AIMC Topic: Coronary Vessels
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First comparison between artificial intelligence-guided coronary computed tomography angiography versus single-photon emission computed tomography testing for ischemia in clinical practice.
Coronary artery disease
Dec 20, 2024
BACKGROUND: Noninvasive cardiac testing with coronary computed tomography angiography (CCTA) and single-photon emission computed tomography (SPECT) are becoming alternatives to invasive angiography for the evaluation of obstructive coronary artery di...
Radiomics and deep learning features of pericoronary adipose tissue on non-contrast computerized tomography for predicting non-calcified plaques.
Journal of X-ray science and technology
Dec 18, 2024
BACKGROUND: Inflammation of coronary arterial plaque is considered a key factor in the development of coronary heart disease. Early the plaque detection and timely treatment of the atherosclerosis could effectively reduce the risk of cardiovascular e...
Artificial intelligence-derived coronary artery calcium scoring saves time and achieves close to radiologist-level accuracy accuracy on routine ECG-gated CT.
The international journal of cardiovascular imaging
Dec 16, 2024
Artificial Intelligence (AI) has been proposed to improve workflow for coronary artery calcium scoring (CACS), but simultaneous demonstration of improved efficiency, accuracy, and clinical stability have not been demonstrated. 148 sequential patients...
Cardiac-Gated Imaging Techniques
Coronary Vessels
Multidetector Computed Tomography
Vascular Calcification
Computed Tomography Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Workflow
Observer Variation
Aged
Male
Middle Aged
Severity of Illness Index
Predictive Value of Tests
Coronary Angiography
Artificial Intelligence
Radiologists
Time Factors
Retrospective Studies
Electrocardiography
Humans
Female
Reproducibility of Results
Machine learning-based radiomic features of perivascular adipose tissue in coronary computed tomography angiography predicting inflammation status around atherosclerotic plaque: a retrospective cohort study.
Annals of medicine
Dec 12, 2024
OBJECTIVES: This study expolored the relationship between perivascular adipose tissue (PVAT) radiomic features derived from coronary computed tomography angiography (CCTA) and the presence of coronary artery plaques. It aimed to determine whether PVA...
Artificial Intelligence-Driven Assessment of Coronary Computed Tomography Angiography for Intermediate Stenosis: Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve.
The American journal of cardiology
Dec 11, 2024
We aimed to compare artificial intelligence (AI)-based coronary stenosis evaluation of coronary computed tomography angiography (CCTA) with its quantitative counterpart of invasive coronary angiography (ICA) and invasive fractional flow reserve (FFR)...
Constraint-Aware Learning for Fractional Flow Reserve Pullback Curve Estimation From Invasive Coronary Imaging.
IEEE transactions on medical imaging
Dec 2, 2024
Estimation of the fractional flow reserve (FFR) pullback curve from invasive coronary imaging is important for the intraoperative guidance of coronary intervention. Machine/deep learning has been proven effective in FFR pullback curve estimation. How...
Automated Classification of Coronary Plaque on Intravascular Ultrasound by Deep Classifier Cascades.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 27, 2024
Intravascular ultrasound (IVUS) is the gold standard modality for in vivo visualization of coronary arteries and atherosclerotic plaques. Classification of coronary plaques helps to characterize heterogeneous components and evaluate the risk of plaqu...
Impact of tooth loss and patient characteristics on coronary artery calcium score classification and prediction.
Scientific reports
Nov 16, 2024
This study, for the first time, explores the integration of data science and machine learning for the classification and prediction of coronary artery calcium (CAC) scores. It focuses on tooth loss and patient characteristics as key input features to...
Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.
JACC. Cardiovascular interventions
Oct 30, 2024
BACKGROUND: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully automated) provides real-time, objective, and reproducible quantitative analysis of coronary angiography without requiring additional time or labor.
Image Interpretation, Computer-Assisted
Time Factors
Automation
Treatment Outcome
Coronary Vessels
Female
Predictive Value of Tests
Humans
Coronary Angiography
Aged
Tomography, Optical Coherence
Artificial Intelligence
Percutaneous Coronary Intervention
Male
Prospective Studies
Coronary Artery Disease
Middle Aged
Republic of Korea
Stents
Meta-analysis of deep learning approaches for automated coronary artery calcium scoring: Performance and clinical utility AI in CAC scoring: A meta-analysis: AI in CAC scoring: A meta-analysis.
Computers in biology and medicine
Oct 23, 2024
INTRODUCTION: Manual Coronary Artery Calcium (CAC) scoring, crucial for assessing coronary artery disease risk, is time-consuming and variable. Deep learning, particularly through Convolutional Neural Networks (CNNs), promises to automate and enhance...
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