Experimental and computational evaluation of knee implant wear and creep under in vivo and ISO boundary conditions

Abstract

Experimental knee implant wear testing according to ISO 14243 is a standard procedure, but it inherently possesses limitations for preclinical evaluations due to extended testing periods and costly infrastructure. In an effort to overcome these limitations, we hereby develop and experimentally validate a finite element (FE) based algorithm, including a novel cross-shear and contact pressure dependent wear and creep model, and apply it towards understanding the sensitivity of wear outcomes to the applied boundary conditions. Specifically, we investigated the application of in vivo data for level walking from the publicly available "Stan" dataset, which contains single representative tibiofemoral loads and kinematics derived from in vivo measurements of six subjects, and compared wear outcomes against those obtained using the ISO standard boundary conditions. To provide validation of the numerical models, this comparison was reproduced experimentally on a six-station knee wear simulator over 5 million cycles, testing the same implant Stan's data was obtained from. Experimental implementation of Stan's boundary conditions in displacement control resulted in approximately three times higher wear rates (4.4 vs. 1.6 mm3 per million cycles) and a more anterior wear pattern compared to the ISO standard in force control. While a force-controlled ISO FE model was unable to reproduce the bench test kinematics, and thus wear rate, displacement-controlled FE models accurately predicted the laboratory wear tests for both ISO and Stan boundary conditions. The credibility of the in silico wear and creep model was further established per the ASME V&V-40 standard. The model is thus suitable for supporting future patient specific models and development of novel implant designs.

The influence of implant design and limb alignment on in vivo wear rates of fixed‐bearing and rotating‐platform knee implant retrievals

“…However, laboratory tests often fail to accurately reproduce the depth 3 and broad extent of wear scars, [3][4][5][6] as well as the diversity of damage modes 4,7,8 observed in vivo. While computational models can offer predictive insights for data from large patient cohorts, provided realistic input loads and kinematics are even available, such models critically require extensive validation from experimental 9 or retrieval 10 studies to be credible. Therefore, whether the objective is to investigate in vivo wear directly or to validate experiments and models, the need for real-world data from retrievals is unavoidable.…”