ArticleCardiovascular diabetology2025
Pericoronary adipose tissue radiomics to improve risk stratification for patients with acute coronary syndrome: a multicenter retrospective cohort study.
Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Prediction of coronary atherosclerosis progression in type 2 diabetes mellitus based on AI-derived CCTA parameters and clinical factors: a follow-up study.Acta diabetologica · 2026Article
- Explainable ML for ACS culprit plaques: a multidimensional CCTA model highlighting hemodynamic increment.The international journal of cardiovascular imaging · 2026Article
- Analysis of epicardial adipose tissue in relation to arterial hypertension using radiomics in photon-counting CT.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
- Pericoronary adipose tissue radiomics enhances prediction of major adverse cardiovascular events beyond CCTA-derived functional parameters in coronary atherosclerosis.Frontiers in cardiovascular medicine · 2026Article
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Abstract
backgroundPericoronary adipose tissue (PCAT) radiomics derived from coronary computed tomography angiography (CCTA) for predicting major adverse cardiovascular events (MACE) in patients with acute coronary syndrome (ACS) remains unclear. This study aimed to assess whether PCAT radiomics could further provide complementary predictive value for the risk of MACE during long-term follow-up.
methodsA multicenter retrospective study enrolled 777 subjects who underwent pre-intervention CCTA at 3 medical centers. Patients from one institution (n = 664) formed an internal cohort and were randomly split into training and internal test sets (7:3). Multivariable Cox regression models were developed using clinical scores, traditional CCTA, PCAT attenuation (PCATa) and PCAT radiomics, and were tested using the internal test set. Data from two additional institutions (n = 113) were reserved as an external test set to evaluate the applicability and generalizability of models.
resultsA total of 777 participants (61.0 ± 9.70 years; 506 males) were analyzed. During a median follow-up of 5.45 years (interquartile range: 4.03, 7.12 years), 177 (22.78%) cases experienced a MACE. Adding culprit PCATa or three vessels-based PCATa did not improve predictive ability for the model containing clinical scores and traditional CCTA, whereas further addition of PCAT
conclusionsPCAT radiomics can enhance long-term prediction of MACE in ACS patients beyond current clinical scores, traditional CCTA and PCATa. Addition of PCAT radiomics to a conventional risk assessment improves the identification of high-risk individuals with MACE.
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