Trial reportEuropean radiology2022
Prediction of acute coronary syndrome within 3 years using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography.
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 47 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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
47 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.
- CT and MRI radiomics in cardiovascular risk prediction: a systematic review and meta-analysis by the EuSoMII Radiomics Auditing Group.European radiology · 2026Pooled it
- Pericoronary fat radiomics on coronary CT angiography for predicting major adverse cardiac events: a systematic review and meta-analysis.European radiology · 2026Article
- Explainable ML for ACS culprit plaques: a multidimensional CCTA model highlighting hemodynamic increment.The international journal of cardiovascular imaging · 2026Article
- A fine-grained transformer combined with multimodal data for predicting hospital length of stay in acute coronary syndrome.Scientific reports · 2026Article
- Patient-level CAD-RADS scoring from coronary radiomic features.Scientific reports · 2026Article
- Identification of histological carotid plaque vulnerability by CT angiography using perivascular adipose tissue radiomics signature.Insights into imaging · 2026Article
- Incremental value of the perivascular fat attenuation index surrounding the superior mesenteric artery on non-contrast CT for predicting SMA abnormalities in patients with acute abdominal pain.Frontiers in medicine · 2026Article
- Pericoronary Adipose Tissue Imaging on Coronary CT Angiography: From Fat Attenuation Index to Radiomic Risk Phenotyping.BioMed research international · 2026Review
- Non-enhanced CT-based radiomics signature of epicardial adipose tissue for screening coronary heart disease.Frontiers in cardiovascular medicine · 2026Article
- Predicting major adverse cardiovascular events in diabetic and non-diabetic patients with coronary artery disease: visual models integrating multi-parametric coronary computed tomography angiography and pericoronary adipose tissue radiomics.Frontiers in cardiovascular medicine · 2026Article
- A CCTA coronary plaque radiomic model for predicting major adverse cardiovascular events in patients with coronary artery disease.Frontiers in cardiovascular medicine · 2026Article
- Improving Risk Stratification for Transient Ischaemic Attacks and Ischaemic Stroke in Patients with Coronary Artery Disease: A Combined Radiomics Analysis of Multimodal Adipose Tissue.Diagnostics (Basel, Switzerland) · 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 to improve risk stratification for patients with acute coronary syndrome: a multicenter retrospective cohort study.Cardiovascular diabetology · 2025Article
- Predicting symptomatic carotid artery plaques with radiomics-based carotid perivascular adipose tissue characteristics: a multicenter, multiclassifier study.BMC medical imaging · 2025Article
- MRI ensemble model of plaque and perivascular adipose tissue as PET-equivalent for identifying carotid atherosclerotic inflammation.EJNMMI research · 2025Article
- Multimodal prediction of major adverse cardiovascular events in hypertensive patients with coronary artery disease: integrating pericoronary fat radiomics, CT-FFR, and clinicoradiological features.La Radiologia medica · 2025Article
- Cardiac CT Perfusion Imaging of Pericoronary Adipose Tissue (PCAT) Highlighting Potential Confounds in CTA Analysis.Journal of clinical medicine · 2025Article
- Pericoronary adipose tissue feature analysis in computed tomography calcium score images in comparison to coronary computed tomography angiography.Journal of medical imaging (Bellingham, Wash.) · 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
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesTo evaluate whether radiomics signature of pericoronary adipose tissue (PCAT) based on coronary computed tomography angiography (CCTA) could improve the prediction of future acute coronary syndrome (ACS) within 3 years.
methodsWe designed a retrospective case-control study that patients with ACS (n = 90) were well matched to patients with no cardiac events (n = 1496) during 3 years follow-up, then which were randomly divided into training and test datasets with a ratio of 3:1. A total of 107 radiomics features were extracted from PCAT surrounding lesions and 14 conventional plaque characteristics were analyzed. Radiomics score, plaque score, and integrated score were respectively calculated via a linear combination of the selected features, and their performance was evaluated with discrimination, calibration, and clinical application.
resultsRadiomics score achieved superior performance in identifying patients with future ACS within 3 years in both training and test datasets (AUC = 0.826, 0.811) compared with plaque score (AUC = 0.699, 0.640), with a significant difference of AUC between two scores in the training dataset (p = 0.009); while the improvement of integrated score discriminating capability (AUC = 0.838, 0.826) was non-significant. The calibration curves of three predictive models demonstrated a good fitness respectively (all p > 0.05). Decision curve analysis suggested that integrated score added more clinical benefit than plaque score. Stratified analysis revealed that the performance of three predictive models was not affected by tube voltage, CT version, different sites of hospital.
conclusionCCTA-based radiomics signature of PCAT could have the potential to predict the occurrence of subsequent ACS. Radiomics-based integrated score significantly outperformed plaque score in identifying future ACS within 3 years. KEY POINTS: • Plaque score based on conventional plaque characteristics had certain limitations in the prediction of ACS. • Radiomics signature of PCAT surrounding plaques could have the potential to improve the predictive ability of subsequent ACS. • Radiomics-based integrated score significantly outperformed plaque score in the identification of future ACS within 3 years.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.