Journal of cardiovascular computed tomography
Apr 24, 2024
INTRODUCTION: Coronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™...
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...
RATIONALE AND OBJECTIVES: To assess the impact of deep learning-based imaging reconstruction (DLIR) on quantitative results of coronary artery calcium scoring (CACS) and to evaluate the potential of DLIR for radiation dose reduction in CACS.
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...
OBJECTIVES: Utilising readily available clinical variables, we aimed to develop and validate a novel machine learning (ML) model to predict severe coronary calcification, and further assessed its prognostic significance.
OBJECTIVE: This study used random forest model to explore the feasibility of radial artery calcification in prediction of coronary artery calcification in hemodialysis patients.
BACKGROUND: Abdominal aortic aneurysm (AAA) rupture prediction based on sex and diameter could be improved. The goal was to assess whether aortic calcification distribution could better predict AAA rupture through machine learning and LASSO regressio...
OBJECTIVE: This study aimed to determine the feasibility and limitations of deep learning-based coronary calcium scoring using positron emission tomography-computed tomography (PET-CT) in comparison with coronary calcium scoring using ECG-gated non-c...
OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcifications (ECACs) in cone beam computed tomography scans.
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