An Overview of Computational Coronary Physiology Technologies Based on Medical Imaging and Artificial Intelligence

Abstract

This article reviews four new technologies for assessment of coronary hemodynamics based on medical imaging and artificial intelligence, including quantitative flow ratio (QFR), optical flow ratio (OFR), computational fractional flow reserve (CT-FFR) and artificial intelligence (AI)-based instantaneous wave-free ratio (iFR). These technologies use medical imaging such as coronary angiography, computed tomography angiography (CTA), and optical coherence tomography (OCT), to reconstruct three-dimensional vascular models through artificial intelligence algorithms, simulate and calculate hemodynamic parameters in the coronary arteries, and achieve non-invasive and rapid assessment of the functional significance of coronary stenosis. This article details the working principles, advantages such as non-invasiveness, efficiency, accuracy, limitations such as image dependency, and assumption restrictions, of each technology. It also compares and analyzes the image dependency, calculation accuracy, calculation speed, and operation simplicity, of the four technologies. The results show that these technologies are highly consistent with the traditional invasive wire method, and shows distinct advantages in terms of accuracy, reliability, convenience and cost-effectiveness, but there are also factors that affect accuracy. The results of this review demonstrates that AI-based iFR technology is currently one of the most promising technologies. The main challenges and directions for future development are also discussed. These technologies bring new ideas for the non-invasive assessment of coronary artery disease, and are expected to promote the technological progress in this field.

Keywords

• coronary hemodynamics
• non-invasive assessment
• medical imaging
• quantitative flow ratio
• optical flow ratio
• computational fractional flow reserve
• instantaneous wave-free ratio