Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 624267, 12 pages
Encoding Scratch and Scrape Features for Wear Modeling of Total Joint Replacements
1Orthopaedic Biomechanics Laboratory, Department of Orthopaedics and Rehabilitation, University of Iowa, 2181 Westlawn Building, Iowa City, IA 52242-1100, USA
2Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
3Department of Materials Science and Engineering, Ohio State University, Columbus, OH 43210, USA
Received 20 December 2012; Accepted 25 February 2013
Academic Editor: Kumar Durai
Copyright © 2013 Karen M. Kruger et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.