Current methodologies for assessing wear on acetabular cups have focused on quantifying the amount of material loss on the bearing surface. The bearing surface is constituted by well-defined geometry and surface characteristics. As such, methods are able to estimate the unworn surface and determine the amount of material loss. When edge wear is present at the boundary between the bearing surface and outer cup geometry, it is normally thresholded during the analysis process. This can potentially underestimate the amount of wear present on acetabular cups. This paper details the requirements and methodologies for measurement and analysis of edge wear and focuses on ceramic liners. Two methodologies have been developed based on measurements using a coordinate measuring machine and a roundness measuring machine. The entire bearing surface as well as the edge geometry can be scanned using a coordinate measuring machine. A new analysis methodology has been developed to recreate the edge geometry using segmentation and identification of unworn areas. Based on the reconstructed surface, a wear map is produced and the volume of wear is quantified. The second method, based on the roundness measuring machine, is capable of nanometer-scale resolution point measurement for a defined measurement range. Because of the 2-mm limitation in the gauge measurement range, only a well-defined area located on both the bearing surface and the edge surface can be measured. The roundness traces are used to reconstruct a surface map that is analyzed based on a newly developed methodology. Both methods have been evaluated using ceramic liners tested in vitro under edge loading conditions, and the volume loss is compared to gravimetric measurements. The results show that both methods have the required resolution to measure volume loss of less than 1 mm3 and are thus capable of providing a volume loss estimation for ceramic acetabular cups.
|Title of host publication
|Beyond the Implant
|Subtitle of host publication
|Retrieval Analysis Methods for Implant Surveillance
|William M. Mihalko, Jack E. Lemons, A. Seth Greenwald, Steven M. Kurtz
|Number of pages
|Published - 30 Jun 2018