Machine Learning Algorithms to Distinguish Myocardial Perfusion SPECT Polar Maps.

Myocardial perfusion imaging (MPI) plays an important role in patients with suspected and documented coronary artery disease (CAD). Machine Learning (ML) algorithms have been developed for many medical applications with excellent performance. This study used ML algorithms to discern normal and abnormal gated Single Photon Emission Computed Tomography (SPECT) images.

Machine Learning Algorithms to Detect Sex in Myocardial Perfusion Imaging.

Myocardial perfusion imaging (MPI) is an essential tool used to diagnose and manage patients with suspected or known coronary artery disease. Additionally, the General Data Protection Regulation (GDPR) represents a milestone about individuals' data security concerns. On the other hand, Machine Learning (ML) has had several applications in the most diverse knowledge areas.

Quantification of Calcified Coronary Plaques by Chest Computed Tomography: Correlation with the Calcium Score Technique.

Background: Cardiovascular disease is the leading cause of mortality in the world. Parietal calcifications of the arteries may be visualized and quantified at initial and subclinical states by computed tomography (CT), and expressed as calcium score (CS). It is possible to estimate the prognosis of future cardiovascular events using this score.

Artificial Intelligence in Cardiology: Concepts, Tools and Challenges - "The Horse is the One Who Runs, You Must Be the Jockey".

The recent advances at hardware level and the increasing requirement of personalization of care associated with the urgent needs of value creation for the patients has helped Artificial Intelligence (AI) to promote a significant paradigm shift in the most diverse areas of medical knowledge, particularly in Cardiology, for its ability to support decision-making and improve diagnostic and prognostic performance. In this context, the present work does a non-systematic review of the main papers published on AI in Cardiology, focusing on its main applications, potential impacts and challenges.

Myocardial Perfusion by Coronary Computed Tomography in the Evaluation of Myocardial Ischemia: Simultaneous Stress Protocol with SPECT.

Background: Functional assessment to rule out myocardial ischemia using coronary computed tomography angiography (CCTA) is extremely important and data on the Brazilian population are still limited.

Objective: To assess the diagnostic performance of myocardial perfusion by CCTA in the detection of severe obstructive coronary artery disease (CAD) compared with single-photon emission computerized tomography (SPECT). To analyze the importance of anatomical knowledge to understand the presence of myocardial perfusion defects on SPECT imaging that is not identified on computed tomography (CT) scan.

Diagnostic performance of combined cardiac MRI for detection of coronary artery disease.

Objective: To evaluate the diagnostic performance of stress perfusion cardiac MR (CMR) for detecting significant CAD (≥70% narrowing) in comparison with invasive coronary angiography (ICA) as a reference standard.

Methods: Examinations of 54 patients who underwent both stress perfusion CMR and ICA for investigation of CAD between 2007 and 2009 were evaluated. The CMR protocol included dipyridamole stress and rest perfusion, stress and rest cine MRI for assessment of ventricular function and delayed gadolinium enhancement for assessment of myocardial viability and detection of infarction.