Abstract
Proximal humerus fractures are the third most common fragility fractures with treatment remaining challenging. Mechanical fixation failure rates of locked plating range up to 35%, with 80% of them being related to the screws perforating the glenohumeral joint. Secondary screw perforation is a complex and not yet fully understood process. Biomechanical testing and finite element (FE) analysis are expected to help understand the importance of various risk factors. Validated FE simulations could be used to predict perforation risk. This study aimed to (1) develop an experimental model for single screw perforation in the humeral head and (2) evaluate and compare the ability of bone density measures and FE simulations to predict the experimental findings.
Screw perforation was investigated experimentally via quasi-static ramped compression testing of 20 cuboidal bone specimens at 1 mm/min. They were harvested from four fresh-frozen human cadaveric proximal humeri of elderly donors (aged 85 ± 5 years, f/m: 2/2), surrounded with cylindrical embedding and implanted with a single 3.5 mm locking screw (DePuy Synthes, Switzerland) centrally. Specimen-specific linear µFE (ParOSol, ETH Zurich) and nonlinear explicit µFE (Abaqus, SIMULIA, USA) models were generated at 38 µm and 76 µm voxel sizes, respectively, from pre- and post-implantation micro-Computed Tomography (µCT) images (vivaCT40, Scanco Medical, Switzerland). Bone volume (BV) around the screw and in front of the screw tip, and tip-to-joint distance (TJD) were evaluated on the µCT images. The µFE models and BV were used to predict the experimental force at the initial screw loosening and the maximum force until perforation.
Initial screw loosening, indicated by the first peak of the load-displacement curve, occurred at a load of 64.7 ± 69.8 N (range: 10.2 – 298.8 N) and was best predicted by the linear µFE (R2 = 0.90), followed by BV around the screw (R2 = 0.87). Maximum load was 207.6 ± 107.7 N (range: 90.1 – 507.6 N) and the nonlinear µFE provided the best prediction (R2 = 0.93), followed by BV in front of the screw tip (R2 = 0.89). Further, the nonlinear µFE could better predict screw displacement at maximum force (R2 = 0.77) than TJD (R2 = 0.70). The predictions of non-linear µFE were quantitatively correct.
Our results indicate that while density-based measures strongly correlate with screw perforation force, the predictions by the nonlinear explicit µFE models were even better and, most importantly, quantitatively correct. These models have high potential to be utilized for simulation of more realistic fixations involving multiple screws under various loading cases. Towards clinical applications, future studies should investigate if explicit FE models based on clinically available CT images could provide similar prediction accuracies.
