Machine learning can accurately predict survival after echocardiography by analyzing unique data produced from heart images and electronic health record (EHR) information, according to a recent study in the Journal of the American College of Cardiology: Cardiovascular Imaging.

A new vascular imaging technique—coronary ultrafast Doppler angiography (CUDA)—can accurately and noninvasively map the intramyocardial coronary structure and quantify fluctuations in intramural coronary blood flow.

Machine learning models using echocardiographic data and variables from the electronic health record (EHR) can significantly improve mortality predictions compared to traditional risk scores, researchers reported in JACC: Cardiovascular Imaging.

The U.S. Preventive Services Task Force (USPSTF) issued a Grade D recommendation against screening with resting or exercise electrocardiography (ECG) to prevent cardiovascular disease events in asymptomatic adults at low risk of CVD events.

CT angiography (CTA), coupled with fractional flow reserve (FFR), demonstrated an ability to detect functionally significant lesions in patients with multivessel coronary artery disease (CAD).

A noninvasive imaging technique combined with fractional flow reserve (FFR) showed the potential to detect functionally significant lesions in patients with multivessel coronary artery disease (CAD), according to a study published June 11 in the Journal of the American College of Cardiology.

A scientist at the American Society of Clinical Oncology (ASCO)’s annual meeting discussed how cardiac imaging and biomarker measurements could improve care for cancer survivors.

Affidea, the leading European provider of diagnostic imaging, outpatient and cancer care services, announced that 11 of its centers have been awarded "5 Stars" on the EuroSafe Wall by the European Society of Radiology.