King's College London

Scientist from King’s College London believe that Artificial Intelligence could hold the key to identifying the best way to treat the country’s biggest killer, coronary heart disease (CHD).

And now the team has secured close to £250,000 from by national charity Heart Research UK to pursue the test, that if successful would be less invasive, faster and more cost-effective than existing procedures.

Lead scientist Dr Jack Lee and his King’s College London team have been awarded a Novel and Emerging Technologies (NET) Grant by Heart Research UK to develop a type of advanced computing technique which will learn to identify patterns from blood flow simulations in thousands of coronary arteries.

Called ‘deep learning’, the computing algorithm will make a pressure-based assessment of coronary artery narrowings safer, quicker and easier than at present

When a patient is admitted to a catheter lab for treatment for CHD, doctors must decide whether the artery should be reopened physically with a stent or, in less severe cases, treated with medication.

There is much evidence that measuring the pressure drop across the coronary artery narrowing is a highly accurate way of deciding the best treatment. The test involves inserting a wire into the coronary artery which has a sensor to measure pressure.

However, the majority of catheter labs in the UK do not currently measure pressure routinely due to the risk to patients, and the extra time and cost of the procedure.

Coronary angiography is the conventional method for looking at the coronary arteries and involves taking x-ray images of the blood vessels. This information can be combined with a computer model of blood flow to estimate the pressure drop, without carrying out invasive measurements on patients. There are already accurate methods to simulate the blood flow through blood vessels but they are time-consuming and require special training to perform.

In an alternative approach, Dr Lee’s project will use an advanced computing algorithm known as ‘deep learning’. This is a type of artificial intelligence technique which will identify patterns from blood flow simulations in thousands of coronary arteries, so the computer ‘learns’ how the geometry of the narrowings affects the pressure pattern.

In turn, this information may allow the pressure drop across the coronary artery narrowing to be calculated directly and in real-time from the angiography images. The team will then test the new method on real patient data to demonstrate its clinical usefulness.

Dr Lee said: “The successful outcome of this research may help doctors decide on the best treatment for CHD using a test with reduced risk and less discomfort for patients. A fast and automatic method may also lead to shorter waiting times and cost savings for the NHS.”

Barbara Harpham, Chief Executive at Heart Research UK, said: “CHD, where the coronary arteries that supply the heart muscle with blood become narrowed by a gradual build-up of fatty material, is the leading cause of death in the UK.

“This exciting project at King’s College London will use the most advanced computing methods to develop a new test with the aim of benefiting patients with CHD as soon as possible. We look forward to supporting Dr Lee and his team and seeing the results of this pioneering medical research.”

Heart Research UK’s NET Grants are for research projects which focus on the development of new and innovative technologies to diagnose, treat and prevent heart disease and related conditions.  They have given out NET Grants since 2006, awarding £2,657,041 in total.