comprehensive validation of the predictions by the finite element models, since thousand of points are tracked along the femoral neck and trochanter region, i.e., the sites that are most critical for femur fracture. Moreover, strain measurement biases due to the strain gage reinforcement effect, were avoided. The combined experimental-numerical approach proved to be ready for application to in-vitro tests of human cadaver femurs, thus helping to develop a suitable mechanistic fracture risk criterion.
The majority of the works available in literature used data from strain gages to validate the model, thus having up to 15 experimental measurements. Optical techniques, such as Digital Image Correlation, can help to improve the models by providing a continuous field of deformation data over a femoral surface. The main objective of this study was to validate finite element models of six composite femora against strain data from digital image correlation, obtained during fracture tests performed in quasi-axial loading configuration. The finite element models were obtained from CT scans, by means of a semi-automatic segmentation. The principal strains both during the elastic phase and close to the fracture were compared, and showed a correlation coefficient close to 0.9. In the linear region, the slope and intercept were close to zero and unity, while for the case when fracture load was simulated, the slope decreased somewhat. The accuracy of the obtained results is comparable with the state-of-the-art literature, with the significant improvement of having around 50000 data points for each femur. This large number of measurements allows a more comprehensive validation of the predictions by the finite element models, since thousand of points are tracked along the femoral neck and trochanter region, i.e., the sites that are most critical for femur fracture. Moreover, strain measurement biases due to the strain gage reinforcement effect, were avoided. The combined experimental-numerical approach proved to be ready for application to in-vitro tests of human cadaver femurs, thus helping to develop a suitable mechanistic fracture risk criterion.
Avdelning/ar
Publiceringsår
2013
Språk
Engelska
Sidor
86-94
Publikation/Tidskrift/Serie
Journal of the Mechanical Behavior of Biomedical Materials
Volym
21
Dokumenttyp
Artikel i tidskrift
Förlag
Elsevier
Ämne
- Mechanical Engineering
Nyckelord
- Composite femur
- Digital image correlation
- Bone fracture
- Finite element
Status
Published
ISBN/ISSN/Övrigt
- ISSN: 1751-6161