Localised loss of bone at sites of structural importance can increase risk of osteoporotic fracture, whilst changes in the bone underlying articular cartilage (subchondral bone) such as bone marrow lesions precede osteoarthritic change. Previous study has shown that regular exercise may induce localized changes in bone structure which affect bone strength independently of bone mineral content (BMC) which could thus affect risk of osteoporosis or osteoarthritis. However, the scanning techniques used in previous research cannot provide adequate resolution on the microscopic changes of bone morphology caused by mechanical loading, nor it can tell the effect of localized bone adaption on further development of bone marrow lesions and osteoarthritis. This cross-school, multi-disciplinary project is to continue develop our novel experimental technique based on in-vivo High Resolution peripheral Quantitative Computed Tomography (HR-pQCT) and Magnetic Resonance Imaging (MRI) in order to evaluate and quantify micromorphological responses of subchondral bone-cartilage interface subject to brief, regular (high-impact loading) exercise. The developed technique therefore, allows a quantitative evaluation of the effects of exercise on structures that affect the risk of osteoarthritis and osteoporosis.
In addition, evaluating loading induced skeletal changes in intervention trials using MRI and high resolution CT scans is extremely time-consuming and expensive. Therefore, the proposed study also provides further aspect in computational development, such as 3D statistical shape modelling, microstructural finite element analysis, machine learning technique. The developed modelling approach will further enhance the capacity and accuracy of the current gold-standard bone quality assessment and ultimately lead to increase possibility of early prognosis of osteoporosis/osteoarthritis.
Start date: 1 April, 1 July or 1 October 2020.
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in engineering, physics, applied mathematics or a related subject. A relevant Master’s degree and/or experience in one or more of the following will be an advantage: • Mechanical engineering • Biomechanical engineering • Solid mechanics • Applied mathematics • Physics • Sport exercise and Health Sciences
How to apply:
All applications are made online, please select the school/department name under the programme name section and include the quote reference number.