Background And Aims: Coronary angiography-derived wall shear stress (WSS) may enable identification of vulnerable plaques and patients. A new recently introduced software allows seamless three-dimensional quantitative coronary angiography (3D-QCA) reconstruction and WSS computation within a single user-friendly platform carrying promise for clinical applications. This study examines for the first time the efficacy of this software in detecting vulnerable lesions in patients with intermediate non-flow limiting stenoses.
View Article and Find Full Text PDFTraditionally, coronary angiography was restricted to visual estimation of contrast-filled lumen in coronary obstructive diseases. Over the previous decades, considerable development has been made in quantitatively analyzing coronary angiography, significantly improving its accuracy and reproducibility. Notably, the integration of artificial intelligence (AI) and machine learning into quantitative coronary angiography (QCA) holds promise for further enhancing diagnostic accuracy and predictive capabilities.
View Article and Find Full Text PDFJACC Basic Transl Sci
November 2024
Circ Cardiovasc Interv
December 2024