Abstract
AbstractIn recent years, coronary computed tomography angiography (CCTA) has emerged as an accurate and safe non-invasive imaging modality in terms of detecting and excluding coronary artery disease (CAD). In the latest European Society of Cardiology Guidelines CCTA received Class I recommendation for the evaluation of patients with stable chest pain with low to intermediate clinical likelihood of CAD. Despite its high negative predictive value, the diagnostic performance of CCTA is limited by the relatively low specificity, especially in patients with heavily calcified lesions. The discrepancy between the degree of stenosis and ischemia is well established based on both invasive and non-invasive tests. The rapid evolution of computational flow dynamics has allowed the simulation of CCTA derived fractional flow reserve (FFR-CT), which improves specificity by combining anatomic and functional information regarding coronary atherosclerosis. FFR-CT has been extensively validated against invasively measured FFR as the reference standard. Due to recent technological advancements FFR-CT values can also be calculated locally, without offsite processing. Wall shear stress (WSS) and axial plaque stress (APS) are additional key hemodynamic elements of atherosclerotic plaque characteristics, which can also be measured using CCTA images. Current evidence suggests that WSS and APS are important hemodynamic features of adverse coronary plaques. CCTA based hemodynamic calculations could therefore improve prognostication and the management of patients with stable CAD.
Highlights
Coronary Computed Tomography Angiography (CCTA) is currently the most accurate noninvasive imaging modality that enables the detection and characterization of coronary artery disease (CAD) [1,2,3]
This study demonstrated a proof of concept which indicates that the availability of fractional flow reserve (FFR)-CT has an essential role in identifying significant CAD, on the management of patients with stable chest pain [46]
The aim of the study was to assess the benefits of non-invasive hemodynamic indices in the identification of high-risk plaques that led to acute coronary syndrome
Summary
Coronary Computed Tomography Angiography (CCTA) is currently the most accurate noninvasive imaging modality that enables the detection and characterization of coronary artery disease (CAD) [1,2,3]. On a per patient level the positive predictive value (89%) and the overall diagnostic accuracy (85%) improved by adding ML-based FFR-CT [38, 43] According to these promising study results ML-based algorithms might play a more significant role in the future of CCTA with rapid assessment of hemodynamically significant CAD. In the SYNTAX III Revolution study (A Randomized Study Investigating the Use of CT Scan and Angiography of the Heart to Help the Doctors Decide Which Method is the Best to Improve Blood Supply to the Heart in Patients With Complex Coronary Artery Disease), FFR-CT was examined for its role in treatment decision changes and planning in terms of coronary artery bypass graft versus PCI [50].
Published Version (
Free)
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have