Best Practices for Imaging of Transcatheter Valve Failure: An Update From the Heart Valve Collaboratory.

This updated Heart Valve Collaboratory framework addresses the growing concern for transcatheter valve failure (TVF) following transcatheter aortic valve replacement (TAVR). With the increasing volume of redo-TAV and surgical TAV explantation, there is a critical need for standardized pathways and protocols for evaluating TVF using echocardiography and cardiac computed tomography (CT) angiography. This document clarifies prior definitions of bioprosthetic valve deterioration and bioprosthetic valve failure in a practical, imaging directed context for TAVR.

Understanding Right Heart Flow: Implications for Interatrial Shunt Device Therapy in Heart Failure.

Elevation in left atrial pressure with subsequent pulmonary congestion is central to the pathology of heart failure. Interatrial shunts have emerged as a potential therapeutic strategy in patients with heart failure, especially those with diastolic dysfunction. These devices decrease left atrial pressure by shunting blood into the right atrium.

Imaging Assessment After Percutaneous Left Atrial Appendage Closure: From Immediate to Long-Term Follow-Up.

Growing evidence has demonstrated the clinical benefit of percutaneous left atrial appendage closure (LAAC) in patients with atrial fibrillation. Although procedural complication rates have declined with increasing experience, post-procedural device-related complications persist, impacting prognosis and reducing the long-term benefits of the procedure. Given the potential impact of these complications, surveillance imaging after LAAC is mandatory.

Artificial intelligence quantification and experienced reader computed tomography analysis for differentiating normal from minimally and mildly diseased coronary arteries: an early real-world compatibility study.

Differentiating normal from minimally and mildly diseased coronary arteries on coronary computed tomographic angiography (CCTA) is crucial, impacting treatment decisions due to the extremely low coronary artery event risk associated with the former. Artificial intelligence quantitative computed tomographic (AI-QCT) can potentially identify subclinical atherosclerosis in cases deemed normal by reader interpretation. We aimed to evaluate AI-QCT's ability to distinguish reader-determined normal coronary arteries from those with minimal and mild diseased on CCTA.