Replicate bones are widely used as an alternative for cadaveric bones for in vitro testing. These composite bone models are more easily available and show low inter-specimen variability compared to cadaveric bone models. The combination of in vitro testing with in silico models can provide further insights in the evaluation of the mechanical behavior of orthopedic implants. An accurate numerical representation of the experimental model is important to draw meaningful conclusions from the numerical predictions. This study aims to determine the elastic material constants of a commonly used composite clavicle model by combining acoustic experimental and numerical modal analysis. The difference between the experimental and finite element (FE) predicted natural frequencies was minimized by updating the elastic material constants of the transversely isotropic cortical bone analogue that are provided by the manufacturer. The longitudinal Young’s modulus was reduced from 16.00 GPa to 12.88 GPa and the shear modulus was increased from 3.30 GPa to 4.53 GPa. These updated material properties resulted in an average natural frequency difference of 0.49% and a maximum difference of 1.73% between the FE predictions and the experimental results. The presented updated model aims to improve future research that focuses on mechanical simulations with clavicle composite bone models.

Surface registration, in which a mapping between surfaces is calculated, is a powerful tool to create patient-specific musculoskeletal and statistical shape models. However, to create these models, surface registration must assure a one-to-one correspondence between both surfaces. To enhance this process, a surface registration framework that uses a combination of manual and automatic landmark detection is presented in this study. In addition, an extensive parameter study of the framework for a femur and a clavicle is conducted. The average correspondence quality of nine femur landmarks decreased from 15.6 mm using automatic point detection to 6.1 mm by combining manually and automatically indicated landmarks. For the clavicle, the average distance of five landmarks decreased from 2.8 to 0.9 mm. Combining manual and automatic landmark detection clearly improved correspondence quality. Results confirmed the applicability of the proposed registration framework for femur and clavicle, although with different parameter settings.