The demand for total knee arthroplasty (TKA) is increasing steadily. In 2007, Kurtz et al.  predicted that TKA procedures would increase from 402,100 in 2003 to 3.48 million by 2030. Recent US national inpatient survey data have borne out these trends [2, 3]. Furthermore, demand is growing fastest in people younger than 65  — patients who will need their implants to last the longest. The major factors limiting prosthesis longevity involve wear of the polyethylene bearing surfaces. Wear continues to be a problem at the knee; for example, advances that reduce hip implant wear such as crosslinking of polyethylene are not widely used in TKA due to fears of early material breakdown under knee loading conditions . Preclinical TKA testing is performed with knee wear simulators under generic walking conditions. Efforts are ongoing by us  and others  to improve the physiological relevance of current testing standards. Nevertheless, a simulator would need to run ∼eight months continuously to simulate 20 years of walking, assuming one-million steps per year and speed of one cycle per second. As a complementary tool, computational models can test multiple conditions efficiently and ensure a faster turnaround time in the design process to eliminate inferior designs earlier. The purpose of this work is to describe a computational framework for predicting TKA loading, and ultimately implant longevity, on a patient-specific basis. The rationale is that, after developing a patient-specific computational framework, TKA designs of any material and under any patient behavior can be modulated to promote contact conditions best for implant longevity.
- Bioengineering Division
Computational Framework for Determining Patient-Specific Total Knee Arthroplasty Loading
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Lundberg, HJ, & Wimmer, MA. "Computational Framework for Determining Patient-Specific Total Knee Arthroplasty Loading." Proceedings of the ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. ASME 2013 Conference on Frontiers in Medical Devices: Applications of Computer Modeling and Simulation. Washington, DC, USA. September 11–13, 2013. V001T09A002. ASME. https://doi.org/10.1115/FMD2013-16062
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