Trial reportEuropean radiology2022
Identification of patients with acute myocardial infarction based on coronary CT angiography: the value of pericoronary adipose tissue radiomics.
Trial report in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it, 66 citations in OpenAlex.
- Correlation Between Fat Attenuation Index and Major Adverse Cardiovascular Events: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2026Pooled it
- Reproducibility of radiomics quality score: an intra- and inter-rater reliability study.European radiology · 2024Trial
- Diagnosis of coronary artery disease in patients with type 2 diabetes mellitus based on computed tomography and pericoronary adipose tissue radiomics: a retrospective cross-sectional study.Cardiovascular diabetology · 2023Trial
- Pericoronary fat radiomics on coronary CT angiography for predicting major adverse cardiac events: a systematic review and meta-analysis.European radiology · 2026Article
- Non-enhanced CT-based radiomics signature of epicardial adipose tissue for screening coronary heart disease.Frontiers in cardiovascular medicine · 2026Article
- Pericoronary Adipose Tissue Imaging on Coronary CT Angiography: From Fat Attenuation Index to Radiomic Risk Phenotyping.BioMed research international · 2026Review
- Predicting symptomatic carotid artery plaques with radiomics-based carotid perivascular adipose tissue characteristics: a multicenter, multiclassifier study.BMC medical imaging · 2025Article
- Development of a clinical prediction model for acute myocarditis using coronary computed tomography angiography-based radiomics.Cardiovascular diagnosis and therapy · 2025Article
- Mapping the knowledge of omics in myocardial infarction: A scientometric analysis in R Studio, VOSviewer, Citespace, and SciMAT.Medicine · 2025Article
- Differentiation of non-ST-segment elevation myocardial infarction from unstable angina using coronary computed tomography angiography: the role of imaging features and pericoronary adipose tissue radiomics.Cardiology journal · 2025Article
- Radiomics model based on coronary CT angiography for predicting major adverse cardiovascular events in patients with coronary artery disease: comparison of lesion-specific pericoronary adipose tissue model and pericoronary adipose tissue model.Frontiers in cardiovascular medicine · 2025Article
- Radiomics Feature Stability in True and Virtual Non-Contrast Reconstructions from Cardiac Photon-Counting Detector CT Datasets.Diagnostics (Basel, Switzerland) · 2024Article
- Association of Cardiovascular Risk Factors and Coronary Calcium Burden with Epicardial Adipose Tissue Volume Obtained from PET-CT Imaging in Oncological Patients.Journal of cardiovascular development and disease · 2024Article
- Ultrathin crystalline silicon-based omnidirectional strain gauges for implantable/wearable characterization of soft tissue biomechanics.Science advances · 2024Article
- A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.Tomography (Ann Arbor, Mich.) · 2024Article
- Coronary CTA-based radiomic signature of pericoronary adipose tissue predict rapid plaque progression.Insights into imaging · 2024Article
- Radiomics analysis of lesion-specific pericoronary adipose tissue to predict major adverse cardiovascular events in coronary artery disease.BMC medical imaging · 2024Article
- CT radiomic features reproducibility of virtual non-contrast series derived from photon-counting CCTA datasets using a novel calcium-preserving reconstruction algorithm compared with standard non-contrast series: focusing on epicardial adipose tissue.The international journal of cardiovascular imaging · 2024Article
- Radiomics-based discrimination of coronary chronic total occlusion and subtotal occlusion on coronary computed tomography angiography.BMC medical imaging · 2024Article
- Coronary inflammation based on pericoronary adipose tissue attenuation in type 2 diabetic mellitus: effect of diabetes management.Cardiovascular diabetology · 2024Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo determine whether radiomics analysis of pericoronary adipose tissue (PCAT) captured by coronary computed tomography angiography (CCTA) could discriminate acute myocardial infarction (MI) from unstable angina (UA).
methodsIn a single-center retrospective case-control study, patients with acute MI (n = 105) were matched to patients with UA (n = 105) and all patients were randomly divided into training and validation cohorts with a ratio of 7:3. Fat attenuation index (FAI) and PCAT radiomics features selected by Max-Relevance and Min-Redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) around the proximal three major epicardial coronary vessels (LAD [left anterior descending artery], LCx [left circumflex artery], and RCA [right coronary artery]) were used to build logistic regression models. Finally, a FAI model, three radiomics models of PCAT (LAD, LCx, and RCA), and a combined model that used the scores of these independent models were constructed. The performance of the models was evaluated by identification, calibration, and clinical application.
resultsIn training and validation cohorts, compared with the FAI model (AUC = 0.53, 0.50), the combined model achieved superior performance (AUC = 0.97, 0.95) while there was a significant difference of AUC between two models (p < 0.05). The calibration curves of the combined model demonstrated the smallest Brier score loss. Decision curve analysis suggested that the combined model provided higher clinical benefit than the FAI model.
conclusionsThe CCTA-based radiomics phenotype of PCAT outperforms the FAI model in discriminating acute MI from UA. The combination of PCAT radiomics and FAI could further enhance the performance of acute MI identification. KEY POINTS: • Fat attenuation index based on CCTA can detect inflammation-induced changes in the ratio of lipid to aqueous phase in pericoronary adipose tissue. • Fat attenuation index cannot distinguish acute MI patients from UA patients, suggesting that the two groups have the same degree of ratio of lipid to aqueous phase in pericoronary adipose tissue. • Radiomics features of PCAT have the potential to distinguish acute MI patients from UA patients.
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