MRC DiMeN Doctoral Training Partnership: Building integrated machine learning and genomic approaches to quantitate bone quality and fracture risk

This PhD Project would suit a candidate inspired by the prospect of participating in a multidisciplinary team in a project that sits at the interface between clinical medicine, computer science, and genomic medicine and who wishes to develop core skills in mathematics, statistics and computation. The student will develop methods and tools for integrating these multiscale/multisource datasets with machine learning to extract individualised imaging phenotypes and relate them to reference control and fracture populations.

Eighty thousand people sustain a fragility femoral neck fracture every year in the UK. The 1-year mortality following this injury is 20-30%, and 30% of surviving patients fail to return to independent living. Susceptibility to osteoporotic fracture runs strongly in families, but is also lifestyle dependent. Dual energy X-ray absorptiometry (DXA) is the standard method used to estimate fracture risk but yields only modest estimates of risk and does not account for the spatial bone microarchitecture or genetic and lifestyle risk factors.

Using novel computer vision approaches we can exploit texture, shape, contour and contextual information from image sequences to provide 4D information to help us better understand health and disease. Exploiting these technologies on a dedicated in-house platform (http://www.multi-x.org) we have developed a high-throughput computational tool for DXA scan analysis that utilises advanced computer vision approaches to extract and interpret pixel-level spatial information from within conventional DXA scans (see PMID 25222069, 25640686, 28169450, and 28652104).

In this project, the student will join an inter-disciplinary and cross-institutional team using existing patient cohorts to empower better understand the structural influence that clinical, genetic, lifestyle factors and interventions have on the proximal femur (thigh bone).

Specifically, the student will apply these computational approaches to understand:
1) How variations in local bone texture in the femoral neck region with age and gender associate with subsequent fracture events
2) How established osteoporosis risk factors and genetic variation affect femoral neck bone architecture and fracture risk
3) How established treatments, dietary modification and exercise affect local bone architecture to influence fracture risk

To achieve these goals the student will make use of already established cohorts, including the UK Biobank, containing longitudinal outcomes in >20000 individuals and >500 femoral neck fracture episodes from which they will construct relationships between the variables to better understand femoral neck microarchitecture and fracture risk.

See the following links for more details of the supervisors and their work:
Mark Wilkinson https://mellanbycentre.org/mark-wilkinson/
Alex Frangi https://engineering.leeds.ac.uk/staff/1535/Prof_Alejandro_F_Frangi
Ele Zeggini https://www.helmholtz-muenchen.de/itg/index.html

Benefits of being in the DiMeN DTP:
This project is part of the Discovery Medicine North Doctoral Training Partnership (DiMeN DTP), a diverse community of PhD students across the North of England researching the major health problems facing the world today. Our partner institutions (Universities of Leeds, Liverpool, Newcastle and Sheffield) are internationally recognised as centres of research excellence and can offer you access to state-of the-art facilities to deliver high impact research.
We are very proud of our student-centred ethos and committed to supporting you throughout your PhD. As part of the DTP, we offer bespoke training in key skills sought after in early career researchers, as well as opportunities to broaden your career horizons in a range of non-academic sectors.
Being funded by the MRC means you can access additional funding for research placements, international training opportunities or internships in science policy, science communication and beyond. See how our current DiMeN students have benefited from this funding here: http://www.dimen.org.uk/overview/student-profiles/flexible-supplement-awards
Further information on the programme can be found on our website:
http://www.dimen.org.uk/