AIMC Topic: Vascular Calcification

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Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects.

Circulation. Cardiovascular imaging Feb 17, 2020
BACKGROUND: Epicardial adipose tissue (EAT) volume (cm) and attenuation (Hounsfield units) may predict major adverse cardiovascular events (MACE). We aimed to evaluate the prognostic value of fully automated deep learning-based EAT volume and attenua...
Prognosis Tomography, X-Ray Computed Female Risk Factors Aged Aged, 80 and over Humans Asymptomatic Diseases Pericardium Predictive Value of Tests Male Coronary Angiography Middle Aged Coronary Artery Disease Risk Assessment Coronary Vessels Deep Learning Vascular Calcification Adipose Tissue
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Deep Learning for Automatic Calcium Scoring in CT: Validation Using Multiple Cardiac CT and Chest CT Protocols.

Radiology Feb 11, 2020
Background Although several deep learning (DL) calcium scoring methods have achieved excellent performance for specific CT protocols, their performance in a range of CT examination types is unknown. Purpose To evaluate the performance of a DL method ...
Coronary Artery Disease Thorax Vascular Calcification Clinical Protocols Humans Retrospective Studies Tomography, X-Ray Computed Middle Aged Female Deep Learning Aged Heart Male
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Development and application of artificial intelligence in cardiac imaging.

The British journal of radiology Feb 6, 2020
In this review, we describe the technical aspects of artificial intelligence (AI) in cardiac imaging, starting with radiomics, basic algorithms of deep learning and application tasks of algorithms, until recently the availability of the public databa...
Artificial Intelligence Algorithms Databases, Factual Prognosis Deep Learning Humans Coronary Disease Vascular Calcification Computed Tomography Angiography Cardiomyopathies Coronary Stenosis Fractional Flow Reserve, Myocardial Magnetic Resonance Imaging Adipose Tissue Heart Myocardial Infarction Heart Ventricles
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Evaluation of a Deep Learning-Based Automated CT Coronary Artery Calcium Scoring Algorithm.

JACC. Cardiovascular imaging Nov 13, 2019
Computed Tomography Angiography Cardiac-Gated Imaging Techniques Diagnosis, Computer-Assisted Deep Learning Electrocardiography Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Automation Coronary Vessels Vascular Calcification Reproducibility of Results Aged Male Middle Aged Severity of Illness Index Humans Software Retrospective Studies Female
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Coronary artery calcium score quantification using a deep-learning algorithm.

Clinical radiology Nov 11, 2019
AIM: To investigate the impact of a deep-learning algorithm on the quantification of coronary artery calcium score (CACS) and the stratification of cardiac risk.
Female Aged Male Middle Aged Deep Learning Humans Retrospective Studies Tomography, X-Ray Computed Electrocardiography Feasibility Studies Coronary Disease Vascular Calcification
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Motion-corrected coronary calcium scores by a convolutional neural network: a robotic simulating study.

European radiology Oct 18, 2019
OBJECTIVE: To classify motion-induced blurred images of calcified coronary plaques so as to correct coronary calcium scores on nontriggered chest CT, using a deep convolutional neural network (CNN) trained by images of motion artifacts.
Vascular Calcification Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Artifacts Coronary Vessels Plaque, Atherosclerotic Robotics Coronary Artery Disease Motion
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Machine learning based risk prediction model for asymptomatic individuals who underwent coronary artery calcium score: Comparison with traditional risk prediction approaches.

Journal of cardiovascular computed tomography Sep 23, 2019
BACKGROUND: Machine learning (ML) is a computer algorithm used to identify patterns for prediction in various tasks, and ML methods have been beneficial for developing prediction models when applied to heterogeneous and large datasets. We aim to exam...
Humans Machine Learning Decision Support Techniques Databases, Factual Prognosis Retrospective Studies Republic of Korea Female Risk Factors Adult Asymptomatic Diseases Predictive Value of Tests Male Coronary Angiography Middle Aged Registries Risk Assessment Coronary Artery Disease Time Factors Vascular Calcification Health Status
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Influence of Coronary Calcium on Diagnostic Performance of Machine Learning CT-FFR: Results From MACHINE Registry.

JACC. Cardiovascular imaging Aug 14, 2019
OBJECTIVES: This study was conducted to investigate the influence of coronary artery calcium (CAC) score on the diagnostic performance of machine-learning-based coronary computed tomography (CT) angiography (cCTA)-derived fractional flow reserve (CT-...
Vascular Calcification Aged Asia Male Computed Tomography Angiography Severity of Illness Index Middle Aged Humans Fractional Flow Reserve, Myocardial Diagnosis, Computer-Assisted Machine Learning Predictive Value of Tests North America Europe Female Coronary Angiography Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Registries Coronary Artery Disease
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Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes.

PloS one Sep 7, 2018
Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with adverse health outcomes, such as increased mortality, large vessel disease, and reduced white matter volume, cardiovascular and cerebrovascular events. Apar...
Vascular Stiffness Fibroblast Growth Factor-23 Cardiovascular Diseases White Matter Middle Aged Vascular Calcification Fibroblast Growth Factors Humans Cohort Studies Frontal Lobe Axons Neural Networks, Computer Renal Insufficiency, Chronic Endothelium, Vascular Female Risk Factors Male Magnetic Resonance Imaging
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Machine learning in cardiac CT: Basic concepts and contemporary data.

Journal of cardiovascular computed tomography Apr 30, 2018
Propelled by the synergy of the groundbreaking advancements in the ability to analyze high-dimensional datasets and the increasing availability of imaging and clinical data, machine learning (ML) is poised to transform the practice of cardiovascular ...
Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Vascular Calcification Algorithms Prognosis Reproducibility of Results Severity of Illness Index Predictive Value of Tests Computed Tomography Angiography Humans Machine Learning
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