Artificial Intelligence (AI) is commonplace in just about every industry you can imagine these days. It’s a part of our daily lives without us even noticing or thinking about it. AI is an incredibly helpful and important tool in the technology space, and its evolution, while having grown exponentially over the decades, still has room to go much further. AI as it pertains to orthopedic medicine aims to help doctors better plan their procedures as well as perform more accurate procedures. This post will focus specifically on total knee arthroplasty (TKA) and the role that AI plays during preoperative, intraoperative, and postoperative care. A group of researchers have reviewed hundreds of articles between 2000 and 2021 to evaluate the effect that AI technology has had during the various phases of a total knee arthroplasty.
Before a knee arthroplasty procedure, AI is being used in a handful of ways in order to improve patient outcomes. The first one that the researchers point out is one that isn’t immediately obvious; and that is patient selection. Improperly selected patients have a much higher risk for an unsatisfactory outcome. The American Academy of Orthopedic Surgeons has developed an AI algorithm in order to standardize the patient selection process. This is done through several factors such as medical history, symptom severity, previous treatments, etc. to help ensure that doctors are at least more aware of these higher risk patients before considering a TKA.
AI is also a critical part of surgical training. One of the newest ways this is being done, and we’ve talked about this in prior posts, is through virtual reality (VR). A VR environment uses computer software to simulate the procedure in a cost-effective and fully immersive way. Here, the actions that the surgeon takes during the VR simulation can be recorded, analyzed, and improved upon. With VR there is no limit to how many training simulations can be performed and there is little to no risk of injury or need for real cadavers. There are, however, some drawbacks with VR training such as image fidelity, haptic response, and potential device related issues.
Once a patient has been scheduled for surgery, AI technology can be greatly leveraged for preoperative planning. Demographic data of the patient can help surgeons narrow down the wide array of implant sizes and options. Perhaps more useful is the way AI can be used to segment the patient’s anatomy for 3D applications. This is done through CT or MRI scans which can then be uploaded to computer software and segmented into individual bones, presenting a much faster way to convert patient imaging into 3D than manually.
During surgery, AI is used primarily in the form of robot-assisted procedures. Again, these use computer software to integrate preoperative imaging in order to map out the bony surfaces and landmarks. Robotic systems generally require input data from the surgeon before they begin the procedure. This data gives the robotic system specific parameters in which to operate, reducing the potential for error during the procedure. Additionally, previous surgeries done through a robotic system can create machine learning models improving accuracy based on the data of previous surgeries. While there have been positive short-term functional outcomes compared to conventional TKA, there are significant drawbacks to robotic systems. The physical size, investment, and required training all result in what could be seen as an overly expensive and impractical solution.
Augmented reality uses AI during a total knee arthroplasty in similar ways to robotic systems without any of the physical footprint. Augmented reality uses visual overlays displayed via specialized glasses to superimpose surgical data on top of what the surgeon is actually seeing. By using sensors or visual markers placed on specific areas of the patient, the glasses are able to track and update the visual feedback for the surgeon during the procedure. While this has been used in a small number of TKAs, there are no clinical studies available to support the clinical accuracy and efficiency of augmented reality devices.
After surgery, AI can be used for remote patient monitoring. Using devices that most people already have, smartphones have given doctors a convenient new method for tracking patient activity and engagement throughout their recovery process. Kinomatic is leveraging our partnership with OneStep to gather postoperative measurements and track patient progress. Providers can see the activity through a dashboard and get real time data on how their patients are improving or perhaps needing more assistance. Studies have shown a statistically significant reduction in rehospitalization for patients undergoing remote rehab compared to conventional postoperative rehab.
AI offers an intuitive and promising way for orthopedic surgeons to explore more advanced patient offerings. Total knee arthroplasty still has a range of outcomes and AI systems are a positive step toward reducing the percentage of unsatisfactory patient outcomes. AI technology has come a long way and the benefits are certainly showing through, but the real exciting bit comes in imagining the future potential AI still has left.
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Reference:
Batailler, C., Shatrov, J., Sappey-Marinier, E. et al. Artificial intelligence in knee arthroplasty: current concept of the available clinical applications. Arthroplasty 4, 17 (2022). https://doi.org/10.1186/s42836-022-00119-6
