BACKGROUND: The integration of artificial intelligence (AI) into medical diagnostics has significantly impacted cardiology by enhancing diagnostic precision and therapeutic strategies. Coronary artery disease continues to be a leading cause of global...
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.
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...
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...
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)...
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...
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...
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...
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...
The international journal of cardiovascular imaging
Apr 22, 2025
In symptomatic patients undergoing coronary CTA for suspected coronary artery disease (CAD), we assessed if quantification of plaque burden, in addition to luminal narrowing and clinical risk factors, offers incremental value for the identification o...
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