Press-fitted implants are implanted by impaction to ensure adequate seating, but without overloading the components, the surgeon, or the patient. To understand this interrelationship a uniaxial discretised model of the hammer/introducer/implant/bone/soft-tissues was developed. A parametric analysis of applied energy, component materials and geometry, and interactions between implant and bone and between bone and soft-tissues was performed, with implant seating and component stresses as outcome variables. To reduce the impaction effort (energy) required by the surgeon for implant seating and also reduce stresses in the hardware the following outcomes were observed: Reduce energy per hit with more hits / Increase hammer mass / Decrease introducer mass / Increase implant-bone resistance (eg stem roughness). Hardware stiffness and patient mechanics were found to be less important and soft tissue forces, due to inertial protection by the bone mass, were so low that their damage would be unlikely. This simple model provides a basic understanding of how stress waves travel through the impacted system, and an understanding of their relevance to implantation technique and component design.
BackgroundPress-fitted implants are implanted by impaction to ensure adequate seating, but without overloading the components, the surgeon, or the patient. To understand this interrelationship a uniaxial discretised model of the hammer/introducer/implant/bone/soft-tissues was developed. A parametric analysis of applied energy, component materials and geometry, and interaction between implant-bone and bone-soft-tissue was performed, with implant seating and component stresses as outcome variables. ResultsTo reduce stresses without compromising seating, the following outcomes were observed: Less energy per hit with more hits / Increase hammer mass / Decrease introducer mass / Increase implant-bone resistance (eg stem roughness). Material stiffness and patient mechanics were found to be less important.ConclusionsThis simple model provides a basic understanding of how stress waves travel through the impacted system, and an understanding of their relevance to component design.
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.
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