2020 NIHR ACF PES Imperial Platform Science and Bioinformatics 4
2020 NIHR Academic Clinical Fellowship in Priority Research Themes
HEE Local Office: North West London
Medical School: Imperial College London
Research Theme: Platform Science and Bioinformatics
Specialty Options: Clinical Radiology
Plain English Summary
Academic Imaging at Imperial is a cross-cutting discipline that undertakes an extensive programme of basic science, translational research and interventional studies. The NHS department works closely with partners at the Comprehensive Cancer Imaging Centre, MRC London Institute for Medical Science, Imperial’s Biomedical Image Analysis Group. We have a strong track record of collaboration with basic sciences including mathematicians and engineers for developing computer vision and machine learning technology, and geneticists and bioinformaticians to discover imaging markers for the molecular basis of cancer and heart disease.
i) Candidates will be able to choose from a number of areas of active research:
Artificial intelligence for predicting patient outcomes using cardiac imaging (Dr O'Regan): The UK Digital Heart project at Imperial has developed a resource of >10,000 cardiac MRI datasets, all with full patient data and genetics. This research extends machine learning to three-dimensional data of the moving heart. This work has already led to the discovery of how rare genetic variants predispose to heart failure, and has developed automated machine learning analysis of cardiac imaging to predict patient survival. This program would offer ACFs the opportunity to work at the cutting edge of interdisciplinary radiological artificial intelligence.
ii) Radiomic prognostic markers in cancer: This program extends the concept of platform science to the large volume of features embedded in images that can be analysed by machine learning in parallel with genetic and molecular data. This program, led by Profs Rockall and Aboagye, works on development of new methods for experimental and clinical cancer molecular imaging, and predicting patient outcomes.
iii) Automated tools for identifying frailty in cancer patients:
Frailty is a common clinical syndrome that carries an increased risk of death. We are working on automated tools to identify signs of frailty in patients from routine imaging. This includes machine learning body composition analysis as an objective marker of frailty.
Imperial is one of the strongest Cardiology research departments in the UK, given its breadth across Imperial trust and the Royal Brompton Hospital, and has successfully supported 25 ACFs in the last 10 years, 100% into PhDs.
Research programmes could be selected from:
i) Radiomics and the UK digital heart project (see above).
ii). Big data analytics from the world’s largest collaboration between hospitals to study the acute coronary syndromes (UK NHIC).
iii) Analysis of the world’s largest digital data-capture system from the cardiac cath lab. We have developed an integrated system pulling data through over 1,000 cath labs worldwide.
iv) The Connected Care Bureau (CCB) – designed to triage and maintain patients with long-term conditions well, out in the community and away from hospital admission. An ACF would be integral to the programme and develop novel research into its clinical effectiveness. The CCB currently supports 40,000 patients in which specialist nurses, physiologists, pharmacists, etc manage patients based on data from connected technologies. This will involve close collaboration with existing services in the major co-morbid conditions and with both Engineers and Basic Scientists in testing/researching novel technologies and bioassays. The CCB generates large volumes of real time data, combined with Imperial’s world leading AI in Health, will provide an ideal training programme in platforms/bio-informatics.