A new study has shown the remarkable potential of artificial intelligence (AI) technology in analyzing coronary angiography, a common diagnostic procedure for coronary artery disease.
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The study has been published in the journal JMIR Cardio.
Headed by Dr. In Tae Moon, the study performed at Uijeongbu Eulji University Hospital in Korea exhibits the power of AI-based quantitative coronary angiography (AI-QCA) in improving clinical decision-making.
The study made a comparison of the AI-QCA to intravascular ultrasound (IVUS) to validate its performance. IVUS is an extensively utilized imaging tool to evaluate coronary artery stenotic lesions. In other words, such lesions could lead to cause narrowing of the coronary arteries and additionally limit the blood flow to the heart.
The analysis contained more than 54 considerable lesions from 47 patients who underwent IVUS-guided coronary intervention. The scientists discovered that AI-QCA offered precise and comfortable measurements of coronary stenotic lesions, similar to IVUS, thus indicating that it can be safely utilized in clinical practice.
With the help of an MPXA-2000 (Medipixel), the AI-QCA analysis was executed, a newly developed software that makes use of an algorithm intended to copy the QCA process performed by human experts.
The AI-enabled QCA could automatically examine 2D angiography images and hence guide physicians in identifying optimal stent sizes. Hence, this technology can enhance patient outcomes and assist clinical decision-making.
We believe that this novel tool could provide confidence to treating physicians and help in making optimal clinical decisions.
Dr In Tae Moon, Study Lead Author, Uijeongbu Eulji University Hospital
A groundbreaking approach has been offered by AI-QCA to examine coronary angiography images, thereby offering automated and real-time insights. This study marks a significant step forward in the application of AI to enhance cardiovascular care.
While the study offers useful outcomes, additional research is needed to completely explore the clinical utility and safety of AI-QCA.
Journal Reference
Moon, I. T., et al. (2023) Accuracy of Artificial Intelligence–Based Automated Quantitative Coronary Angiography Compared to Intravascular Ultrasound: Retrospective Cohort Study. JMIR Cardio. doi.org/10.2196/45299.
Source: https://www.jmirpublications.com/