AIMC Topic: Coronary Angiography

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Prediction of Percutaneous Coronary Intervention Success in Patients With Moderate to Severe Coronary Artery Calcification Using Machine Learning Based on Coronary Angiography: Prospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Given the challenges faced during percutaneous coronary intervention (PCI) for heavily calcified lesions, accurately predicting PCI success is crucial for enhancing patient outcomes and optimizing procedural strategies.

Knowledge, attitudes, and practices of cardiovascular health care personnel regarding coronary CTA and AI-assisted diagnosis: a cross-sectional study.

Journal of global health
BACKGROUND: Artificial intelligence (AI) holds significant promise for medical applications, particularly in coronary computed tomography angiography (CTA). We assessed the knowledge, attitudes, and practices (KAP) of cardiovascular health care perso...

Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients.

Cardiovascular diabetology
BACKGROUND: Coronary Heart Disease (CHD) and Non-Alcoholic Fatty Liver Disease (NAFLD) share overlapping pathogenic mechanisms including adipose tissue dysfunction, insulin resistance, and systemic inflammation mediated by adipokines. However, the sp...

Two birds with one stone: pre-TAVI coronary CT angiography combined with FFR helps screen for coronary stenosis.

BMC medical imaging
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)...

Deep learning-based classification of coronary arteries and left ventricle using multimodal data for autonomous protocol selection or adjustment in angiography.

Scientific reports
Optimal selection of X-ray imaging parameters is crucial in coronary angiography and structural cardiac procedures to ensure optimal image quality and minimize radiation exposure. These anatomydependent parameters are organized into customizable orga...

Fast and automatic coronary artery segmentation using nnU-Net for non-contrast enhanced magnetic resonance coronary angiography.

The international journal of cardiovascular imaging
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...

Optimising coronary imaging decisions with machine learning: an external validation study.

Open heart
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...

Impact of CT reconstruction algorithms on pericoronary and epicardial adipose tissue attenuation.

European journal of radiology
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...