Cardiologist user experience of artificial intelligence-based quantitative coronary angiography.

ABSTRACT:

Background

Artificial intelligence-assisted quantitative coronary angiography (AI-QCA) has been developed to enable the automated, objective assessment of coronary artery stenosis without human intervention. Previous studies have shown its accuracy compared with manual QCA and intravascular ultrasound. In this study, we aimed to evaluate cardiologists' experience of analyzing coronary lesions with AI-QCA.

Methods

Ten board-certified cardiologists from multiple centers specializing in coronary intervention, with varying periods of experience, participated in this study. They analyzed angiograms from 180 patients with marked coronary stenosis requiring coronary revascularization. Correlations between manual QCA and AI-QCA were measured by using Pearson's or Spearman's correlat

SUBMITTER: Kwon O 

PROVIDER: S-EPMC12775163 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature