Using large scale imaging datasets to understand and manage hypertensive disease progression after pregnancy

Our research group aims to understand unique patterns of hypertensive end organ disease progression of women and their children following a hypertensive pregnancy. This information is used to develop personalised clinical tools to identify, track, and slow end organ disease to prevent early onset cardiac, cerebral and vascular disease in these families.

This project will make use of information from computational modelling to study disease progression related to a hypertensive pregnancy across multiple modalities and organs. The insights into key structural and functional changes at the organ-level that describe stages of disease will be used to help identify potential targeted intervention.

The project will make use of a collection of unique imaging and clinical datasets from clinical trials and observational studies in families with a hypertensive pregnancy history. Furthermore, our clinical trials help us understand how interventions modify the underlying disease development.

Potential areas for a PhD project include: 

• Artificial intelligence - Application of artificial intelligence and machine learning to large research imaging datasets to improve the clinical tools already available to identify those at risk, and to identify next generation imaging and management approaches.
   
• Novel markers of early disease - Using imaging and laboratory studies to identify early cardiac and vascular changes in young people at risk of cardiovascular disease.
   
• Young adult cardiovascular prevention trials - Running trials to understand how novel approaches to lifestyle and clinical management may be able to modify these early risk cardiovascular phenotypes to prevent the development of later disease.