Date of Award


Document Type


Degree Name

Master of Science (MS)


Biomedical Engineering

Research Advisor

William M. Mihalko, MD PhD


Denis D. DiAngelo, PhD John L. Williams, PhD


Arthroplasty, Laxity, Soft tissue balancing, Wear analysis


Total knee arthroplasty is a proven technique which combines specially designed components and surgical processes to treat cartilage degeneration and alleviate pain in arthritic knees. However, this technique is limited by component design and surgical precision. Due to these limitations, knee arthroplasty components will eventually wear out, causing rejection and necessitating the need for a replacement. For this reason, it would be beneficial to experts if the primary causes of this wear could be identified in order to minimize the number of replacements.

This study aims to determine if a correlation exists between instability of a knee joint and the amount of wear present in an implant, and also relate surgical alignment to this wear. To accomplish this aim, a custom laxity machine was used to assess joint stability in 20 knees of human bodies donated to science. This laxity data was compared to damage scores expressing the amount of wear on each implant specimen, and was used in conjuction with alignment data obtained from CT scans. Alignment data was expressed as the difference in component rotations, as well as a new method here named “congruency mismatch”.

A significant correlation was found between wear and anterior and posterior laxity, indicating the need for additional constraint in implant design to minimize sliding which can lead to wear. No significant relationships were observed between either alignment analysis technique and wear scores. Results do show a positive postoperative relationship between external femoral rotation and increasing varus coronal angle, which is inversely related to previous studies which were undertaken preoperatively. Implant functionality and successful outcomes are directly related to design and proper surgical technique, which can be quantified and improved using new methods such as patient-specific design and robotic surgical systems