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Ligament strain sensors: improving monitoring after ligament reconstruction surgery

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  • Full or part time
    Dr Elise Pegg
  • Application Deadline
    No more applications being accepted
  • Competition Funded PhD Project (European/UK Students Only)
    Competition Funded PhD Project (European/UK Students Only)

Project Description

To really understand how a reconstructed ligament is performing after surgical treatment, you need to be able to view the ligament directly and examine its performance during real-time motion. Currently that is not possible because the ligaments have low X-ray attenuation and cannot be distinguished from the surrounding tissue. Consequently, surgeons are reliant on indirect methods, such as manual manipulation of the joint and patient reported pain, which can result in misdiagnosis and limit refinement of surgical technique. Quantitative, reliable, non-subjective outcome measures are required for informed decision making.

This project will create novel polyethylene sutures for suture augmented ligament repair, which have radiopaque (X-ray visible) marker lines along the length; these lines will enable quantification of strain and suture position during real-time fluoroscopic imaging. The method used to make polyethylene radiopaque is unique to Dr Pegg’s research group. Research to date has achieved radiopacity with bulk polyethylene components; for the first time this project will create radiopaque patterns on polyethylene.

The project will be in collaboration with orthopaedic surgeons and medical device manufacturers. By the end of the project, the potential and clinical safety of the suture strain sensors will be known. Imaging of the sutures clinically using standard radiography will have been optimised, and the accuracy to which they can measure strain determined. The final results from the project will be used to justify in vivo testing and to encourage financial industry support, with a view to gathering the case for clinical trials of the technology.

We are looking for a highly motivated candidate with a strong background in materials, engineering, chemical engineering, or related area, to research this exciting new technique. The project will involve a combination of laboratory testing and numerical simulation work. By the end of the doctorate the candidate will:

• have extensive knowledge of biomaterial safety and design
• have been trained in a wide range of materials characterisation techniques
• be able to develop numerical models to represent ligament loading and perform computational simulations to predict behaviour
• be an expert in polyethylene biomaterials
• have presented their work at, at least, one international conference and built up a network of contacts

The candidate will have the opportunity to work with researchers within the medical device industry in the later stages of the project, as well as collaborating directly with surgeons and clinical staff throughout. Furthermore, the University of Bath provides a wide range of training courses, teaching opportunities, and career support for PhD students.

Informal enquiries should be directed to Dr Elise Pegg ([Email Address Removed])

Formal applications should be made via the University of Bath’s online application form for a PhD in Mechanical Engineering. Please ensure that you state the full project title and lead supervisor name on the application form.

https://www.bath.ac.uk/samis/urd/sits.urd/run/siw_ipp_lgn.login?process=siw_ipp_app&code1=RDUME-FP01&code2=0013

A full application must be submitted by the application deadline, including all supporting documents, to enable review.

More information about applying for a PhD at Bath may be found here:

http://www.bath.ac.uk/guides/how-to-apply-for-doctoral-study/

Anticipated start date: 30 September 2019

Funding Notes

Funding will cover Home/EU tuition fees, a maintenance stipend (£14,777 pa (2018/19 rate)) and a training support fee of £1,000 per annum for 3.5 years.

How good is research at University of Bath in Aeronautical, Mechanical, Chemical and Manufacturing Engineering?

FTE Category A staff submitted: 61.00

Research output data provided by the Research Excellence Framework (REF)

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