Enabling stratification of early stage knee interventions

Summary

PhD positions are available in Leeds to evaluate early-stage surgical interventions for knee disorders, using experimental and computational engineering methods. Areas of interest are related to how localised tissue repairs for the cartilage and/or meniscus perform biomechanically, including the interaction with the surrounding tissues. The work will involve developing and using computational and experimental laboratory methods to evaluate the effects of surgical and patient variables and how they relate to the outcomes of the treatments.

Over five million people in the UK are estimated to have knee osteoarthritis. Total knee replacement is regarded as a successful procedure in older patients, however device survivorship in younger and more active patients is lower with one in five patients reporting dissatisfaction with the outcome. There are long waiting lists for surgery, and delays have been shown to correlate with higher complication and revision rates. The relative ease of surgical access and earlier presentation of symptoms in the knee compared to other joints have led to the development of a range of earlier-stage interventions, such as Meniscus Allograft Transplantation (MAT), a surgical option for meniscus-deficient knees, or Osteochondral Grafting (OCG), an option for cartilage-deficient knees. However, the outcome of MAT and OCG interventions are dependent on how the implanted materials interact with tissues that are preserved during surgery, and those tissues can also be degenerated. There is little known about the interaction between the repairs and surrounding tissues and this interaction is often not taken into consideration when developing new interventions.

In this PhD project, you will be able to access unique computational and experimental facilities developed through a large programme of research. You will aim to develop an experimental or computational testing process for the biomechanical assessment of interventions and how they interact with surrounding tissues. This will be used to optimise surgical variables or identify patients who would benefit the most from the interventions. The studies will include the use of Finite Element Analysis and 3D image analysis alongside in vitro testing methodologies and equipment to examine the mechanical performance of the knee after interventions.

You will have a background in finite element analysis, in 3D image analysis, or in experimental testing of materials. You will gain technical skills in computational modelling including verification and validation aspects, 3D image analysis, experimental testing of tissues, and testing of interventions in the knee.

Background

The project is part of a large multidisciplinary research area on the evaluation of medical devices for the knee. We have developed a preclinical testing protocol for the assessment of early-stage interventions in the knee, which combines experimental and computational evaluations. The computational approach provides capacity to test a larger range of variables than is possible experimentally, scoping which factors may be critical to the outcome of treatments. These variables can be either surgical variables or patient variables, such as variation in the anatomy of surrounding structures.

The research in this PhD will aim to answer surgical questions which depend on these variations.

Research objectives

In this PhD project, you will aim to develop a testing process for the biomechanical assessment of early-stage interventions which includes their interaction with surrounding tissues and how these vary with surgical techniques or patient variables.

Specific objectives will depend on your skills and preferences and will be developed with the supervision team. Examples could include

• Development of robust computational methodologies to evaluate mechanical performance of knee therapies,
• Acquisition of robust experimental data regarding the mechanical performance of treatment using cadaveric tissue,
• Validation of computational methods based on 3D specimen-specific imaging and modelling,
• Development of population models based on machine learning methods including statistical models and on 3D image analysis,
• Identification of key patient-specific characteristics that can be used to answer clinical questions.

Skills required and development

You will have a background in finite element analysis (if possible, with knowledge of non-linear modelling), in 3D image analysis (if possible, with experience of clinically relevant imaging modalities), or in experimental testing of materials (if possible, with experience working with anatomical tissues). During the project, you may be expected to prepare and test human cadaveric or animal tissue specimens; previous experience in handling human or animal tissue would be beneficial, but not essential.

Full training will be provided on all laboratory methods and the associated health and safety requirements. You will learn practical aspects of project management, scientific writing for technical or non-technical dissemination, and gain presentation skills through international conferences and group meetings. You will gain specific technical skills and training in computational modelling including verification and validation aspects, 3D image analysis, experimental testing of tissues, and testing of interventions in the knee as well as gaining broader experience in preclinical testing of medical devices.

Environment

In these projects, you will be able to access unique experimental and computational facilities developed through a large programme of research.

You will join the multi-disciplinary, dynamic Institute of Medical and Biological Engineering (IMBE) embedded within the School of Mechanical Engineering and the Faculty of Biological Sciences at the University of Leeds. The IMBE is a world-renowned medical engineering research centre which specialises in research and translation of medical technologies that promote ’50 active years after 50’.

As a PhD student within IMBE, there will be opportunities to contribute to wider activities related to medical technologies including public and patient engagement, group training and social events. Groups of researchers working on aligned projects or using similar methods meet regularly to share ideas and best practice, and we encourage collegiate working. We will support your long-term career ambitions through bespoke training and encourage external secondments, laboratory visits or participation at international conferences.

Applicants to research degree programmes should normally have at least a first class or an upper second class British Bachelors Honours degree (or equivalent) in an appropriate discipline. The criteria for entry for some research degrees may be higher, for example, several faculties, also require a Masters degree. Applicants are advised to check with the relevant School prior to making an application. Applicants who are uncertain about the requirements for a particular research degree are advised to contact the School or Graduate School prior to making an application.

The minimum English language entry requirement for research postgraduate research study is an IELTS of 6.0 overall with at least 5.5 in each component (reading, writing, listening and speaking) or equivalent. The test must be dated within two years of the start date of the course in order to be valid. Some schools and faculties have a higher requirement.