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Improving cardiometabolic risk evaluation using CT

Fat (adipose) tissue can become inflamed and can be a critical factor in the major complications of diabetes. But not all fat tissue is considered ‘harmful’. Even in people who are not obese, inflamed fat ‘hidden’ in certain locations can still be a risk factor. None of the routine scans or tests can identify inflammation in fat tissue.

FatHealth detects fat tissue inflammation using new artificial intelligence (AI) techniques applied to routine computed tomography (‘CT’) scans. FatHealth can identify people who may be at risk of developing diabetes, and people with diabetes who are at high risk of death from cardiovascular disease. This new method is better than other diagnostic tests for this purpose.

Caristo Diagnostics is a new technology company associated with the University of Oxford. The intention is to analyse 20,000 CT scans to train its AI algorithm and develop rapid and reliable AI analysis of CT scans to deliver accurate risk predictions.

Caristo, along with NHS trusts in Leeds and Milton Keynes and the Oxford AHSN, will evaluate the effectiveness of the FatHealth test in patients at risk of diabetes. By the end of the project, our intention is to have FatHealth adopted into routine use, thereby saving the NHS considerable costs and improving the lives of many at-risk patients.

This independent research is funded by the National Institute for Health Research (Artificial Intelligence to improve Cardiometabolic Risk Evaluation using CT (ACRE-CT), AI_AWARD 02013) and NHSX.


Case study

Evaluating AI-enhanced technology to identify patients at risk of developing diabetes