AIMC Topic: Coronary Angiography

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Prediction of obstructive coronary artery disease using coronary calcification and epicardial adipose tissue assessments from CT calcium scoring scans.

Journal of cardiovascular computed tomography Feb 4, 2025
BACKGROUND: Low-cost/no-cost non-contrast CT calcium scoring (CTCS) exams can provide direct evidence of coronary atherosclerosis. In this study, using features from CTCS images, we developed a novel machine learning model to predict obstructive coro...
Humans Machine Learning Decision Support Techniques Prognosis Coronary Angiography Coronary Artery Disease Coronary Vessels Vascular Calcification Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Female Reproducibility of Results Risk Factors Aged Male Middle Aged Risk Assessment Severity of Illness Index Adipose Tissue Predictive Value of Tests
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Ultra-low-dose coronary CT angiography via super-resolution deep learning reconstruction: impact on image quality, coronary plaque, and stenosis analysis.

European radiology Feb 1, 2025
OBJECTIVES: To exploit the capability of super-resolution deep learning reconstruction (SR-DLR) to save radiation exposure from coronary CT angiography (CCTA) and assess its impact on image quality, coronary plaque quantification and characterization...
Humans Prospective Studies Female Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Radiation Dosage Plaque, Atherosclerotic Aged Computed Tomography Angiography Male Coronary Stenosis Middle Aged Deep Learning Coronary Angiography
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A continuous-action deep reinforcement learning-based agent for coronary artery centerline extraction in coronary CT angiography images.

Medical & biological engineering & computing Jan 31, 2025
The lumen centerline of the coronary artery allows vessel reconstruction used to detect stenoses and plaques. Discrete-action-based centerline extraction methods suffer from artifacts and plaques. This study aimed to develop a continuous-action-based...
Computed Tomography Angiography Humans Reinforcement Machine Learning Algorithms Deep Learning Image Processing, Computer-Assisted Coronary Angiography Coronary Artery Disease Artifacts Coronary Vessels
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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...
Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Humans Coronary Vessels Aged Coronary Stenosis Artificial Intelligence Male Retrospective Studies Middle Aged Female Severity of Illness Index Reproducibility of Results Predictive Value of Tests
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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 Angiography Humans Coronary Vessels Male Positron Emission Tomography Computed Tomography Vascular Calcification Middle Aged Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Neoplasms Female Coronary Artery Disease Deep Learning Automation Reproducibility of Results Predictive Value of Tests Aged
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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...
Observer Variation Coronary Vessels Retrospective Studies Computed Tomography Angiography Female Coronary Stenosis Reproducibility of Results Severity of Illness Index Humans Aged Predictive Value of Tests Artificial Intelligence Male Coronary Angiography Algorithms Middle Aged Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease
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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 ...
Retrospective Studies Female Reproducibility of Results Aged Male Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Coronary Angiography Humans Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Computed Tomography Angiography Coronary Stenosis
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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...
Aged Male Middle Aged Deep Learning Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Humans Observer Variation Retrospective Studies Computed Tomography Angiography Female Coronary Stenosis Reproducibility of Results
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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...
Male Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Humans Retrospective Studies Female Reproducibility of Results Aged Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels
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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 Aged, 80 and over Coronary Angiography Male Ventricular Function, Left Radiographic Image Interpretation, Computer-Assisted Artificial Intelligence Stroke Volume Aortic Valve Stenosis Automation Retrospective Studies Risk Assessment Severity of Illness Index Atrial Function, Left Aortic Valve Humans Female Time Factors Predictive Value of Tests Computed Tomography Angiography Risk Factors Treatment Outcome Aged
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