AIMC Topic: Coronary Angiography

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Enhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.

The international journal of cardiovascular imaging Jan 29, 2025
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MP...
Radiographic Image Interpretation, Computer-Assisted Middle Aged Humans Coronary Artery Disease Severity of Illness Index Artificial Intelligence Coronary Vessels Predictive Value of Tests Coronary Stenosis Coronary Angiography Retrospective Studies Female Reproducibility of Results Aged Male
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Application of deep learning in automated localization and interpretation of coronary artery calcification in oncological PET/CT scans.

The international journal of cardiovascular imaging Jan 13, 2025
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radia...
Coronary Vessels Vascular Calcification Positron Emission Tomography Computed Tomography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Humans Automation Middle Aged Neoplasms Deep Learning Predictive Value of Tests Retrospective Studies Coronary Angiography Female Reproducibility of Results Aged Male
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Diagnostic accuracy in coronary CT angiography analysis: artificial intelligence versus human assessment.

Open heart Jan 11, 2025
BACKGROUND: Visual assessment of coronary CT angiography (CCTA) is time-consuming, influenced by reader experience and prone to interobserver variability. This study evaluated a novel algorithm for coronary stenosis quantification (atherosclerosis im...
Retrospective Studies Female Reproducibility of Results Aged Male Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Humans Coronary Stenosis Artificial Intelligence Algorithms Coronary Artery Disease Observer Variation Coronary Vessels Computed Tomography Angiography
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End-to-end deep-learning model for the detection of coronary artery stenosis on coronary CT images.

Open heart Jan 11, 2025
PURPOSE: We examined whether end-to-end deep-learning models could detect moderate (≥50%) or severe (≥70%) stenosis in the left anterior descending artery (LAD), right coronary artery (RCA) or left circumflex artery (LCX) in iodine contrast-enhanced ...
Coronary Stenosis Aged Humans Male Retrospective Studies Predictive Value of Tests Middle Aged Female Severity of Illness Index Coronary Angiography Reproducibility of Results Deep Learning Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Computed Tomography Angiography
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Automated classification of coronary LEsions fRom coronary computed Tomography angiography scans with an updated deep learning model: ALERT study.

European radiology Jan 10, 2025
OBJECTIVES: The use of deep learning models for quantitative measurements on coronary computed tomography angiography (CCTA) may reduce inter-reader variability and increase efficiency in clinical reporting. This study aimed to investigate the diagno...
Humans Retrospective Studies Female Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Observer Variation Computed Tomography Angiography Coronary Stenosis Aged Male Middle Aged Deep Learning Coronary Angiography
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Automated stenosis estimation of coronary angiographies using end-to-end learning.

The international journal of cardiovascular imaging Jan 9, 2025
The initial evaluation of stenosis during coronary angiography is typically performed by visual assessment. Visual assessment has limited accuracy compared to fractional flow reserve and quantitative coronary angiography, which are more time-consumin...
Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels Humans Coronary Stenosis Aged Retrospective Studies Fractional Flow Reserve, Myocardial Male Female Middle Aged Reproducibility of Results Severity of Illness Index Deep Learning
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Predicting mortality after transcatheter aortic valve replacement using AI-based fully automated left atrioventricular coupling index.

Journal of cardiovascular computed tomography Jan 9, 2025
BACKGROUND: This study aimed to determine whether artificial intelligence (AI)-based automated assessment of left atrioventricular coupling index (LACI) can provide incremental value above other traditional risk factors for predicting mortality among...
Transcatheter Aortic Valve Replacement Radiographic Image Interpretation, Computer-Assisted Automation Atrial Function, Left Computed Tomography Angiography Ventricular Function, Left Stroke Volume Risk Assessment Severity of Illness Index Time Factors Treatment Outcome Aortic Valve Stenosis Aortic Valve Predictive Value of Tests Coronary Angiography Female Risk Factors Aged Aged, 80 and over Male Humans Artificial Intelligence Retrospective Studies
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Segmentation and Vascular Vectorization for Coronary Artery by Geometry-Based Cascaded Neural Network.

IEEE transactions on medical imaging Jan 2, 2025
Segmentation of the coronary artery is an important task for the quantitative analysis of coronary computed tomography angiography (CCTA) images and is being stimulated by the field of deep learning. However, the complex structures with tiny and narr...
Computed Tomography Angiography Algorithms Image Processing, Computer-Assisted Coronary Angiography Coronary Vessels Humans Neural Networks, Computer
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Clinical Validation of a Deep Learning Algorithm for Automated Coronary Artery Disease Detection and Classification Using a Heterogeneous Multivendor Coronary Computed Tomography Angiography Data Set.

Journal of thoracic imaging Jan 1, 2025
PURPOSE: We sought to clinically validate a fully automated deep learning (DL) algorithm for coronary artery disease (CAD) detection and classification in a heterogeneous multivendor cardiac computed tomography angiography data set.
Humans Algorithms Retrospective Studies Female Middle Aged Deep Learning Coronary Angiography Reproducibility of Results Coronary Artery Disease Aged Computed Tomography Angiography Adult Sensitivity and Specificity Male
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Computerized classification method for significant coronary artery stenosis on whole-heart coronary MRA using 3D convolutional neural networks with attention mechanisms.

Radiological physics and technology Dec 31, 2024
This study aims to develop a computerized classification method for significant coronary artery stenosis on whole-heart coronary magnetic resonance angiography (WHCMRA) images using a 3D convolutional neural network (3D-CNN) with attention mechanisms...
Heart Male Humans Magnetic Resonance Angiography Middle Aged Neural Networks, Computer Convolutional Neural Networks Coronary Stenosis Female Imaging, Three-Dimensional Aged Coronary Angiography
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