A routine strategy that assesses function of all epicardial vessels at the time of diagnostic angiography in patients with new-onset chest pain doesn’t cost any more than conventional diagnostic ...

Please provide your email address to receive an email when new articles are posted on . Implementing a CT angiography-derived fractional flow reserve program improved certain outcomes in patients with ...

After controlling for known CV risk factors, all FFR-CT subgroups remained significantly associated with MI, revascularization. (HealthDay News) — For patients with coronary artery disease (CAD), ...

Please provide your email address to receive an email when new articles are posted on . Abnormal FFR-CT findings were significantly prognostic of poor long-term outcomes in patients with stable angina ...

A score derived from plaque features on coronary CT angiography (CCTA) using machine learning can predict ischemia just as well as CT-derived estimates of fractional flow reserve (FFR-CT), with the ...

In patients with coronary artery disease scheduled for a percutaneous intervention (PCI), fractional flow reserve (FFR) assessment at the time of angiography significantly improves outcome, but it has ...

OAK BROOK, Ill. – A new study showed that a non-invasive imaging test can help identify patients with coronary artery blockage or narrowing who need a revascularization procedure. The findings were ...

OAK BROOK, Ill. – An advanced CT test can identify individuals with stable angina at a reduced risk of three-year adverse outcomes despite their having a high coronary artery calcium score, according ...

A new study found that a non-invasive, AI enabled Coronary Computer Tomography Angiography effectively identified stenosis equally well or better than the conventional gold standard of invasive ...

Cedars-Sinai investigators and colleagues have developed an artificial intelligence (AI) tool that uses computed tomography (CT) scans to identify patients at risk of reduced blood flow to the heart.

Researchers at the University of Pennsylvania have developed CAMEL, an AI model that interprets ECG data like language to forecast cardiac events minutes before they occur. In parallel, advances in CT ...