AIMC Topic: Plaque, Atherosclerotic

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Deep learning-based fully automatic screening of carotid artery plaques in computed tomography angiography: a multicenter study.

Clinical radiology May 6, 2024
AIM: To develop and validate a deep learning (DL) algorithm for the automated detection and classification of carotid artery plaques (CAPs) on computed tomography angiography (CTA) images.
Male Middle Aged Deep Learning Radiographic Image Interpretation, Computer-Assisted Carotid Arteries Retrospective Studies Female Aged Sensitivity and Specificity Humans Plaque, Atherosclerotic Computed Tomography Angiography Carotid Stenosis Carotid Artery Diseases
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Radiomics and artificial intelligence: General notions and applications in the carotid vulnerable plaque.

European journal of radiology May 6, 2024
Carotid atherosclerosis plays a substantial role in cardiovascular morbidity and mortality. Given the multifaceted impact of this disease, there has been increasing interest in harnessing artificial intelligence (AI) and radiomics as complementary to...
Humans Artificial Intelligence Radiomics Image Interpretation, Computer-Assisted Plaque, Atherosclerotic Carotid Artery Diseases
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Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.

The international journal of cardiovascular imaging Apr 28, 2024
The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascu...
Carotid Arteries Plaque, Atherosclerotic Carotid Artery Diseases Risk Assessment Female Deep Learning Humans Time Factors Risk Factors Canada Aged Decision Support Techniques Coronary Angiography Predictive Value of Tests Male Prognosis Coronary Artery Disease Middle Aged Heart Disease Risk Factors Image Interpretation, Computer-Assisted Carotid Intima-Media Thickness
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A deep learning-based calculation system for plaque stenosis severity on common carotid artery of ultrasound images.

Vascular Apr 24, 2024
ObjectivesAssessment of plaque stenosis severity allows better management of carotid source of stroke. Our objective is to create a deep learning (DL) model to segment carotid intima-media thickness and plaque and further automatically calculate plaq...
Carotid Stenosis Severity of Illness Index Deep Learning Ultrasonography Predictive Value of Tests Image Interpretation, Computer-Assisted Observer Variation Carotid Intima-Media Thickness Carotid Artery, Common Plaque, Atherosclerotic Female Reproducibility of Results Aged Male Middle Aged Humans
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Integrating machine learning algorithms and single-cell analysis to identify gut microbiota-related macrophage biomarkers in atherosclerotic plaques.

Frontiers in cellular and infection microbiology Apr 23, 2024
OBJECTIVE: The relationship between macrophages and the gut microbiota in patients with atherosclerosis remains poorly defined, and effective biological markers are lacking. This study aims to elucidate the interplay between gut microbial communities...
Antigens, CD Biomarkers Atherosclerosis Antigens, Differentiation, Myelomonocytic Gene Expression Profiling Plaque, Atherosclerotic Humans Agammaglobulinaemia Tyrosine Kinase Interferon Regulatory Factors Single-Cell Analysis Machine Learning Receptors, CCR1 Gene Regulatory Networks CD68 Molecule Algorithms Gastrointestinal Microbiome Macrophages
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A comparative analysis of deep learning-based location-adaptive threshold method software against other commercially available software.

The international journal of cardiovascular imaging Apr 18, 2024
Automatic segmentation of the coronary artery using coronary computed tomography angiography (CCTA) images can facilitate several analyses related to coronary artery disease (CAD). Accurate segmentation of the lumen or plaque region is one of the mos...
Female Reproducibility of Results Aged Male Middle Aged Humans Software Retrospective Studies Coronary Artery Disease Coronary Vessels Plaque, Atherosclerotic Computed Tomography Angiography Deep Learning Predictive Value of Tests Coronary Angiography Ultrasonography, Interventional Radiographic Image Interpretation, Computer-Assisted
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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...
Humans Radiographic Image Interpretation, Computer-Assisted Male Plaque, Atherosclerotic Coronary Artery Disease Artificial Intelligence Middle Aged Observer Variation Vascular Calcification Female Severity of Illness Index Coronary Vessels Computed Tomography Angiography Reproducibility of Results Predictive Value of Tests Multidetector Computed Tomography Coronary Stenosis Aged Coronary Angiography
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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
Male Middle Aged Severity of Illness Index Deep Learning Predictive Value of Tests Plaque, Atherosclerotic Coronary Angiography Humans Retrospective Studies Computed Tomography Angiography Radiographic Image Interpretation, Computer-Assisted Female Coronary Stenosis Coronary Artery Disease Reproducibility of Results Automation Aged Coronary Vessels
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Cross-sectional angle prediction of lipid-rich and calcified tissue on computed tomography angiography images.

International journal of computer assisted radiology and surgery Mar 13, 2024
PURPOSE: The assessment of vulnerable plaque characteristics and distribution is important to stratify cardiovascular risk in a patient. Computed tomography angiography (CTA) offers a promising alternative to invasive imaging but is limited by the fa...
Vascular Calcification Computed Tomography Angiography Deep Learning Lipids Coronary Artery Disease Plaque, Atherosclerotic Humans Male
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Reproducibility of artificial intelligence-enabled plaque measurements between systolic and diastolic phases from coronary computed tomography angiography.

European radiology Mar 11, 2024
OBJECTIVES: Current coronary CT angiography (CTA) guidelines suggest both end-systolic and mid-diastolic phases of the cardiac cycle can be used for CTA image acquisition. However, whether differences in the phase of the cardiac cycle influence coron...
Reproducibility of Results Aged Male Middle Aged Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Systole Plaque, Atherosclerotic Computed Tomography Angiography Humans Artificial Intelligence Female Diastole
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