Rapid patient-specific model development for joint replacement surgery of large acetabular defects
Associate Professor David Ackland, Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne
Professor Peter Lee, Department of Biomedical Engineering, Faculty of Engineering and Information Technology, The University of Melbourne
Daniel spent the first ten years of his professional life teaching snowboarding in New Zealand, Japan, and the USA, but his interest in science and engineering brought him back into education and he went on to complete a bachelor’s degree in Mechanical Engineering at the University of Liverpool, UK. After graduation, he worked as a research assistant at the university designing prototype pole climbing robots before deciding to further his career in research by starting a PhD in Biomedical Engineering at the University of Melbourne.
Daniel’s project aims to improve the understanding of the key parameters needed to ensure long-term stability of revision acetabular components used in revision total hip arthroplasty (rTHA). rTHA procedures have a poor success rate, particularly when involving large acetabular defects, and there is currently no consensus on the best treatment options. Current methods to simulate surgical procedures and implant performance can be time-consuming and difficult to perform, resulting in studies of insufficient size and scope to fully consider all factors. A rapid automated modelling pipeline utilising neural networks and finite element modelling could potentially perform much larger studies to help understand these factors and, therefore, start to improve the success rate of rTHA procedures.