Pre-Clinical Testing and Finite Element Simulations of Orthopaedic Impaction Instruments Used in Seating of Implants

Abstract

Orthopaedic impaction-instruments are used to drive implants into the bone of the patient. Pre-clinical experimental testing protocols and computer models of those are used to assess robustness and functional efficiency of such instruments. This generally involves impaction of the instrument mounted on a substrate that should represent the mechanics of the patient. In this study, the effects of the substrate on stressing of the impaction-instruments were investigated using dynamic finite element analysis. Model results were compared with experimental data from lab protocols, which have been derived to recreate the mechanics of cadaveric implantations, which represent clinical conditions.FEA models of selected experimental protocols were created in which a simplified instrument was impacted on substrates with varying material properties and boundary conditions. After impaction, the instrument settled into a modal vibration which then decayed over time. The resulting axial strain data from the computational model was compared to strain-gauge data collected from experimental measurements. Strain signal amplitude, frequency and decay were compared. The damping-ratio was derived from the decay of the strain signal.The computational model slightly over-predicted the initial experimental strain amplitudes in all cases, but the frequency of the cyclic strain signals matched. However, the model underestimated the experimentally measured rate of signal decay. Inclusion of implant seating and soft-tissue conditions had little effect on decay.Clinical failures of impaction-instruments may be related to multiple fatigue cycles for each impaction and should be modelled accurately to allow failure prediction. Any soft substrate results in an impedance mismatch at the instrument interface, which reflects the pressure wave and causes vibration with a frequency related to the speed-of-sound in the instrument, and its geometry. While this could be accurately modelled computationally, signal decay was underestimated. Further experimental quantification of energy losses will be important to understand vibration decay.