University news

A new research collaboration is setting out to develop computational tools to improve treatments for one of the world’s most common causes of death.
 
The University of Glasgow will lead the newly-established EPSRC Centre for Future PCI Planning, which aims to improve outcomes from a frequently-performed treatment for heart artery disease.
 
The Centre is supported by £1.25m in new funding from the UKRI Engineering and Physical Sciences Research Council. It will unite engineers, mathematicians, statisticians and doctors at the University of Glasgow with partners in industry, medicine and academia to take a new approach to planning treatment of the disease.
 
Blockage of heart arteries is the most common type of cardiovascular disease, contributing to around 16% of the world’s deaths each year. It occurs when plaque builds up in the walls of the arteries that deliver blood to the heart muscle, narrowing the arteries and restricting blood flow.
 
One of the most effective treatments for the disease is percutaneous coronary intervention, or PCI. PCI involves placing a scaffolding stent device or balloon to unblock the artery. These devices also deliver drugs to reduce the chances of the artery renarrowing in the future.
 
Despite the lifesaving success of PCI procedures, more than a quarter of patients in the UK will require repeat treatments, putting patients at risk of future problems including heart attacks. This places a considerable burden on healthcare services.
 
Currently, doctors have limited tools to guide them how best to treat the condition and to predict whether the PCI will be successful for an individual patient. Having a clearer idea of what to expect before the procedure is carried out gives doctors the chance to deliver the best outcome.  The Centre aims to revolutionise the way in which procedures are undertaken, by developing computational tools that enable the tailoring of the procedure for each individual patient.
 
The key to achieving this is the use of cutting-edge techniques to analyse images of the narrowed heart arteries, creating a more complete picture of the plaque buildup. Over the next four years, the Centre’s researchers will find new ways to harness the full potential of the information available from imaging to improve the outcomes of each patient’s procedure.
 
Using high-quality images that have been gathered from clinical trials in leading centres in Scotland and across the world, the team will build on existing mathematical models to develop better ways to visualise each stage of PCI procedures. Importantly, the team are aiming to build these tools whilst reducing the computer processing expense by harnessing the power of AI.

 
Dr Sean McGinty, of the James Watt School of Engineering, is the project’s principal investigator. He said: “Our population is living longer than ever before, partly because we now have very good treatments for heart artery disease. While that is undoubtedly good news for individuals and their families, healthcare services are being increasingly stretched.
 
“What we’re aiming to do with this project is develop faster and more robust methods to improve the effectiveness of treatments and significantly reduce the number of repeat PCI procedures. As well as delivering better results for patients, this will make a big difference to healthcare budgets in the future.
 
“By the end of this project, we will have developed a suite of computational tools, that we aim to integrate into the imaging and diagnostic systems already in use to deliver PCI treatments. We’re looking forward to playing our part in improving PCI procedures and providing the best possible outcomes for patients and health services alike.”
 
The Centre is supported by collaborators at the leading edge of clinical care, academia and industry including: Aarhus University Hospital, Abbott Vascular, Biosensors Europe SA. Boston Scientific, Cardiovascular Research Center Aalst, Columbia University Medical Centre, Golden Jubilee National Hospital, MedAlliance Ltd, Medis Medical Imaging System, Pie Medical Imaging and Politecnico di Torino.
 

First published: 12 June 2024