Impact of machine-learning CT-derived fractional flow reserve for the diagnosis and management of coronary artery disease in the randomized CRESCENT trials.
Journal:
European radiology
Published Date:
Jul 1, 2020
Abstract
OBJECTIVE: To determine the potential impact of on-site CT-derived fractional flow reserve (CT-FFR) on the diagnostic efficiency and effectiveness of coronary CT angiography (CCTA) in patients with obstructive coronary artery disease (CAD) on CCTA.
Authors
Keywords
Aged
Cardiac Catheterization
Cohort Studies
Computed Tomography Angiography
Coronary Angiography
Coronary Artery Disease
Coronary Stenosis
Disease Management
Female
Fractional Flow Reserve, Myocardial
Hemodynamics
Humans
Machine Learning
Male
Middle Aged
Percutaneous Coronary Intervention
Retrospective Studies
Tomography, X-Ray Computed