Raman Group: Multi-Organ MRI Phenotyping for Risk Prediction in Heart Failure and Multisystem Diseases: Insights from Prospective Imaging Cohorts and UK Biobank

About the Research 

Myocardial diseases and heart failure affects over 64 million people worldwide, imposes a serious economic burden on healthcare systems, and is one of the leading causes of hospitalisation, disability, and reduced quality of life in older adults. Heart failure is increasingly recognised as a systemic disease, with multi-organ dysfunction involving the brain, liver, kidneys, lungs, skeletal muscle, and adipose tissue.

Yet, current clinical care and risk prediction remain largely cardiac-centric, overlooking early or subtle extracardiac organ impairment that may modify outcomes, treatment response, or disease progression. This translational research project will evaluate the prognostic and pathophysiological relevance of multi-organ MRI-derived biomarkers in individuals with heart failure or at high cardiometabolic risk. The study will draw upon:

a)      Prospective multicentre multiorgan imaging cohorts, including patients with heart failure, cardiomyopathy, and post-infectious or inflammatory syndromes

b)     Data from the UK Biobank multiorgan imaging study, including post-COVID follow-up datasets with linked outcomes

c)      Available clinical, biochemical, ECG, and longitudinal follow-up data

The primary objectives are – a) To define multi-organ imaging signatures associated with adverse outcomes in patient heart muscle disease, b) To explore how extracardiac organ health interacts with cardiac dysfunction and comorbidities, c) To develop integrated risk prediction models using AI/machine learning that incorporate cardiac and extracardiac imaging features, d) To identify distinct phenotypes or trajectories in multisystem disease using deep learning approaches, e) discover novel organ (heart, liver, kidney, brain skeletal muscle, fat distribution) derived specific MRI-based signatures linked to outcomes f) develop risk-scores based on multiorgan health.

This project is ideally suited to students with an exceptional track record and with a background in biomedical sciences, statistics, engineering, computer science, or data science, with an interest in translational medical research. Prior experience with Python, MATLAB, or R will be essential. Enthusiasm for working at the interface of cardiology, medical imaging, and machine learning is welcomed. Interested candidates are encouraged to reach out to PI Betty.raman@cardiov.ox.ac.uk with a copy of their CV to discuss project details.

This MSc by Research project may be suitable for part-time research.

Training Opportunities

1. Advanced multi-organ MRI acquisition and analysis using established pipelines (e.g. UK Biobank-style methods)
2. Exposure to data harmonisation across organs, scanners, and cohorts
3. Training in advanced machine learning approaches and application to imaging and imaging derived phenotype clustering, and survival modelling for risk prediction
4. Knowledge about clinical cardiac syndromes and gaps in evidence base and priorities for research
5. Machine learning applications to organ segmentation to develop image analysis pipelines
6. Hands-on experience in phenome-wide association studies (PheWAS)
7. Cross-disciplinary collaboration with neuroradiologist, radiologist AI scientists, and clinicians
8. Public health insights through integration of lifestyle, genomics (GWAS), and imaging in population studies
9. Development of clinical risk tools or decision aids that incorporate multi-organ MRI biomarkers
10. Training in presenting high-dimensional data for early disease detection and prognostic risk stratification.

Students are encouraged to attend the MRC Weatherall Institute of Molecular Medicine DPhil Course, which takes place in the autumn of their first year. Running over several days, this course helps students to develop basic research and presentation skills, as well as introducing them to a wide range of scientific techniques and principles, ensuring that students have the opportunity to build a broad-based understanding of differing research methodologies.

Generic skills training is offered through the Medical Sciences Division's Skills Training Programme. This programme offers a comprehensive range of courses covering many important areas of researcher development: knowledge and intellectual abilities, personal effectiveness, research governance and organisation, and engagement, influence, and impact. Students are actively encouraged to take advantage of the training opportunities available to them.

As well as the specific training detailed above, students will have access to a wide range of seminars and training opportunities through the many research institutes and centres based in Oxford.

The Department has a successful mentoring scheme, open to graduate students, which provides an additional possible channel for personal and professional development outside the regular supervisory framework. We hold an Athena SWAN Silver Award in recognition of our efforts to build a happy and rewarding environment where all staff and students are supported to achieve their full potential.

Additional Supervisors

1. Stefan Neubauer 

2. Abhirup Banerjee

3. Qiang Zhang

Publications