Master of Engineering Science
Electrical and Computer Engineering
This thesis presents a method for evaluating and comparing assistive total knee arthroplasty (TKA) devices while controlling surgeon landmarking variability. To achieve consistent landmark selection by surgeons during TKA procedures, the method uses identical 3D-printed knees with indented landmarks. This method was used to compare a robotic and computer-assisted TKA device on three metrics: measurement accuracy, alignment accuracy, and cut-surface uniformity. Although both devices had considerable sagittal plane measurement errors, the robotic device had better measurement and alignment accuracy than the computer-assisted device. Furthermore, the robotic device's measuring error compensated for cutting errors, but the computer-assisted device's compounded them. However, both techniques were equally able to maintain small bone-implant gaps. This thesis demonstrates that this new method can be used to draw conclusions about the inherent capabilities and limitations of robotic and computer-assisted TKA devices.
Summary for Lay Audience
Total Knee Arthroplasty (TKA) is a common procedure for treating knee osteoarthritis (KOA). During the surgery, the surfaces of the knee joint are cut off and replaced with implants. TKA technologies that are robotic-assisted or computer-assisted attempt to increase surgical accuracy and reduce complications. These devices require picking landmarks on the knee with a sensor so that the devices know where the knee is in space and can inform the surgeon where the knee cut will be performed. However, there is limited information on the effectiveness of these devices, and their performance in prior research has always been influenced by the surgeon selecting different landmarks during each trial. It is also hard to tell how well the devices are working because there is no objective way to measure the cuts after they have been made.
This thesis developed an objective assessment method based on 3D-printed knees with identical landmarks to achieve consistent landmark selection by surgeons during TKA procedures that use assistive devices. The method was used to evaluate the ROSA Knee, a robotic-assisted TKA device, and the Intellijoint Knee, a computer-assisted TKA device, using three metrics: measurement accuracy, alignment accuracy, and cut surface uniformity. The measurement accuracy of a device is an indicator of how well it can perceive its location in space. The device's alignment accuracy is an indicator of how well the device can cut the bone according to the surgeon's plan. Cut-surface uniformity measures the smoothness of the cut surface after the cuts have taken place.
Even though both devices had large measurement errors in the sagittal plane, the ROSA performed better at measuring and aligning than the Intellijoint. Furthermore, the ROSA's measurement errors compensated for cutting errors, whereas the Intellijoint's measurement errors added to them. However, both approaches were found to be equally effective at preserving small bone-implant gaps. This thesis demonstrates that this new method can be used to draw conclusions about the accuracy of assistive TKA devices.
Stevens, Delaney R.G., "A Novel Method for Determining the Inherent Capabilities of Computer and Robotic-Assisted Total Knee Arthroplasty Devices" (2023). Electronic Thesis and Dissertation Repository. 9594.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Share Alike 4.0 License.