The Association of Coronary Fat Attenuation Index Quantified by Automated Software on Coronary Computed Tomography Angiography with Adverse Events in Patients with Less than Moderate Coronary Artery Stenosis

Abstract

Objective: This study analyzed the relationship between the coronary FAI on CCTA and coronary adverse events in patients with moderate coronary artery disease based on machine learning. Methods: A total of 172 patients with coronary artery disease with moderate or lower coronary artery stenosis were included. According to whether the patients had coronary adverse events, the patients were divided into an adverse group and a non-adverse group. The coronary FAI of patients was quantified via machine learning, and significant differences between the two groups were analyzed via t-test. Results: The age difference between the two groups was statistically significant (p p > 0.05). There was a significant difference in the FAIs between the two groups (p p < 0.001).

Keywords

• coronary heart disease
• PCAT
• machine learning
• FAI
• vascular inflammation