AIMC Topic: Coronary Vessels

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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...
Predictive Value of Tests Coronary Angiography Positron Emission Tomography Computed Tomography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels Vascular Calcification Aged Male Middle Aged Neoplasms Deep Learning Humans Retrospective Studies Female Reproducibility of Results
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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...
Reproducibility of Results Aged Male Middle Aged Severity of Illness Index Artificial Intelligence Algorithms Retrospective Studies Female Coronary Vessels Computed Tomography Angiography Coronary Stenosis Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Observer Variation Humans
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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 ...
Humans Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Coronary Vessels Computed Tomography Angiography Coronary Stenosis Female Middle Aged Reproducibility of Results Severity of Illness Index Aged Deep Learning Male Predictive Value of Tests 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 Humans Male Retrospective Studies Middle Aged Female Severity of Illness Index Reproducibility of Results Deep Learning Aged Coronary Vessels Coronary Stenosis Fractional Flow Reserve, Myocardial
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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...
Algorithms Image Processing, Computer-Assisted Humans Coronary Angiography Neural Networks, Computer Coronary Vessels Computed Tomography Angiography
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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...
Coronary Artery Disease Radiomics Humans Coronary Vessels Male Plaque, Atherosclerotic Tomography, X-Ray Computed Middle Aged Epicardial Adipose Tissue Female Deep Learning Adipose Tissue Aged
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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...
Time Factors Electrocardiography Predictive Value of Tests Coronary Angiography Radiologists Aged Multidetector Computed Tomography Humans Radiographic Image Interpretation, Computer-Assisted Male Vascular Calcification Artificial Intelligence Coronary Artery Disease Middle Aged Computed Tomography Angiography Retrospective Studies Workflow Severity of Illness Index Cardiac-Gated Imaging Techniques Female Observer Variation Reproducibility of Results Coronary Vessels
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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...
Humans Machine Learning Retrospective Studies Female Aged Plaque, Atherosclerotic Nomograms Computed Tomography Angiography Adipose Tissue Coronary Angiography Radiomics Coronary Artery Disease Male Coronary Vessels Middle Aged Inflammation
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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)...
Coronary Vessels Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Male Middle Aged Severity of Illness Index Predictive Value of Tests Coronary Angiography Artificial Intelligence Retrospective Studies Humans Female Aged
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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...
Humans Machine Learning Algorithms Male Deep Learning Coronary Angiography Coronary Vessels Fractional Flow Reserve, Myocardial
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