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Coronary Stenosis

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Myocardial Fractional Flow Reserve Measurement Using Contrast Media as a First-Line Assessment of Coronary Lesions in Current Practice.

The Canadian journal of cardiology
BACKGROUND: Fractional flow reserve (FFR) measurement requires adenosine injection. However, adenosine can induce conductive and rhythmic complications, or be contraindicated in some patients. Contrast-induced hyperemia could provide a simple first-l...

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

Medical image analysis
Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for d...

Diagnostic Performance of Artificial Neural Network for Detecting Ischemia in Myocardial Perfusion Imaging.

Circulation journal : official journal of the Japanese Circulation Society
BACKGROUND: The purpose of this study was to apply an artificial neural network (ANN) in patients with coronary artery disease (CAD) and to characterize its diagnostic ability compared with conventional visual and quantitative methods in myocardial p...

Non-invasive physiological assessment of intermediate coronary stenoses from plain angiography through artificial intelligence: the STARFLOW system.

European heart journal. Quality of care & clinical outcomes
BACKGROUND: Despite evidence supporting use of fractional flow reserve (FFR) and instantaneous waves-free ratio (iFR) to improve outcome of patients undergoing coronary angiography (CA) and percutaneous coronary intervention, such techniques are stil...

Relationship of age, atherosclerosis and angiographic stenosis using artificial intelligence.

Open heart
OBJECTIVE: The study evaluates the relationship of coronary stenosis, atherosclerotic plaque characteristics (APCs) and age using artificial intelligence enabled quantitative coronary computed tomographic angiography (AI-QCT).

Deep learning for prediction of fractional flow reserve from resting coronary pressure curves.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
BACKGROUND: It would be ideal for a non-hyperaemic index to predict fractional flow reserve (FFR) more accurately, given FFR's extensive validation in a multitude of clinical settings.

Training and validation of a deep learning architecture for the automatic analysis of coronary angiography.

EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology
BACKGROUND: In recent years, the use of deep learning has become more commonplace in the biomedical field and its development will greatly assist clinical and imaging data interpretation. Most existing machine learning methods for coronary angiograph...

Feasibility of using deep learning to detect coronary artery disease based on facial photo.

European heart journal
AIMS: Facial features were associated with increased risk of coronary artery disease (CAD). We developed and validated a deep learning algorithm for detecting CAD based on facial photos.