Purpose This study investigated the impact of gender differences on the diagnostic
performance of machine-learning based coronary CT angiography (cCTA)-derived fractional …

Objective To investigate the effect of image quality of coronary CT angiography (CCTA) on
the diagnostic performance of a machine learning–based CT-derived fractional flow reserve …

Background Compared with invasive fractional flow reserve (FFR), coronary CT
angiography (cCTA) is limited in detecting hemodynamically relevant lesions. cCTA-based …

Objectives This study was conducted to investigate the influence of coronary artery calcium
(CAC) score on the diagnostic performance of machine-learning–based coronary computed …

Coronary artery disease (CAD) is a common clinical cardiovascular disease. Fractional flow
reserve (FFR) is the criterion standard for assessing coronary hemodynamics. 1 Based on …

Objectives To examine the diagnostic accuracy of machine learning–based coronary CT
angiography–derived fractional flow reserve (FFRCT) in diabetes mellitus (DM) patients …

Purpose To evaluate the diagnostic performance of coronary computed tomography
angiography derived fractional flow reserve (CT-FFR) with invasive fractional flow reserve …

Purpose To compare two technical approaches for determination of coronary computed
tomography (CT) angiography–derived fractional flow reserve (FFR)—FFR derived from …

OBJECTIVE. Coronary CT angiography (CCTA)-based methods allow noninvasive
estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) …

Background: Coronary computed tomographic angiography (CTA) is a reliable modality to
detect coronary artery disease. However, CTA generally overestimates stenosis severity …