Clinical validation of a computer model for prediction of hip joint impingement severity

Summary

This PhD, based in Leeds, will develop and clinically validate a computational hip joint impingement model, assessing the influence of joint shape and movement. This project area focuses on the computational modelling of hip joint impingement, common in young adults and athletes, and analyses the mechanism of soft tissue damage which occurs when particular joint shapes are combined with the higher forces and larger motions occurring during certain activities. The work will consist of designing and conducting a study where clinical imaging and tissue damage data is collected and compared to the predictions from subject-specific mechanical models. This technical work will involve computer programming, medical image analysis and computational model workflow optimisation.

Femoroacetabular impingement syndrome (FAIS) is a common condition of the hip joint affecting young adults which causes significant pain and damage to the joint. The condition has been shown to increase the likelihood of developing osteoarthritis of the hip later in life. The condition is increasingly recognised and there has been an increase in the number of surgeries performed to change the bone shape and repair soft tissues. However, diagnosis requires consideration of multiple factors beyond simply bone shape, as many of the characteristic shape features can be seen in the asymptomatic population. And there is no current consensus for the selection of surgery versus physiotherapy. The aim of this research work is to add critical information for decisions in the patient care pathway, e.g. timing of physiotherapy versus surgery, and for planning of bone removal in surgery. A better understanding of the drivers for the most severe kinds of tissue damage (e.g. cartilage delamination) will significantly improve treatment triage and therefore patient outcomes.

You will have a background in computer programming or computational modelling (if possible, with experience of developing algorithms and complex data structures) and in 3D image analysis (if possible, with experience of clinically relevant imaging modalities). You will be supported to develop your programming skills, knowledge of computational model verification and validation, and specialist knowledge of the clinical data. 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.

Background

This project will use, and further develop, a computational model of the femoroacetabular impingement syndrome, developed at Leeds, which has been shown to generate different patterns of impingement across a cohort of patients with specific bony shape features. The key challenges for this work are the bottlenecks in the current patient-specific model development process and the need for validation against clinically observed tissue damage. Within the host institute there is strong foundational work and expertise, specialist medical image processing software and the collaborators in place to tackle these two challenges. This is therefore an exciting opportunity to advance this work to answer clinically relevant questions.

Research objectives

The aim of this project is to identify the hip shape and alignment factors involved in cam-type femoroacetabular impingement, through validation and sensitivity testing of a patient-specific in silico model predicting the severity of damage.
Specific objectives will depend on your skills and preferences and will be developed with the supervision team. Examples include:
1: Explore machine learning, and other automation, for an existing in silico model of cam-type hip impingement, for efficient processing of patient-specific cases.
2: Conduct a retrospective patient study validating impingement severity predictions against surgically observed damage of hip tissues.
3: Establish the hip shape and alignment features which are most critical to severity of impingement, through analysis of a large patient cohort and sensitivity testing.

Environment

In this project you will be able to access unique computational facilities developed through previous research and supported through aligned 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.