AIMC Topic: Coronary Stenosis
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Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.
Biomolecules & biomedicine
Sep 6, 2024
Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major a...
Integrated deep learning model for automatic detection and classification of stenosis in coronary angiography.
Computational biology and chemistry
Aug 24, 2024
Coronary artery disease poses a significant threat to human health. In clinical settings, coronary angiography remains the gold standard for diagnosing coronary heart disease. A crucial aspect of this diagnosis involves detecting arterial narrowings....
Development of machine learning models for fractional flow reserve prediction in angiographically intermediate coronary lesions.
Catheterization and cardiovascular interventions : official journal of the Society for Cardiac Angiography & Interventions
Aug 1, 2024
BACKGROUND: Fractional flow reserve (FFR) represents the gold standard in guiding the decision to proceed or not with coronary revascularization of angiographically intermediate coronary lesion (AICL). Optical coherence tomography (OCT) allows to car...
Plaque, Atherosclerotic
Humans
Cardiac Catheterization
Software
Coronary Stenosis
Fractional Flow Reserve, Myocardial
Decision Support Techniques
Tomography, Optical Coherence
Databases, Factual
Coronary Angiography
Female
Coronary Artery Disease
Reproducibility of Results
Supervised Machine Learning
Aged
Coronary Vessels
Male
Middle Aged
Severity of Illness Index
Predictive Value of Tests
Noninvasive and fast method of calculation for instantaneous wave-free ratio based on haemodynamics and deep learning.
Computer methods and programs in biomedicine
Jul 23, 2024
BACKGROUND AND OBJECTIVES: Instantaneous wave-free ratio (iFR) is a new invasive indicator of myocardial ischaemia, and its diagnostic performance is as good as the "gold standard" of myocardial ischaemia diagnosis: fractional flow reserve (FFR). iFR...
Prognostic value of a novel artificial intelligence-based coronary CTA-derived ischemia algorithm among patients with normal or abnormal myocardial perfusion.
Journal of cardiovascular computed tomography
Apr 24, 2024
BACKGROUND: Among patients with obstructive coronary artery disease (CAD) on coronary computed tomography angiography (CTA), downstream positron emission tomography (PET) perfusion imaging can be performed to assess the presence of myocardial ischemi...
Humans
Artificial Intelligence
Algorithms
Prognosis
Retrospective Studies
Female
Reproducibility of Results
Risk Factors
Aged
Computed Tomography Angiography
Coronary Circulation
Myocardial Perfusion Imaging
Finland
Angina, Unstable
Coronary Stenosis
Adenosine
Coronary Angiography
Male
Coronary Artery Disease
Middle Aged
Positron-Emission Tomography
Severity of Illness Index
Coronary Vessels
Time Factors
Vasodilator Agents
Predictive Value of Tests
The value of AI-based analysis of fractional flow reserve of volume computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Apr 17, 2024
PURPOSE: The aim of our work was to demonstrate the importance of artificial intelligence-based analysis of fractional flow reserves of computed tomographically detected coronary artery stenosis with regard to their hemodynamic relevance in patients ...
Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.
The international journal of cardiovascular imaging
Apr 17, 2024
This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who und...
Vascular Calcification
Computed Tomography Angiography
Coronary Stenosis
Coronary Artery Disease
Observer Variation
Coronary Vessels
Multidetector Computed Tomography
Plaque, Atherosclerotic
Humans
Artificial Intelligence
Female
Reproducibility of Results
Aged
Male
Middle Aged
Severity of Illness Index
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Validation of a fully automated deep learning-enabled solution for CCTA atherosclerotic plaque and stenosis quantification in a diverse real-world cohort.
Journal of cardiovascular computed tomography
Mar 28, 2024
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Automation
Coronary Vessels
Plaque, Atherosclerotic
Middle Aged
Severity of Illness Index
Deep Learning
Predictive Value of Tests
Coronary Angiography
Computed Tomography Angiography
Humans
Coronary Stenosis
Retrospective Studies
Female
Reproducibility of Results
Aged
Male
Diagnostic performance of deep learning to exclude coronary stenosis on CT angiography in TAVI patients.
The international journal of cardiovascular imaging
Mar 10, 2024
We evaluated the diagnostic performance of a deep-learning model (DLM) (CorEx®, Spimed-AI, Paris, France) designed to automatically detect > 50% coronary stenosis on coronary computed tomography angiography (CCTA) images. We studied inter-observer va...
Coronary Stenosis
Transcatheter Aortic Valve Replacement
Observer Variation
Coronary Vessels
False Positive Reactions
Multidetector Computed Tomography
Computed Tomography Angiography
Aortic Valve Stenosis
Aortic Valve
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Aged
Humans
Aged, 80 and over
Retrospective Studies
Male
Female
Severity of Illness Index
Deep Learning
Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease.
European radiology
Feb 26, 2024
OBJECTIVES: To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis.
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