AI-Driven Quantitative Coronary CT Angiography in Suspected Coronary Artery Disease

20260 citationsJournal Articlediamond Open Access

Authors

Alexander van Rosendael · Leiden University Medical Center

Rine Nakanishi · Toho University

Jeroen J. Bax · Leiden University Medical Center

Gianluca Pontone · Centro Cardiologico Monzino

Saima Mushtaq · Centro Cardiologico Monzino

Ronny R. Buechel · University of Zurich

Christoph Gräni

Abstract

This first multicenter global registry with AI-guided quantitative CT identified noncalcified plaque burden and increment in stenosis severity as the most powerful predictors of MACE, demonstrating the interplay between traditional and novel measures of the severity of CAD. Standardized and rapid quantitative assessment of CAD may improve clinical implementation of multidimensional assessment of CAD as a cornerstone for risk assessment.

Topics & Keywords

Cardiac Imaging and Diagnostics Coronary Interventions and Diagnostics Cardiovascular Disease and Adiposity

UN Sustainable Development Goals

Good health and well-being

Publication Details

Published in: JACC Advances

Volume 5, Issue 3, pp. 102618-102618

DOI: 10.1016/j.jacadv.2026.102618

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