May Advanced technology offers revolutionary coronary care

Harnessing AI would enable advancement of cardiovascular care for millions, with greatest impact in the developing world

Pioneering technology offers physicians more accurate understanding of heart condition, leading to better patient outcomes

A world-leading interventional cardiologist and researcher at University of Galway has called for a revolutionary change in healthcare – with artificial intelligence, machine learning and virtual reality to be used to better diagnose and treat cardiac patients.

Professor of Interventional Cardiology William Wijns, along with international colleagues from China, Italy, Switzerland and the USA, is urging the adoption of the most advanced technologies to empower clinicians to uncover previously concealed information within a coronary angiogram.

Professor Wijns made the call in a specially commissioned article in Nature Review in Cardiology.

In the paper, Professor Wijns emphasised the limitations of relying solely on traditional visual angiographic guidance for diagnosis and treatment of coronary artery disease. He cited previously published research which showed that diagnosis and treatment through the cardio-angiogram led to inappropriate stenting and overtreatment in 37% of patients; that 30% of interventional procedures are deemed unnecessary; and 20% are found to be needed but not performed.

Stenting, although a common procedure, comes with potential problems to the patient, such as restenosis, thrombosis, damage to blood vessels and other risks. When the cardiologist uses angiographic images to precisely navigate catheters through arteries, results are not always optimal - about 50% of patients end up with suboptimal functional outcomes, leaving them vulnerable to further heart issues in the short and long term.

Professor Wijns explained: “It is time for a paradigm shift in how we diagnose and treat coronary patients. We have good evidence that a new approach, taking into account the unique physiological characteristics of each patient’s heart, allows for more precise and effective treatment decisions. By integrating advanced technologies, such as artificial intelligence, into the interventional procedures, physicians can obtain a more accurate understanding of the heart's condition, leading to better patient outcomes, reducing the risk of adverse events, and preventing subsequent problems.”

Research contends that recent advances in AI, machine learning and virtual reality can empower interventional cardiologists to uncover previously concealed information within a standard cardio-angiogram. This additional information holds significant implications and advantages for patients, providing a deeper insight into their individual condition. Blockages in smaller blood vessels in particular can also now be uncovered from image based AI.

This new approach enables a more tailored response and treatment approach. This advancement will enable physicians to refine patient treatments, resulting in enhanced interventions compared to traditional angiograms, that don’t use AI assistance.

Professor Wijns continued: “While the integration of artificial intelligence into coronary disease diagnosis and treatment planning represents a significant step forward in boosting accessibility on a global scale, it has never been more important to increase access to resources. Our new approach is refining the understanding of how blockages and other obstacles are impeding normal blood flow to the heart. Enabling access to this AI-led approach will advance cardiovascular care in emerging nations, bridging the gap with the first world and fostering substantial global impact, while also decreasing differences in quality of care in centres in the developed world.

“Additional research is currently underway to validate the effectiveness of these new strategies, and we are optimistic about the potential to revolutionise care of coronary artery disease and improve the lives of millions of patients worldwide.”

The paper can be accessed here: https://doi.org/10.1038/s41569-024-01014-0

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