Abstract

In silico testing in healthcare is becoming increasingly cost-effective and time saving to understand the behavior of medical devices before conducting clinical trials. It also enables regulatory approval while prioritizing patient safety. Our proposal is the development of an innovative modelling framework based on the coupling of analytical material selection methodology with a simulation driven design approach, that supports material and geometry optimisation for new medical devices development [1]. One example of a medical application, where this approach might be used, is in the design of a total hip joint implant to replace a worn or damaged femur. The first part of this work is to identify the best material candidates that have met design constraints and objectives of a total hip joint replacement, using Ansys Granta software which contains databases of advanced bio-engineering materials and their properties. In the second part, a computer-aided design (CAD) model of a hip implant is imported on Ansys Discovery where it is simulated using finite-element analysis (FEA). The model is subjected to multiple structural forces that mimic a real-life scenario of a hip implant. The software facilitates meshing of the model and delivers instant multiphysics simulation. An instantaneous visualization of stress and strain fields into the hip joint led to an optimized combination of material and geometry; resulting in developing relevant new designs of a common hip joint. The effect of material choice on various components of the hip implant is also analyzed in the study. Our numerical outcomes were finally compared to reference data from literature [2]. [1] Fleischmann C. et al., A new approach to quickly edit geometries and estimate stresses and displacements of implants in real-time, Current Directions in Biomedical Engineering 5(1):553-556 (2019). https://doi.org/10.1515/cdbme-2019-0139 [2] Şensoy, A.T. et al. Optimal Material Selection for Total Hip Implant: A Finite Element Case Study. Arab J Sci Eng 44, 10293–10301 (2019). https://doi.org/10.1007/s13369-019-04088-y