ArticleFrontiers in cardiovascular medicine2024
Predicting major adverse cardiovascular events in angina patients using radiomic features of pericoronary adipose tissue based on CCTA.
Article in Frontiers in cardiovascular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- CT and MRI radiomics in cardiovascular risk prediction: a systematic review and meta-analysis by the EuSoMII Radiomics Auditing Group.European radiology · 2026Pooled it
- Correlation Between Fat Attenuation Index and Major Adverse Cardiovascular Events: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2026Pooled it
- Pericoronary fat radiomics on coronary CT angiography for predicting major adverse cardiac events: a systematic review and meta-analysis.European radiology · 2026Article
- Role of artificial intelligence in developing predictive models for major adverse cardiovascular outcomes using CCTA adipose tissue characteristics: a systematic review and meta-analysis.European heart journal. Digital health · 2026Review
- Pericoronary adipose tissue radiomics enhances prediction of major adverse cardiovascular events beyond CCTA-derived functional parameters in coronary atherosclerosis.Frontiers in cardiovascular medicine · 2026Article
- Pericoronary Adipose Tissue Radiomics-Based Prediction Models for Cardiovascular Events: A Systematic Review of Predictive Performance, Validation, and Incremental Value.International journal of general medicine · 2026Review
- Multimodal Cardiovascular Risk Discrimination: Clinical, Biochemical, and Doppler Ultrasound Insights from a Contemporary Atherosclerotic Cardiovascular Disease Cohort.Anatolian journal of cardiology · 2025Article
- A Narrative Review of Multimodal Data Fusion Strategies for Precision Risk Prediction in Coronary Artery Disease: Advances, Challenges, and Future Informatics Directions.Rambam Maimonides medical journal · 2025Review
- Pericoronary adipose tissue: potential for pathological diagnosis and therapeutic applications.Cardiovascular intervention and therapeutics · 2025Review
- Roles of perivascular adipose tissue in the pathogenesis of atherosclerosis - an update on recent findings.Frontiers in physiology · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This study aims to evaluate whether radiomic features of pericoronary adipose tissue (PCAT) derived from coronary computed tomography angiography (CCTA) can better predict major adverse cardiovascular events (MACE) in patients with angina pectoris. Methods: A single-center retrospective study included 239 patients with angina pectoris who underwent coronary CT examinations. Participants were divided into MACE ( Results: The radiomics model demonstrated superior performance in predicting MACE in patients with angina pectoris within both the training and validation cohorts, yielding areas under the curve (AUC) of 0.83 and 0.71, respectively, which significantly outperformed the FAI model (AUC = 0.71, 0.54) and the clinical model (AUC = 0.81, 0.67), with statistically significant differences in AUC ( Conclusion: The CCTA-based PCAT radiomics model is an effective tool for predicting MACE in patients with angina pectoris, assisting clinicians in optimizing risk stratification for individual patients. The CCTA-based radiomics model significantly surpasses traditional FAI and clinical models in predicting major adverse cardiovascular events in patients with angina pectoris.
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