Artificial Intelligence to improve Cardiometabolic Risk Evaluation using CT (ACRE-CT)

Caristo Diagnostics Ltd
University of Oxford

Parijat is investigating how recent developments in AI, radiomics and deep learning can be used in the detection of individuals at risk from diabetes, pre-diabetes, and related cardiovascular conditions. Parijat will use existing Computerised Tomography (CT) scan technology to detect unhealthy fat tissue and identify patient specific risk of developing cardiometabolic disease. A CT scan is a non-invasive procedure which carries very low risk, and Parijat’s project hopes to use data from such scans to detect unhealthy tissue with similar accuracy to an invasive biopsy. The project will take place at the Division of Cardiovascular Medicine, using infrastructure from the Acute Vascular Imaging Centre, at the University of Oxford, in collaboration with Caristo Diagnostics.

Currently, methods used for imaging of adipose (fat) tissue lack sophistication and often add little more information to existing measures such as BMI or waist-to-hip ratio. Parijat’s work hopes to provide a greater understanding of individual risk through these novel AI models and drive worldwide clinical adoption of personalised preventative healthcare. The impact of such developments cannot be understated. At a conservative estimate, prevention of 10% of diabetes and related cardiovascular complications would translate to £1.4 billion in annual savings for the NHS.

Parijat holds a Master’s degree in software engineering from Oxford Brookes University and has worked with Caristo since 2019 as a software engineer. Her expertise in computing and software development combines with Caristo’s mission for better cardiovascular diagnostic capabilities to create the future of AI driven medical prognostics.

“I have a personal interest in the field of AI, deep learning techniques and their potential to transform healthcare outcomes in the medical field. This project is an opportunity for me to explore the field of AI in the clinical care sector, and hopefully aid in early detection of people at risk of developing diabetes.”