AIMC Topic: Computed Tomography Angiography

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Epicardial adipose tissue, myocardial remodelling and adverse outcomes in asymptomatic aortic stenosis: a post hoc analysis of a randomised controlled trial.

Heart (British Cardiac Society) Jun 26, 2025
BACKGROUND: Epicardial adipose tissue represents a metabolically active visceral fat depot that is in direct contact with the left ventricular myocardium. While it is associated with coronary artery disease, little is known regarding its role in aort...
Humans Prospective Studies Female Aged Male Asymptomatic Diseases Computed Tomography Angiography Pericardium Severity of Illness Index Epicardial Adipose Tissue Ventricular Function, Left Aortic Valve Stenosis Echocardiography Adipose Tissue Middle Aged Ventricular Remodeling Disease Progression
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The Current State of Artificial Intelligence on Detecting Pulmonary Embolism via Computerised Tomography Pulmonary Angiogram: A Systematic Review.

British journal of hospital medicine (London, England : 2005) Jun 5, 2025
Pulmonary embolism (PE) is a life-threatening condition with significant diagnostic challenges due to high rates of missed or delayed detection. Computed tomography pulmonary angiography (CTPA) is the current standard for diagnosing PE, however, dem...
Humans Artificial Intelligence Reproducibility of Results Pulmonary Embolism Computed Tomography Angiography
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Research on ischemic stroke risk assessment based on CTA radiomics and machine learning.

BMC medical imaging Jun 5, 2025
BACKGROUND: The study explores the value of a model constructed by integrating CTA-based carotid plaque radiomic features, clinical risk factors, and plaque imaging characteristics for prognosticating the risk of ischemic stroke.
Humans Machine Learning Prognosis Female Risk Factors Aged Carotid Artery Diseases ROC Curve Logistic Models Ischemic Stroke Radiomics Plaque, Atherosclerotic Male Computed Tomography Angiography Middle Aged Risk Assessment
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Two birds with one stone: pre-TAVI coronary CT angiography combined with FFR helps screen for coronary stenosis.

BMC medical imaging May 26, 2025
OBJECTIVES: Since coronary artery disease (CAD) is a common comorbidity in patients with aortic valve stenosis, invasive coronary angiography (ICA) can be avoided if significant CAD can be screened with the non-invasive coronary CT angiography (cCTA)...
Computed Tomography Angiography Coronary Stenosis Aortic Valve Stenosis Fractional Flow Reserve, Myocardial Predictive Value of Tests Transcatheter Aortic Valve Replacement Humans Female Coronary Angiography Machine Learning Coronary Artery Disease Aged Retrospective Studies Aged, 80 and over Sensitivity and Specificity Male
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Improving lower-extremity artery depiction and diagnostic confidence using dual-energy technique and popliteal artery monitoring in dual-low dose CT angiography.

Scientific reports May 9, 2025
To assess the utility of dual-energy CT scanning (DECTs) with popliteal artery (PA) monitoring in dual low-dose (radiation and contrast) lower-extremity CT angiography (LE-CTA). 135 patients undergoing LE-CTA were prospectively included and divided i...
Contrast Media Lower Extremity Aged, 80 and over Humans Peripheral Arterial Disease Signal-To-Noise Ratio Adult Prospective Studies Radiation Dosage Male Computed Tomography Angiography Female Middle Aged Popliteal Artery Aged
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Application of deep learning reconstruction combined with time-resolved post-processing method to improve image quality in CTA derived from low-dose cerebral CT perfusion data.

BMC medical imaging Apr 29, 2025
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...
Middle Aged Deep Learning Image Processing, Computer-Assisted Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Female Aged Adult Male Humans Signal-To-Noise Ratio Retrospective Studies Computed Tomography Angiography
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Application and optimization of the U-Net++ model for cerebral artery segmentation based on computed tomographic angiography images.

European journal of radiology Apr 27, 2025
Accurate segmentation of cerebral arteries on computed tomography angiography (CTA) images is essential for the diagnosis and management of cerebrovascular diseases, including ischemic stroke. This study implemented a deep learning-based U-Net++ mode...
Computed Tomography Angiography Cerebral Angiography Cerebral Arteries Humans Reproducibility of Results Deep Learning Radiographic Image Interpretation, Computer-Assisted Cerebrovascular Disorders
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Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging Apr 26, 2025
Non-contrast enhanced magnetic resonance coronary angiography (MRCA) is a promising coronary heart disease screening modality. However, its clinical application is hindered by inherent limitations, including low spatial resolution and insufficient co...
Automation Coronary Vessels Magnetic Resonance Angiography Computed Tomography Angiography Coronary Angiography Coronary Artery Disease Image Interpretation, Computer-Assisted Observer Variation Humans Female Reproducibility of Results Aged Male Middle Aged Deep Learning Time Factors Predictive Value of Tests
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Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart Apr 24, 2025
BACKGROUND: Exclusion of coronary stenosis in individuals with suggestive symptoms is challenging. Cardiac CT or coronary angiography is often used but is inefficient and costly and involves risks. Sex-stratified algorithms based on electronic health...
Coronary Vessels Computed Tomography Angiography Coronary Stenosis Coronary Angiography Coronary Artery Disease Netherlands Aged Sex Factors Male Humans Middle Aged Machine Learning Predictive Value of Tests Algorithms Retrospective Studies Electronic Health Records Female Reproducibility of Results
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Impact of CT reconstruction algorithms on pericoronary and epicardial adipose tissue attenuation.

European journal of radiology Apr 23, 2025
OBJECTIVE: This study aims to investigate the impact of adaptive statistical iterative reconstruction-Veo (ASIR-V) and deep learning image reconstruction (DLIR) algorithms on the quantification of pericoronary adipose tissue (PCAT) and epicardial adi...
Algorithms Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Pericardium Epicardial Adipose Tissue Male Middle Aged Deep Learning Adipose Tissue
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