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Limitations in Transitioning from Conventional to Modern Total Knee Arthroplasty: A Review

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Abstract

Total knee arthroplasty (TKA) has undergone significant evolution from the initial concept of ivory components to the integration of artificial intelligence. Modern technologies, such as computers and surgical robots, are now employed to precisely place implants and achieve a neutral joint configuration with minimal incisions. Despite these advancements, achieving the desired preoperative outcome remains a challenge. Accurate implant alignment continues to be a prominent limitation in the field. Malalignment results in unbalanced stresses, restricted range of motion, patient discomfort, and ultimately, TKA failure. This study reviews the limitations of commercially available TKA techniques, including navigated TKA, robotic-assisted TKA, and artificial intelligence-based approaches. Compared with the conventional TKA, navigated TKA offers the advantage of smaller incisions, but does not consistently achieve the planned implant position. Conversely, robotic-assisted surgery theoretically provides perfect neutral alignment, but its widespread use is hindered by high operational costs and associated complications. While machine learning can predict the outcomes, its current level of accuracy is not yet clinically acceptable. Although most of the calculations for Patient-specific implants are performed during preoperative session, reducing surgery duration, drawbacks include the added expense of CT scans and MRI images, while the promised results have yet to be consistently achieved.

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Acknowledgements

This work was supported by the Ministry of Trade, Industry, and Energy (MOTIE) and the Korea Institute for Advancement of Technology (KIAT), through the International Cooperative R&D program (Project No. P0016173).

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Sohail, M., Park, J., Lee, J. et al. Limitations in Transitioning from Conventional to Modern Total Knee Arthroplasty: A Review. Multiscale Sci. Eng. 5, 77–85 (2023). https://doi.org/10.1007/s42493-024-00095-w

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