UBC Theses and Dissertations
Development and system integration of a computer-asisted total knee replacement technique Bullock, Stacy J.
In a total knee replacement (TKR), the deformed articular surfaces of the knee joint are replaced with femoral, tibial, and patella components. Though this procedure is considered successful, component positioning errors, postoperative instability, and component loosening still exist. Computer-assisted techniques aim to remove the inadequacy of mechanical instrumentation and the visual perception necessary in conventional procedures. Though commercial systems are available, published literature do not entirely support its use. Many systems incorporate algorithms that have not been verified, or that are known to be variable. Our lab (Neuromotor Control Lab, UBC) has been investigating repeatable algorithms for steps of the total knee replacement procedure. The ultimate goal would be a complete, accurate, and cost-effective system that is an open architecture for research incorporating all the verified algorithms. The overall system must be validated and assessed, before it can be ultimately implemented clinically. My thesis focused on determining repeatable algorithms for the requirements of the total knee replacement that had not been previously addressed, and integrating the system to take steps towards providing this open architecture for research. With this, the benefits of computer-assistance over conventional surgery may eventually be shown in this area. In the first study, I investigated the use of a plane probe over a point probe to locate the transepicondylar axis for applications to proper rotational alignment and femoral knee centre. Current computer-assisted systems use a point probe to locate this axis, but this approach has been shown to result in highly variable axis locations. By conducting intraand inter-operator tests on a cadaveric knee, I found that for this specimen, a sphere-fit based method was more reliable than a convex-hull based method in determining medial and lateral epicondylar estimates, and that this method may be more repeatable than using a point probe. In the second study, I investigated a way to locate a tibial knee centre based on optimal coverage of the tibial plateau. Current computer-assisted systems digitize the tibial eminences, and while this may provide a good mediolateral centre, the resulting anteroposterior location is variable. I evaluated the use of an ellipse-fit algorithm on a Sawbones and cadaveric model, and found, upon further verification, that this method could be implemented in computer-assisted systems as it better represents a tibial knee centre than the centre of the tibial eminences currently used in other commercial systems. I then developed the kinematics for, and integrated a prototype of an adjustable cutting guide into our overall system. This cutting guide is different from those in many commercial systems as it can be roughly positioned on the bone, and then adjusted into place. This reduces error that may result from using visual feedback to manually align cutting blocks to guide lines provided on the screen. I evaluated the use of the cutting guide, and recommended changes for a more improved version. Finally, I integrated all the algorithms (includes mine and previous graduate students) developed for each stage of the procedure into a full working system complete with a graphic user interface (GUI). The integrated system was designed to be modular, allowing choices in each step of the procedure. I demonstrated the working system on a Sawbones model, and presented it to an expert orthopaedic surgeon for feedback and recommendations. By combining the contributions of this thesis with those of previous students, and the recommended hardware and software changes, our system provides an open architecture for research in this computer-assisted total knee replacement area. This system should increase the accuracy of TKR thereby increasing implant success and longevity, hence improving the patients quality of life.
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