Encoding Scratch and Scrape Features for Wear Modeling of Total Joint Replacements

Damage to hard bearing surfaces of total joint replacement components typically includes both thin discrete scratches and broader areas of more diffuse scraping. Traditional surface metrology parameters such as average roughness or peak asperity height are not well suited to quantifying those counterface damage features in a manner allowing their incorporation into models predictive of polyethylene wear. A diffused lighting technique, which had been previously developed to visualize these microscopic damage features on a global implant level, also allows damaged regions to be automatically segmented. These global-level segmentations in turn provide a basis for performing high-resolution optical profilometry (OP) areal scans, to quantify the microscopic-level damage features. Algorithms are here reported by means of which those imaged damage features can be encoded for input into finite element (FE) wear simulations. A series of retrieved clinically failed implant femoral heads analyzed in this manner exhibited a wide range of numbers and severity of damage features. Illustrative results from corresponding polyethylene wear computations are also presented