Precision Medicine Doctoral Training Programme

Novel computational modelling for personalised treatment of osteoarthritis

Precision Medicine Project - Novel computational modelling for personalised treatment of osteoarthritis

Supervisor(s): Prof Pankaj Pankaj & Prof Hamish Simpson
Centre/Institute: Institute for Bioengineering, School of Engineering
Industrial Partner: 3D Metal Printing Ltd

Background

Osteoarthritis (OA) is a condition that causes joints to become painful and stiff. Nearly one third of population aged above 45 are affected by OA in the UK. In spite of considerable ongoing research, pathways to OA are not well understood. OA has been generally seen to be caused by the wearing down of protective cartilage. However, there continues to be a debate about whether OA starts in the bone, with increased sclerosis and stiffness and that this results in cartilage deterioration or whether OA starts in the articular cartilage. The current proposal is that OA needs to be viewed as end stage joint failure, with different components of the joint all contributing to the failure.

Both bone and the cartilage are inhomogeneos, anisotropic and time-dependent materials (Xie et al., 2017; Klika et al., 2016). Consequently their response is strongly dependent on the type, rate, magnitude and frequency of loading. In the computational analysis of bone- cartilage systems the time-dependent behavior of bone has not been previously taken into account. The cartilage is highly complex inhomogeneous material with a distinct location dependent biochemical and morphological variations (Mow et al., 2004). The mechanical properties of cartilage vary along the depth (Dabiri and Li, 2013) as well as along the articular surface (Mow et al., 2004). The depth dependent material behaviour has been investigated previously (Dabiri and Li, 2013), but the site-dependency along the articulating surface has not been well established. We hypothesise that the biomechanical physiological loading patterns affect the material response along articular surface as well as along the depth, in both bone and the cartilage.

Aims

The primary aim of the study is to establish the inter-relationship of initial cartilage quality, subchondral bone stiffness and loading scenarios (due to different physiological activies which result in loads with varying magnitudes, frequencies and strain rates) by using computational models to optimise osteoarthritis treatment.

Outline: The research will be conducted by using data from mechanical testing and imaging of testing clinical samples in conjunction with available physiological loading data. Novel computational simulations using the finite element method will be employed. A range of cartilage properties will be considered; variation of properties from normal to cartilage weakened by infection or inflammation will be considered. Similarly the material properties of the subchondral bone will be varied to represent subchondral sclerosis. The findings of this project will enable the interplay of bone and cartilage properties and loading to be considered in different patients. This will indicate the leading mechanism of joint failure in different patients, which will allow us to personalize the treatment inline with the principles of precision medicine.

Training outcomes

By the end of the training the trainee should be able to:

  1. Present and critique the state-of-art with respect to the initiation and development OA.

  2. Develop complex geometry of joints for finite element analysis from 3D scan data.

  3. Conduct micro-CT scans of explants.

  4. Describethemathematicalconstitutivemodelsofcomponentsinvolvedinmodelling.

  5. Develop algorithms and code constitutive models for implementation in finite element packages.

  6. Develop algorithms that incorporate change in macroscale properties of cartilage due to variation in micro-environment of cells.

  7. Describe loadings experienced by the knee due to different physiological activities.

  8. Develop protocols and undertake mechanical tests on explants and simulate the results using cutting edge computational approaches.

  9. Learn to generate, curate and analyse large datasets.

  10. Master techniques for data analysis obtained from computational modelling.

  11. Work in a team and be become self reliant for acquiring resources required for research.

  12. Present research in international conferences and write journal papers.

References

Dabiri, Y., Li, L.P., 2013. Influences of the depth-dependent material inhomogeneity of articular cartilage on the fluid pressurization in the human knee. Medical Engineering and Physics 35:1591-1598.

Mow, V.C., Gu, W.Y., Chen, F.H., 2004. Structure and function of articular cartilage and meniscus. Basic Orthopaedic Biomechanics and Mechano-Biology, Lippincott Williams and Wilkins, 3rd edition, 181-258.

Klika, V., Gaffney, E.A., Chen, Y-C, Brown, P., 2016. An overview of multiphase cartilage mechanical modelling and its role in understanding function and pathology. Journal of the Mechanical Behavior of Biomedical Materials, 62:139-157.

Manda, K., Wallace, R.J., Xie, S., Levrero-Florencio, F., Pankaj, P., 2017. Nonlinear viscoelastic characterization of bovine trabecular bone. Biomechanics and Modeling in Mechanobiology, 16: 173-189

Apply Now

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  • The deadline for 21/22 applications is Thursday 7th January 2021.
  • Applicants must apply to a specific project, ensure you include details of the project you are applying to in Section 4 of your application. You should contact the primary supervisor prior to making your application.  
  • As you are applying to a specific project, you are not required to submit a Research Proposal as part of your application. 
  • Please ensure you upload as many of the requested documents as possible, including a CV, at the time of submitting your application.