An Automated Method for Implant Retrieval Analysis


Timothy M. Wright, PhD

Project Description

Retrieval analysis is valuable in assessing in vivo surface damage on orthopaedic devices and contributes to understanding the responsible mechanisms and subsequently improving implant materials and designs. Damage assessment traditionally employs subjective techniques to grade damage on the implant’s surface. Digital microscopy has improved our ability to localize and quantify damage, although it is unable to measure volumetric removal of material as a function of this damage. Laser scanning technology fills this niche, but provides lower resolution and minimal photographic evidence. Recent advances in imaging enables laser scan data to be rendered with photographs (photorendering), thus combining the strengths of both techniques. We have recently begun using similar methods to improve our capabilities to assess damage in implants and potentially correlate volumetric changes with the damage assessment. While the methodology of combining microscopy to laser scan data works anecdotally, more work remains in testing the robustness of fit and circumventing limitations in both  the microscopy data and the software used to stitch images together. As important, the improved resolution images provided by the microscope offers an opportunity to automate damage assessment, yielding damage mapped images that can also be overlayed on the laser scan data. This may provide a means to better quantify observed damage and yield meaningful correlations with volumetric changes due to wear and deformation of the implant.

Role of the Student:

Learn the basics of the use of the digital microscope and laser scanner.  Be exposed to our retrieval lab and understand the types of damage sustained by implants that we remove from patients. Using the microscope and scanner, develop a reliable methodology for the integrated assessment of visual and deformational damage occurring in orthopaedic implants.

Thsi position has been filled.