Coronary Microcirculation in Acute Myocardial Infarction and the Clinical Significance of Artificial Intelligence-Based Software

Abstract

Background: Cardiovascular diseases (CVDs) is a third leading cause of non-communicable diseases and a leading cause of mortality in Mongolia. Among these, acute myocardial infarction (AMI), a complication of coronary artery disease (CAD), is a leading cause of cardiovascular mortality. In patients with AMI, both epicardial artery blood flow, observed through coronary angiography, and coronary microcirculatory dysfunction (CMD) play critical roles in the disease’s pathophysiology. Recent advancements have introduced artificial intelligence (AI)-based softwares which are capable of analyzing coronary blood flow from coronary angiography images. The AI based softwares can assess not only epicardial blood flow but also CMD in recent studies. In this review, we discussed the role of CMD in pathophysiology of AMI, diagnostic approaches, the application of AI-based technologies, their clinical significance, and future directions. Aim: This review aims to explore the pathophysiological relationship of coronary microcirculatory dysfunction (CMD) in the context of acute myocardial infarction (AMI), diagnostic methodologies, the application of artificial intelligence (AI)-based technologies, and their clinical significance. Hypotheses: 1. AI-based software allows for highly accurate assessment of coronary microcirculation during AMI. 2. CMD during AMI is associated with structural and functional changes in the heart. 3. CMD during AMI is related to disease prognosis and patient outcomes. Methodology: This narrative review was compiled using a systematic and logical approach, based on publicly available recent clinical and biomedical research literature addressing the above hypotheses. Conclusion: In recent years, AI-based image processing software has been developed to analyze angiographic images obtained during percutaneous coronary intervention (PCI) and treatment procedures. These tools show significant promise for early detection and improved diagnosis of CMD during AMI, as well as for better assessment of shortand long-term patient risk.