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Coronary Artery Disease

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Coronary artery disease evaluation during transcatheter aortic valve replacement work-up using photon-counting CT and artificial intelligence.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to evaluate the capabilities of photon-counting (PC) CT combined with artificial intelligence-derived coronary computed tomography angiography (PC-CCTA) stenosis quantification and fractional flow reserve predic...

Machine learning-based coronary artery calcium score predicted from clinical variables as a prognostic indicator in patients referred for invasive coronary angiography.

European radiology
OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.

An Anatomy- and Topology-Preserving Framework for Coronary Artery Segmentation.

IEEE transactions on medical imaging
Coronary artery segmentation is critical for coronary artery disease diagnosis but challenging due to its tortuous course with numerous small branches and inter-subject variations. Most existing studies ignore important anatomical information and vas...

Non-invasive fractional flow reserve estimation using deep learning on intermediate left anterior descending coronary artery lesion angiography images.

Scientific reports
This study aimed to design an end-to-end deep learning model for estimating the value of fractional flow reserve (FFR) using angiography images to classify left anterior descending (LAD) branch angiography images with average stenosis between 50 and ...

A stepwise strategy integrating dynamic stress CT myocardial perfusion and deep learning-based FFR in the work-up of stable coronary artery disease.

European radiology
OBJECTIVES: To validate a novel stepwise strategy in which computed tomography-derived fractional flow reserve (FFR) is restricted to intermediate stenosis on coronary computed tomography angiography (CCTA) and computed tomography myocardial perfusio...

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

European radiology
OBJECTIVES: To prospectively investigate whether fully automated artificial intelligence (FAAI)-based coronary CT angiography (CCTA) image processing is non-inferior to semi-automated mode in efficiency, diagnostic ability, and risk stratification of...

A combined analysis of TyG index, SII index, and SIRI index: positive association with CHD risk and coronary atherosclerosis severity in patients with NAFLD.

Frontiers in endocrinology
BACKGROUND: Insulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resi...

Deep learning-based prediction of coronary artery calcium scoring in hemodialysis patients using radial artery calcification.

Seminars in dialysis
OBJECTIVE: This study used random forest model to explore the feasibility of radial artery calcification in prediction of coronary artery calcification in hemodialysis patients.

A comprehensive approach to prediction of fractional flow reserve from deep-learning-augmented model.

Computers in biology and medicine
The underuse of invasive fractional flow reserve (FFR) in clinical practice has motivated research towards non-invasive prediction of FFR. Although the non-invasive derivation of FFR (FFR) using computational fluid dynamics (CFD) principles has becom...