AIMC Topic: Computed Tomography Angiography

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Derivation and validation of an artificial intelligence-based plaque burden safety cut-off for long-term acute coronary syndrome from coronary computed tomography angiography.

European heart journal. Cardiovascular Imaging
AIMS: Artificial intelligence (AI) has enabled accurate and fast plaque quantification from coronary computed tomography angiography (CCTA). However, AI detects any coronary plaque in up to 97% of patients. To avoid overdiagnosis, a plaque burden saf...

Hybrid strategy of coronary atherosclerosis characterization with T1-weighted MRI and CT angiography to non-invasively predict periprocedural myocardial injury.

European heart journal. Cardiovascular Imaging
AIMS: Coronary computed tomography angiography (CCTA) and magnetic resonance imaging (MRI) can predict periprocedural myocardial injury (PMI) after percutaneous coronary intervention (PCI). We aimed to investigate whether integrating MRI with CCTA, u...

Cost-effectiveness of a novel AI technology to quantify coronary inflammation and cardiovascular risk in patients undergoing routine coronary computed tomography angiography.

European heart journal. Quality of care & clinical outcomes
AIMS: Coronary computed tomography angiography (CCTA) is a first-line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We as...

Two-stage convolutional neural network for segmentation and detection of carotid web on CT angiography.

Journal of neurointerventional surgery
BACKGROUND: Carotid web (CaW) is a risk factor for ischemic stroke, mainly in young patients with stroke of undetermined etiology. Its detection is challenging, especially among non-experienced physicians.

The Machine Learning Models in Major Cardiovascular Adverse Events Prediction Based on Coronary Computed Tomography Angiography: Systematic Review.

Journal of medical Internet research
BACKGROUND: Coronary computed tomography angiography (CCTA) has emerged as the first-line noninvasive imaging test for patients at high risk of coronary artery disease (CAD). When combined with machine learning (ML), it provides more valid evidence i...

Fully automated image quality assessment based on deep learning for carotid computed tomography angiography: A multicenter study.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
PURPOSE: To develop and evaluate the performance of fully automated model based on deep learning and multiple logistics regression algorithm for image quality assessment (IQA) of carotid computed tomography angiography (CTA) images.

GVM-Net: A GNN-Based Vessel Matching Network for 2D/3D Non-Rigid Coronary Artery Registration.

IEEE transactions on medical imaging
The registration of coronary artery structures from preoperative coronary computed tomography angiography to intraoperative coronary angiography is of great interest to improve guidance in percutaneous coronary interventions. However, non-rigid defor...

CCTA-Derived coronary plaque burden offers enhanced prognostic value over CAC scoring in suspected CAD patients.

European heart journal. Cardiovascular Imaging
AIMS: To assess the prognostic utility of coronary artery calcium (CAC) scoring and coronary computed tomography angiography (CCTA)-derived quantitative plaque metrics for predicting adverse cardiovascular outcomes.

Deep learning radiomics of left atrial appendage features for predicting atrial fibrillation recurrence.

BMC medical imaging
BACKGROUND: Structural remodeling of the left atrial appendage (LAA) is characteristic of atrial fibrillation (AF), and LAA morphology impacts radiofrequency catheter ablation (RFCA) outcomes. In this study, we aimed to develop and validate a predict...