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Although TKA is a generally successful procedure, some patients experience post-operative problems, with poorly positioned implants being one of the main causes. Improving our understanding of knee dynamics for specific patients helps, and how they interact with implants is important for creating data to improve pre-surgical planning. Virtual preoperative trials of the resulting kinematics of a given implant selection and component alignment can look at simulation and comparison of different alignment plans, which when linked to patient-reported outcomes (PROs), might allow a predictive algorithm to select plans for future patients.
The full workflow is briefly summarized below:
The study found that the method has potential as a powerful additional tool to TKA surgical decision-making processes, but needs to be used in addition to existing techniques and within the context of non-surgical factors not covered by the project. From this approach, applications might include helping to select between otherwise reasonable surgical alignment plans to identify optimized outcomes. Considered alongside the growing use of image-based surgical planning workflows for the hip and other anatomies, as well as the development of Machine Learning-based approaches to speeding up common tasks, 360MedCare's work shows strong promise for future applications and we look forward to seeing their progress as they continue to grow.
Read the full article Can TKA outcomes be predicted with computational simulation? Generation of a patient specific planning tool published in the journal The Knee.