Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 25: 779–788, 2007

Predicting revision risk for aseptic loosening of femoral components in total hip arthroplasty in individual patients—A finite element study

Alexander B. Lennon John R. Britton Ruairi F. MacNiocaill Damien P. Byrne Patrick J. Kenny Patrick J. Prendergast
Hip

Advances in surgical procedure, prosthesis design, and biomaterials performance have considerably increased the longevity of total joint replacements. Preoperative planning is another step in joint replacement that may have the potential to improve clinical outcome for the individual patient, but has remained relatively consistent for a long time. One means of advancing this aspect of joint replacement surgery may be to include predictive computer simulation into the planning process. In this article, the potential of patient‐specific finite element analysis in preoperative assessment is investigated. Seventeen patient‐specific finite element models of cemented Charnley reconstructions were created, of which six were early (<10 years) revisions. Creep was simulated using a Maxwell model, and fatigue damage was simulated using an anisotropic continuum damage formulation. Account was taken of the relationship between annual loading cycles and age, and stair‐climbing loads were included using a walking to stair‐climbing cycle ratio of 9:1. Simulations for the equivalent of 10 years of loading were performed. Accumulated damage, inducible displacement, and migration were computed. Five of the six early revisions had the highest migration indicating that migration could have been used to identify early failures of these prostheses. Resultant migration showed the most significant difference between the early revised and unrevised groups (p = 0.0024). Furthermore, this trend was apparent from 1 year postimplantation (p = 0.0052). This ability to differentiate early revisions shows that computational simulation of aseptic loosening in cemented prostheses could prove clinically useful in helping surgeons optimize the preoperative plan for individual patients.


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