On the importance of accurate elasto-plastic material properties in simulating plate osteosynthesis failure.

ABSTRACT

Background: Plate osteosynthesis is a widely used technique for bone fracture fixation; however, complications such as plate bending remain a significant clinical concern. A better understanding of the failure mechanisms behind plate osteosynthesis is crucial for improving treatment outcomes. This study aimed to develop finite element (FE) models to predict plate bending failure and validate these against in vitro experiments using literature-based and experimentally determined implant material properties. Methods: Plate fixations of seven cadaveric tibia shaft fractures were tested to failure in a biomechanical setup with various implant configurations. FE models of the bone-implant constructs were developed from computed tomography (CT) scans. Elasto-plastic implant material properties were assigned using either literature data or the experimentally derived data. The predictive capability of these two FE modelling approaches was assessed based on the experimental ground truth. Results: The FE simulations provided quantitatively correct prediction of the in vitro cadaveric experiments in terms of construct stiffness [concordance correlation coefficient (CCC) = 0.97, standard error of estimate (SEE) = 23.66, relative standard error (RSE) = 10.3%], yield load (CCC = 0.97, SEE = 41.21N, RSE = 7.7%), and maximum force (CCC = 0.96, SEE = 35.04, RSE = 9.3%), when including the experimentally determined material properties. Literature-based properties led to inferior accuracies for both stiffness (CCC = 0.92, SEE = 27.62, RSE = 19.6%), yield load (CCC = 0.83, SEE = 46.53N, RSE = 21.4%), and maximum force (CCC = 0.86, SEE = 57.71, RSE = 14.4%). Conclusion: The validated FE model allows for accurate prediction of plate osteosynthesis construct behaviour beyond the elastic regime but only when using experimentally determined implant material properties. Literature-based material properties led to inferior predictability. These validated models have the potential to be utilized for assessing the loads leading to plastic deformation in vivo, as well as aiding in preoperative planning and postoperative rehabilitation protocols.