ArticleJournal of cardiovascular development and disease2026
Radiomic Assessment of Epicardial Adipose Tissue for the Prediction of Non-Calcified Coronary Atherosclerotic Plaques.
Article in Journal of cardiovascular development and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Epicardial adipose tissue (EAT) has previously been associated with coronary artery calcium scores, an increased burden of coronary artery disease (CAD), and features of plaque instability. These associations are likely mediated by endocrine and paracrine signaling from bioactive molecules secreted by EAT, which may contribute to coronary atherosclerosis. EAT can be non-invasively quantified on images obtained during coronary computed tomography angiography (CCTA). This study aimed to evaluate the potential association between EAT and non-calcified coronary plaques with severe stenosis using radiomic methodology. MATERIALS AND
methodsA total of 128 consecutive patients undergoing CCTA-both with and without contrast-for known or suspected CAD were retrospectively analyzed. EAT features were extracted from contrast scans. Coronary artery plaque features were evaluated using Coronary Artery Disease-Reporting and Data System (CAD-RADS).
resultsEAT features showed a statistically significant positive correlation with non-calcified coronary plaques with severe grades of stenosis (CAD-RADS > 4). The Ensemble Machine Learning (EML) model combined with coronary plaque data showed a sensitivity of 1.00 and a specificity of 0.93, with a negative predictive value of 1.00 and a positive predictive value of 0.85, and an accuracy of 0.95 (95% CI: 0.9221-1) in internal validation.
conclusionsEAT may represent a novel imaging biomarker associated with the presence of actionable coronary plaques. Radiomic texture analysis of EAT could enhance the non-invasive prediction of coronary stenoses. These preliminary findings support the clinical utility of EAT evaluation via CCTA in patients with low to intermediate cardiovascular risk.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.