Reduced-order spatio-temporal dynamical modelling and simulation of periprosthetic bone remodelling for joint replacements

Lead Academic – Lingzhong Guo (Sheffield)

Paul Genever (York)

Zhongmin Jin (Leeds)

Understanding periprosthetic bone remodelling is critical for improving the design of implants and aiding in clinical decisions.  Although it has been extensively used for the simulation of periprosthetic bone remodelling, the finite element (FE) method, particularly in three-dimensional simulation, can be quite expensive because of large computational costs. Furthermore simulations are time consuming and often require a computer cluster for running the calculations. To facilitate the use of periprosthetic bone remodelling simulations routinely in clinical practice and implant design, the computational costs need to be reduced.

The aim of this project is to develop a cheaper, faster, yet effective in silico model of periprosthetic bone remodelling. This will be achieved by using model reduction techniques – NARMAX methods – developed in Sheffield [1], which construct a low-dimensional model to approximate a high-dimensional system with a high degree of accuracy, thus reducing the computational cost and time involved. This research will draw upon the expertise, personnel, facilities from across three institutions and the main objectives are:

  • To form a White Rose (WR) network linking the existing expertise in engineering system modelling and bone biology among Sheffield, York and Leeds.
  • To develop a reduced-order model of periprosthetic bone remodelling.
  • To identify strategic projects to improve understanding of bone remodelling.

 

Other academics involved with this project

Yongtao Lu (Sheffield)

Amanda Barnes (York)

Marlène Mengoni (Leeds)

 

References:

[1] Guo, L. Z. and Billings, S. A., State space reconstruction and spatio-temporal prediction of lattice dynamical systems,  IEEE Trans. Automatic Control, 52(4), 622-632, 2007.