Aims Traditional prognostic risk assessment in patients undergoing non-invasive imaging is
based upon a limited selection of clinical and imaging findings. Machine learning (ML) can …

Background: The future risk of myocardial infarction is commonly assessed using cardiovascular
risk scores, coronary artery calcium score, or coronary artery stenosis severity. We …

Data science is likely to lead to major changes in cardiovascular imaging. Problems with
timing, efficiency, and missed diagnoses occur at all stages of the imaging chain. The …

Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML),
which is a subset of AI wherein machines autonomously acquire information by extracting …

Background There have been limited data regarding the value of gated single photon emission
computed tomography (SPECT) myocardial perfusion imaging (MPI) for the detection of …

Objectives : To determine normal limits for ascending and descending thoracic aorta diameters
in a large population of asymptomatic, low-risk adult subjects. Background : Assessment …

Radionuclide myocardial perfusion imaging (MPI) is among the most commonly performed
diagnostic tests in cardiology. Although the diagnostic and prognostic applications of …

The purpose of this document is to update the “ASNC Imaging Guidelines for Nuclear
Cardiology Procedures: Single photon-emission computed tomography” 1 in several areas in …

… Slomka). The content is solely the responsibility of the authors and does not … , and Slomka
participate in software royalties for QPS software at Cedars-Sinai Medical Center. Dr. Slomka …

Objectives : We aimed to evaluate whether pericardial fat has value in predicting the risk of
future adverse cardiovascular outcomes. Background : Pericardial fat volume (PFV) and …