.png){kind=icon}
返回
Imaging Plaques or Imaging Fat
.png){kind=icon}
PRE
AI
DOI：10.1016/j.atherosclerosis.2026.120639.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
• CCTA enables comprehensive assessment of coronary plaque burden, composition, and high-risk features, offering more than just luminal stenosis evaluation. • Low-attenuation plaque (LAP) burden on CCTA is a strong independent predictor of myocardial infarction, with incremental prognostic value beyond calcium scoring and traditional risk factors. • Artificial intelligence (AI)-powered plaque quantification enhances reproducibility, accelerates analysis, and facilitates plaque progression/regression monitoring in large-scale studies. • Fat attenuation index (FAI) and perivascular adipose tissue (PVAT) imaging serve as non-invasive biomarkers of vascular inflammation and improve cardiovascular risk stratification. • Serial CCTA imaging demonstrates that lipid-lowering (e.g., statins, PCSK9 inhibitors, icosapent ethyl) and anti-inflammatory therapies (e.g., colchicine) lead to favorable plaque modification and stabilization. • Adipose tissue characterization (epicardial, pericoronary, thoracic, and visceral fat) is associated with systemic inflammation and cardiometabolic risk, offering a more holistic view of cardiovascular disease. • Integration of CCTA with AI and body composition analysis supports personalized prevention strategies and represents a paradigm shift in preventive cardiology.
期刊
IF:
5.7
论文数:
2.0W
被引数:
2.5W
机构
引用论文
A novel machine learning-derived radiotranscriptomic signature of perivascular fat improves cardiac risk prediction using coronary CT angiography一种新的机器学习衍生的血管周围脂肪的放射转录组学特征改善了使用冠状动脉CT血管造影的心脏风险预测.png)
EUROPEAN HEART JOURNAL
OAAI
EUROPEAN HEART JOURNALIF35.6
OAAI分享收藏Deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction: an international multicentre study深度学习辅助的冠状动脉CT血管造影在斑块和狭窄定量及心脏风险评估中的应用：一项国际多中心研究OAAI
OAAI分享收藏Identification of High-Risk Plaques Destined to Cause Acute Coronary Syndrome Using Coronary Computed Tomographic Angiography and Computational Fluid Dynamics使用冠状动脉计算机断层血管造影和计算流体动力学识别注定导致急性冠状动脉综合征的高危斑块OAAI
OAAI分享收藏
查看更多内容