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UBC Theses and Dissertations

Bone sawing and milling in computer-assisted total knee arthroplasty Plaskos, Christopher

Abstract

In total knee arthroplasty, poor limb alignment has been correlated to early failures requiring revision surgery. This thesis therefore addresses three questions: (1) How repeatable and accurate is the conventional sawing process? (2) Could a milling tool produce better results? (3) How can we optimize the milling process for clinical application? (1) Based on 85 resections performed by eight orthopaedic surgeons on 19 cadaveric femurs and tibias, I estimate the varus/valgus alignment variability associated with making two bone cuts to be ~0.8° SD for expert surgeons and ~1.4° SD for less experienced surgeons (taking √2 x the variability associated with a single cut at 95% confidence). In flexion/extension, alignment precision is estimated to be worse at over 2° SD for the group. A significant bias of ~1° in extension due to saw-blade defection on open guide surfaces was detected. Slotted cutting guides eliminated the bias in the sagittal plane but did not significantly improve frontal plane alignment variability. (2) A novel milling technique is designed and developed to improve cutting precision. Six operators performed a total of 62 cuts on 25 porcine femurs and tibias with the milling technique. The overall varus/valgus alignment variability is estimated to be ~0.6° SD (√2 x °SD at 95% confidence) with the milling instrumentation, regardless of the experience of the operator. Similar improvements were observed in flexion/extension, with an estimated alignment variability of ~1.2° SD (compared with >2°) and no significant bias for the milling instrumentation. (3) A bone-milling model was formulated based on the specific cutting energy of cortical bone, which I estimated from orthogonal cutting tests in the literature. A non-linear model was used to estimate resection accuracy under several different conditions, by solving for the quasi-static deflection of the tool in the direction normal to the cutting surface. Simulation results indicated that resection accuracy could potentially be improved by simply optimizing the surgical parameters of the cutting technique (for example, increasing the feed rate - depth of cut ratio). Alternatively, one could maintain accuracy while improving cutting time.

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