AIMC Topic: Plaque, Atherosclerotic

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Plaque components segmentation in carotid artery on simultaneous non-contrast angiography and intraplaque hemorrhage imaging using machine learning.

Magnetic resonance imaging Apr 5, 2019
PURPOSE: This study sought to determine the feasibility of using Simultaneous Non-contrast Angiography and intraPlaque Hemorrhage (SNAP) to detect the lipid-rich/necrotic core (LRNC), and develop a machine learning based algorithm to segment plaque c...
Sensitivity and Specificity Male Middle Aged Contrast Media Calcinosis Plaque, Atherosclerotic Algorithms Angiography Female Necrosis Reproducibility of Results Carotid Stenosis Aged Plaque, Amyloid Humans Lipids Machine Learning Cerebral Hemorrhage Bayes Theorem Carotid Arteries Carotid Artery, Common
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The best predictor of ischemic coronary stenosis: subtended myocardial volume, machine learning-based FFR, or high-risk plaque features?

European radiology Mar 22, 2019
OBJECTIVES: The present study aimed to compare the diagnostic performance of a machine learning (ML)-based FFR algorithm, quantified subtended myocardial volume, and high-risk plaque features for predicting if a coronary stenosis is hemodynamically s...
Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Female Coronary Stenosis Fractional Flow Reserve, Myocardial Male Middle Aged Coronary Angiography Myocardial Ischemia Plaque, Atherosclerotic
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Machine Learning Using CT-FFR Predicts Proximal Atherosclerotic Plaque Formation Associated With LAD Myocardial Bridging.

JACC. Cardiovascular imaging Mar 13, 2019
Humans Machine Learning Prognosis Coronary Artery Disease Image Interpretation, Computer-Assisted Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography Fractional Flow Reserve, Myocardial Myocardial Bridging Male Retrospective Studies Middle Aged Female Time Factors Risk Factors Predictive Value of Tests Aged Coronary Angiography
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Rheumatoid Arthritis: Atherosclerosis Imaging and Cardiovascular Risk Assessment Using Machine and Deep Learning-Based Tissue Characterization.

Current atherosclerosis reports Jan 25, 2019
PURPOSE OF THE REVIEW: Rheumatoid arthritis (RA) is a chronic, autoimmune disease which may result in a higher risk of cardiovascular (CV) events and stroke. Tissue characterization and risk stratification of patients with rheumatoid arthritis are a ...
Atherosclerosis Carotid Arteries Plaque, Atherosclerotic Carotid Artery Diseases Humans Risk Factors Risk Assessment Deep Learning Ultrasonography Arthritis, Rheumatoid Inflammation Tomography, Optical Coherence
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Decreased circulating catestatin levels are associated with coronary artery disease: The emerging anti-inflammatory role.

Atherosclerosis Dec 24, 2018
BACKGROUND AND AIMS: The neuropeptide catestatin (CST) is an endogenous nicotinic cholinergic antagonist that acts as pleiotropic cardiac protective hormone. This study investigated the association between CST and coronary artery disease (CAD) and th...
Disease Models, Animal Chromogranin A Mice, Knockout, ApoE Coronary Artery Disease Human Umbilical Vein Endothelial Cells Humans Peptidyl-Dipeptidase A Female Peptide Fragments Atherosclerosis Cells, Cultured Plaque, Atherosclerotic Animals Down-Regulation Anti-Inflammatory Agents Cytokines Male Biomarkers Cell Adhesion Molecules Severity of Illness Index Angiotensin-Converting Enzyme 2 Case-Control Studies
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Coronary CT angiography-derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia.

European radiology Dec 6, 2018
OBJECTIVES: We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)-derived plaque markers combined with deep machine learning-based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FF...
Fractional Flow Reserve, Myocardial ROC Curve Coronary Angiography Plaque, Atherosclerotic Computed Tomography Angiography Coronary Stenosis Female Male Middle Aged Diagnosis, Computer-Assisted Humans Machine Learning Retrospective Studies
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A Recurrent CNN for Automatic Detection and Classification of Coronary Artery Plaque and Stenosis in Coronary CT Angiography.

IEEE transactions on medical imaging Nov 28, 2018
Various types of atherosclerotic plaque and varying grades of stenosis could lead to different management of patients with a coronary artery disease. Therefore, it is crucial to detect and classify the type of coronary artery plaque, as well as to de...
Algorithms Image Processing, Computer-Assisted Humans Coronary Angiography Neural Networks, Computer Computed Tomography Angiography Coronary Vessels Coronary Stenosis Plaque, Atherosclerotic
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Iterative quality enhancement via residual-artifact learning networks for low-dose CT.

Physics in medicine and biology Oct 23, 2018
Radiation exposure and the associated risk of cancer for patients in computed tomography (CT) scans have been major clinical concerns. The radiation exposure can be reduced effectively via lowering the x-ray tube current (mA). However, this strategy ...
Humans Neural Networks, Computer Machine Learning Algorithms Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Plaque, Atherosclerotic Artifacts Radionuclide Imaging Brain Diseases Radiation Exposure Radiation Dosage
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Machine-learning integration of CT histogram analysis to evaluate the composition of atherosclerotic plaques: Validation with IB-IVUS.

Journal of cardiovascular computed tomography Oct 21, 2018
BACKGROUND: To determine whether machine learning with histogram analysis of coronary CT angiography (CCTA) yields higher diagnostic performance for coronary plaque characterization than the conventional cut-off method using the median CT number.
Coronary Vessels Multidetector Computed Tomography Plaque, Atherosclerotic Computed Tomography Angiography Predictive Value of Tests Coronary Angiography Ultrasonography, Interventional Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Female Reproducibility of Results Aged Male Humans Machine Learning Retrospective Studies
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Calcium detection, its quantification, and grayscale morphology-based risk stratification using machine learning in multimodality big data coronary and carotid scans: A review.

Computers in biology and medicine Aug 20, 2018
PURPOSE OF REVIEW: Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and ...
Humans Machine Learning Risk Assessment Big Data Multimodal Imaging Plaque, Atherosclerotic Carotid Artery Diseases Ultrasonography, Interventional Calcium Image Interpretation, Computer-Assisted Carotid Arteries
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