AIMC Topic: Computed Tomography Angiography
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AI-Quantitative CT Coronary Plaque Features Associate With a Higher Relative Risk in Women: CONFIRM2 Registry.
Circulation. Cardiovascular imaging
Mar 31, 2025
BACKGROUND: Coronary plaque features are imaging biomarkers of cardiovascular risk, but less is known about sex-specific patterns in their prognostic value. This study aimed to define sex differences in the coronary atherosclerotic phenotypes assesse...
Deep Learning and Radiomics Discrimination of Coronary Chronic Total Occlusion and Subtotal Occlusion using CTA.
Academic radiology
Mar 30, 2025
RATIONALE AND OBJECTIVES: Coronary chronic total occlusion (CTO) and subtotal occlusion (STO) pose diagnostic challenges, differing in treatment strategies. Artificial intelligence and radiomics are promising tools for accurate discrimination. This s...
Preliminary phantom study of four-dimensional computed tomographic angiography for renal artery mapping: Low-tube voltage and low-contrast volume imaging with deep learning-based reconstruction.
Radiography (London, England : 1995)
Mar 26, 2025
INTRODUCTION: A hybrid angio-CT system with 320-row detectors and deep learning-based reconstruction (DLR), provides additional imaging via 4D-CT angiography (CTA), potentially shortening procedure time and reducing DSA acquisitions, contrast media, ...
Technical implications of a novel deep learning system in the segmentation and evaluation of computed tomography angiography before transcatheter aortic valve replacement.
Therapeutic advances in cardiovascular disease
Mar 24, 2025
OBJECTIVE: The goal of this study was to compare the computed tomography angiography scans of the segmentation results from the Cvpilot, 3mensio, and Volume Viewer systems to explore the practicability of the Cvpilot system in the automatic segmentat...
Aortic Valve Stenosis
Multidetector Computed Tomography
Humans
Aortic Valve
Aged
Computed Tomography Angiography
Retrospective Studies
Predictive Value of Tests
Aged, 80 and over
Male
Transcatheter Aortic Valve Replacement
Radiographic Image Interpretation, Computer-Assisted
Female
Deep Learning
Aortography
Reproducibility of Results
A computed tomography angiography-based radiomics model for prognostic prediction of endovascular abdominal aortic repair.
International journal of cardiology
Mar 14, 2025
OBJECTIVE: This study aims to develop a radiomics machine learning (ML) model that uses preoperative computed tomography angiography (CTA) data to predict the prognosis of endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) patien...
Deep learning based automatic quantification of aortic valve calcification on contrast enhanced coronary CT angiography.
Scientific reports
Mar 12, 2025
Quantifying aortic valve calcification is critical for assessing the severity of aortic stenosis, predicting cardiovascular risk, and guiding treatment decisions. This study evaluated the feasibility of a deep learning-based automatic quantification ...
Artificial intelligence driven plaque characterization and functional assessment from CCTA using OCT-based automation: A prospective study.
International journal of cardiology
Mar 9, 2025
BACKGROUND: We aimed to develop and validate an Artificial Intelligence (AI) model that leverages CCTA and optical coherence tomography (OCT) images for automated analysis of plaque characteristics and coronary function.
Forecasting trends of rising emergency department chest imaging using machine learning.
Emergency radiology
Mar 8, 2025
INTRODUCTION: Imaging studies in the acute care setting, such as the emergency room, have been increasing. In this report, we use the Centers for Medicare and Medicaid services (CMS) database to assess trends in ED chest CT and chest CTA imaging in E...
Deep learning-driven pulmonary artery and vein segmentation reveals demography-associated vasculature anatomical differences.
Nature communications
Mar 6, 2025
Pulmonary artery-vein segmentation is critical for disease diagnosis and surgical planning. Traditional methods rely on Computed Tomography Pulmonary Angiography (CTPA), which requires contrast agents with potential health risks. Non-contrast CT, a s...
Deep Learning-Based ASPECTS Algorithm Enhances Reader Performance and Reduces Interpretation Time.
AJNR. American journal of neuroradiology
Mar 4, 2025
BACKGROUND AND PURPOSE: ASPECTS is a long-standing and well-documented selection criterion for acute ischemic stroke treatment; however, the interpretation of ASPECTS is a challenging and time-consuming task for physicians with notable interobserver ...
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