Early Prediction of Heart Failure From Routine Cardiac CT Using Radiomic Phenotyping of Epicardial Fat.

doi:10.1016/j.jacc.2026.02.5116

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Community

Back to search

Article

Early Prediction of Heart Failure From Routine Cardiac CT Using Radiomic Phenotyping of Epicardial Fat.

Journal of the American College of Cardiology - 30 Jun 2026

Oikonomou Evangelos K, Chan Kenneth, Patel Parijat, Wahome Elizabeth, Dangas Katerina, Desai Rohan, Sobirov Ikboljon, Khera Rohan, Petersen Steffen E, Pugliese Francesca, Rajani Ronak, Nicol Edward, Kardos Attila, Adlam David, Kelion Andrew D, Sabharwal Nikant, Screaton Nicholas, Greenwood John P, Rodrigues Jonathan, Huck Daniel, Shirodaria Cheerag, Tomlins Pete, Siddique Muhammad, Sohan Yogesh, Fry Sam, van Assen Marly, Blankstein Ron, Desai Milind Y, Neubauer Stefan, Channon Keith M, Deanfield John, Antoniades Charalambos

Abstract excerpt

BACKGROUND: Epicardial adipose tissue (EAT) is a metabolically active visceral fat depot that is both a sensor and a modulator of myocardial biology and changes its composition in response to paracrine signals from the myocardium. We hypothesized that radiomic characterization of EAT from routine coronary computed tomographic angiography (CCTA) can noninvasively capture this adverse remodeling and enable early...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cohort Studies

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Computed Tomography Angiography

Share to Coronary Angiography

Share to Heart Failure

Share to Predictive Value of Tests

Share to Radiomics

Share to Risk Assessment

Share to Tomography, X-Ray Computed

Source

Open in PubMed Open full text

Identifiers

PMID: 41949519
DOI: 10.1016/j.jacc.2026.02.5116
PMCID: PMC13289806

Genes

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Early Prediction of Heart Failure From Routine Cardiac CT Using Radiomic Phenotyping of Epicardial Fat.PMID 41949519Read ↗

AI-Enabled Echocardiography Identifies an Adverse Epicardial Adiposity Phenotype Associated with Cardiometabolic DysfunctionSemantic proximity Read ↗

The Cardiovascular Impact and Genetics of Pericardial AdipositySemantic proximity Read ↗

Spatial phenotyping of epicardial adipose tissue from cardiac MRI.Semantic proximity Read ↗

Epicardial adipose tissue as a determinant of heart failure prognosis: insights across ejection fraction phenotypes.Semantic proximity Read ↗

Epicardial Adipose Tissue in Myocardial Disease: From Physiology to Heart Failure Phenotypes.Semantic proximity Read ↗

Discovery of cardiac imaging biomarkers by training neural network models across diagnostic modalitiesSemantic proximity Read ↗

Incremental Prognostic Value of Pericardial Adipose Tissue Radiomic Phenotype Based on Cardiac MRI in Patients With End-Stage Renal Disease.Semantic proximity Read ↗

CARDIAC-FM: A Multimodal Foundation Model for Cardiovascular Risk Prediction Using ECG and Cardiac MRISemantic proximity Read ↗

Multimodal AI for Precision Preventive CardiologySemantic proximity Read ↗

Myocardial Infarction Associates With a Distinct Pericoronary Adipose Tissue Radiomic Phenotype: A Prospective Case-Control Study.Semantic proximity Read ↗

LightGBM-Based Classification of Heart Failure Phenotypes Using Morpho-Energy Features from High-Resolution ECG.Semantic proximity Read ↗

Pericardial adiposity is independently linked to adverse cardiovascular phenotypes: a CMR study of 42 598 UK Biobank participants.Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.