AI-based technology offers accurate analysis of cardiac disease

A ground-breaking study published in JMIR Cardio, has unveiled the immense potential of artificial intelligence (AI) technology in revolutionising the analysis of coronary angiography, a widely used diagnostic procedure for cardiac disease, such as coronary artery disease. Led by Dr In Tae Moon, researchers at Uijeongbu Eulji University Hospital, South Korea, showcased the efficacy of AI-based quantitative coronary angiography (AI-QCA) in significantly enhancing clinical decision-making.

To validate the performance of AI-QCA, the study compared it to intravascular ultrasound (IVUS), a commonly used imaging tool for assessing coronary artery stenotic lesions. These lesions can lead to the narrowing of coronary arteries and impede blood flow to the heart. The analysis involved 54 significant lesions from 47 patients who underwent IVUS-guided coronary intervention. The findings revealed that AI-QCA provided accurate and consistent measurements of coronary stenotic lesions, akin to IVUS, thereby suggesting its safe applicability in clinical practice.

The analysis with AI-QCA was carried out using MPXA-2000 (Medipixel), a newly developed software that utilises an algorithm designed to replicate the quantitative coronary angiography process conducted by human experts. By automatically analysing 2D angiography images, AI-enabled QCA can guide physicians in determining optimal stent sizes. This innovative technology holds the potential to enhance patient outcomes and facilitate clinical decision-making.  Moon, the lead author of the study, emphasised, “We believe that this novel tool could instil confidence in treating physicians and aid in making optimal clinical decisions”.

AI-QCA represents a transformative approach to analysing coronary angiography images, providing automated and real-time insights. This study marks a significant stride forward in leveraging AI to advance cardiovascular care. While the results of the study are promising, further research is needed to fully explore the clinical utility and safety of AI-QCA.