Automated Artificial Intelligence Based Interpretation Of Coronary CTA: Plaque Volume, Plaque Characterization And High Risk Plaque Compared With Consensus Of Level III Expert Readers

Abstract

Introduction: Quantitative atherosclerosis evaluation has high clinical import, but the analysis is time-intensive and requires high expertise. Artificial intelligence (AI), through machine learning algorithms is an emerging approach to quantitative image processing and automated interpretation. We present results of the first FDA-cleared, commercially available, end-to-end AI-based solution for the automated evaluation of quantitative atherosclerotic plaque volume, characterization and identification of high-risk plaque on coronary CT angiography (CCTA).