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Posted on 28 March 2024 by Jessica James

²ÝÁñÉçÇø Simpleware software is being used for exciting applications in orthopaedics, where patient-specific data is improving design and treatment options. A collaborative team from the University of Adelaide, Royal Adelaide Hospital, Flinders University, and Queensland University of Technology was recently recognized at the Orthopaedic Research Society (ORS) conference for outstanding published research related to the hip. Joint first authors Stuart Callary and Khoso Fallahnezhad received the 2024 William Harris Award for the best paper published in the Journal of Orthopaedic Research over the past year, which was also part of a larger multidisciplinary project with ANZORS (Australian & New Zealand Orthopaedic Research Society). This research will lead to a clinical trial.

The study validates Finite Element (FE) model simulations for initial acetabular cup migration in hip replacements using pre-operative, post-operative, and follow-up scans with radiolucent markers (RSA) embedded in patients at surgery to quantitatively compare implant position between scans. When combined with functional data from gait analysis, the method allows patient models to be created from pre-operative scans, position implants based on the post-operative scan, apply patient-specific loads and predict implant migration using computational simulation. The results were then compared to the actual patient outcomes to validate the FE prediction accuracy.

Simpleware software played an essential role in segmenting and aligning pre-and post-operative CT data when building the patient-specific hemi-pelvis FE models for eight subjects. After segmenting the pelvis from the pre-operative CT scan, the pre- and post-operative CT scans were registered using landmark pairs. CAD models of the three-holed acetabular shell, polyethylene liner, and femoral head were then added to the segmented pre-operative pelvis using implant position from post-operative scans. Further operations and meshing were then carried out in HyperMesh? (Altair?), and FE analysis was completed using Abaqus? (Dassault Syst¨¨mes?).

This project is the first to corroborate tailored musculoskeletal and FE model predictions with in vivo RSA cup migration, and can help reduce the risk of patients receiving poor-performing implants. To further validate the predictive ability of the models, additional work is need with a larger sample size to cover a broader range of variability. However, this research demonstrates the benefits of using prospectively matched CT, gait, and RSA examinations to improve and validate FE models, enhancing their value when virtually assessing and improving options for total hip replacement patients.