Early Prediction of Heart Failure From Routine Cardiac CT Using Radiomic Phenotyping of Epicardial Fat
Year: 2026
Type: article
Study design: Observational Study
Abstract: 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 heart failure (HF) risk stratification. OBJECTIVES: We sought to develop and externally validate a reproducible radiomic signature of EAT associated with incident HF. METHODS: ). The model was developed in 59,327 individuals from 7 centers (age 57 ± 13 years, 47.5% female) and externally tested in 13,424 participants from 2 geographically distinct centers (58 ± 12 years, 49.4% female). Survival models were adjusted for age, sex, and conventional risk factors, including coronary artery disease (CAD) severity and EAT volume. RESULTS: to conventional risk models, including EAT volume and CAD severity, significantly improved 5-year discrimination (ΔAUC: 0.047; 95% CI: 0.029-0.065) and net reclassification (NRI: 0.39; 95% CI: 0.29-0.48) and suggested net clinical benefit on decision curve analysis. The associations were consistent across demographic subgroups and across the ejection fraction spectrum. CONCLUSIONS: Automated radiomic phenotyping of EAT from routine CCTA enables scalable, biologically informed stratification of future HF risk before clinical onset, positioning opportunistic imaging-based visceral fat profiling as a potential tool for precision prevention.
Authors: Evangelos K. Oikonomou, Kenneth Chan, Parijat Patel, Elizabeth Wahome, Katerina Dangas, Rohan Desai, Ikboljon Sobirov, Rohan Khera, Steffen E. Petersen, Francesca Pugliese, Ronak Rajani, Edward Nicol, Attila Kardos, David Adlam, Andrew D. Kelion, Nikant Sabharwal, Nicholas Screaton, John P. Greenwood, Jonathan Rodrigues, Daniel Huck, Cheerag Shirodaria, Pete Tomlins, Muhammad Siddique, Yogesh Sohan, Sam Fry, Marly van Assen, Ron Blankstein, Milind Y. Desai, Stefan Neubauer, Keith M. Channon, John Deanfield, Charalambos Antoniades, Sheena Thomas, Jon Denton, Robyn Farrall, Wendy Qin, Mary Kasongo, Chrisha Ledesma, Damaris Darby, Ahmad Abdullrahman, Bruno Silva Santos, Alexios S. Antonopoulos, Christos P. Kotanidis, Susan Anthony, Adrian Banning, Cheng Xie, Rafail A. Kotronias, Lucy Kingham, Rajesh K. Kharbanda, Chris Mathers, Edward Nicol, Tarun K. Mittal, Jonathan, Weir-Macall, Attila Kardos, Anne Rose, David Adlam, George Hudson, Amrita Bajaj, Intrajeet Das, Aparna Deshpande, Praveen Rao, Dan Lawday, Francesca Pugliese, Steffen E. Petersen, Saeed Mirsadraee, Nicholas Screaton, Jonathan Rodrigues, David Murphy, Benjamin Hudson, John Graby, Colin Berry, Mohamed Marwan, Pál Maurovich-Horvat, Guo-Wei He, Wen-Hua Lin, Naohiko Takahashi
Institutions: Yale University, University of Oxford, University of London, St Bartholomew's Hospital, Queen Mary University of London, Barts Health NHS Trust, William Harvey Research Institute, St Thomas' Hospital, King's College London, Harefield Hospital, Milton Keynes Hospital, Milton Keynes Hospital NHS Foundation Trust, University of Leicester, NIHR Leicester Biomedical Research Centre, John Radcliffe Hospital, Royal Papworth Hospital, Baker Heart and Diabetes Institute, Leeds Teaching Hospitals NHS Trust, Royal United Hospital Bath NHS Trust, Brigham and Women's Hospital, Harvard University, Emory University Hospital, Cleveland Clinic, University College London
Language: English
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $7,166
OpenAlex ID: W7151982564