Predicting overloading plate failure using specimen-specific finite element models combined with implantable sensors.

Abstract

Mechanical failure of plate osteosyntheses, such as plate bending, still occur in patients. While finite element (FE) models can simulate the mechanical behavior of a bone-plate construct, they lack in vivo validation due to unknown loads. The advent of implantable sensors, which monitor fracture healing by measuring plate deformation, presents an opportunity to validate these FE models in vivo. However, there is currently no established link between the sensor signal and the predicted implant failure. The aim of this study was to bridge this gap by combining FE simulations with sensor data to predict experimentally obtained implant failure of bone-plate constructs. Seven cadaveric ovine tibia shaft fractures, fixed with locking plates, were tested for quasi-static failure, with implantable sensors monitoring plate bending deformation. These setups were mirrored in FE models, where virtual sensor signals, calibrated from a four-point bending test on the isolated sensor, were compared to experimental signals at the onset of plate bending. There was a high correlation between the experimental and virtual sensor signals from the four-point bending test (R² > 0.99). The construct-specific FE models, with the calibrated virtual sensor signals, demonstrated a strong correlation with experimental sensor signals at yield (concordance correlation coefficient = 0.89, standard error of estimate = 187.0, relative standard error = 11.9 %). FE models accurately predicted sensor signals at plate bending onset, enabling retrospective in vivo validation without load data and supporting tailored rehabilitation to lower patient complication rates.