ArticleRadiology. Artificial intelligence2019
Fully Automated CT Quantification of Epicardial Adipose Tissue by Deep Learning: A Multicenter Study.
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Article in Radiology. Artificial intelligence, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 71 papers.
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71citing papers in PubMed
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71 citing papers in PubMed.
- Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a prospective study.Cardiovascular research · 2020Trial
- Deep Learning-Based Quantification of Epicardial Adipose Tissue Volume and Attenuation Predicts Major Adverse Cardiovascular Events in Asymptomatic Subjects.Circulation. Cardiovascular imaging · 2020Trial
- Role of systemic and epicardial adipose tissue in cardiometabolic disease.Nature reviews. Cardiology · 2026Review
- CT Attenuation Map-Derived Body Composition Is Associated with Cardiorespiratory Fitness in Multicenter External Validation.medRxiv : the preprint server for health sciences · 2026Article
- Association of epicardial adipose tissue with markers of cardiac remodelling and clinical outcomes in asymptomatic aortic stenosis.Open heart · 2026Observational
- Epicardial and paracardial adipose tissue quantification in short-axis cardiac cine MRI using deep learning.Magma (New York, N.Y.) · 2026Article
- Fine-grained epicardial adipose tissue segmentation in cardiac CT images with position priors and edge enhancement.Biomedical engineering letters · 2026Article
- Patients with persistent atrial fibrillation and metabolic comorbidities have an altered inflammatory state of atrial epicardial adipose tissue, which is linked to CT-attenuation.Cardiovascular diabetology · 2025Article
- Epicardial adipose tissue and ablation outcomes in obese patients with paroxysmal atrial fibrillation: A comparison of pulsed field and radiofrequency ablation.Heart rhythm O2 · 2025Article
- Deep learning-based quantification of epicardial adipose tissue volume from non-contrast computed tomography images: a multi-centre study.European heart journal. Digital health · 2025Article
- AI in Adipose Imaging: Revolutionizing Visceral Adipose Tissue, Ectopic Fat, and Cardiovascular Risk Assessment.Current atherosclerosis reports · 2025Review
- Ectopic adipose tissue in subsistence populations with minimal coronary disease, large left atria, and very low rates of atrial fibrillation.American journal of preventive cardiology · 2025Article
- Increased Amounts of Epicardial Fat Tissue Are Not Associated With Mitral Annular Calcification in Patients With Severe Aortic Stenosis Planned for Transcatheter Aortic Valve Implantation.Structural heart : the journal of the Heart Team · 2025Article
- AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.Cardiovascular diabetology · 2025Article
- Epicardial Adipose Tissue: A Multimodal Imaging Diagnostic Perspective.Medicina (Kaunas, Lithuania) · 2025Review
- Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.NPJ digital medicine · 2025Article
- Coronary Inflammation and Cardiovascular Events in Patients Without Obstructive Coronary Artery Disease.Current cardiology reports · 2025Review
- Deep learning for opportunistic, end-to-end automated assessment of epicardial adipose tissue in pre-interventional, ECG-gated spiral computed tomography.Insights into imaging · 2024Article
- The change of epicardial adipose tissue characteristics and vulnerability for atrial fibrillation upon drastic weight loss.Adipocyte · 2024Article
- Using artificial intelligence to study atherosclerosis from computed tomography imaging: A state-of-the-art review of the current literature.Atherosclerosis · 2024Review
11 more citing papers are in PubMed but not listed here.
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Authors and funding
14 authors.
Frederic CommandeurBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Markus GoellerBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Aryabod RazipourBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Sebastien CadetBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Michaela M HellBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Jacek KwiecinskiBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Xi ChenBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Hyuk-Jae ChangBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Mohamed MarwanBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Stephan AchenbachBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).ORCID 0000-0002-7596-095X
Daniel S BermanBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).ORCID 0000-0002-3793-9578
Piotr J SlomkaBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).ORCID 0000-0002-6110-938X
Balaji K TamarappooBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).
Damini DeyBiomedical Imaging Research Institute (F.C., A.R., D.D.) and Department of Imaging and Medicine (S.C., J.K., X.C., D.S.B., P.J.S., B.K.T.), Cedars-Sinai Medical Center, 8700 Beverly Blvd, Taper A238, Los Angeles, CA 90048; Department of Cardiology, Friedrich-Alexander University Erlangen-Nürnberg, Erlangen, Germany (M.G., M.M.H., M.M., S.A.); and Severance Cardiovascular Hospital, Yonsei University College of Medicine, Seoul, South Korea (H.J.C.).ORCID 0000-0003-2236-6970
Funding
Automated quantitative CT imaging of epicardial adipose tissue and risk of cardiac eventsR01HL133616 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI · 2016 to 2019
$2.6MNHLBI NIH HHS R01 HL133616
Abstract
purposeTo evaluate the performance of deep learning for robust and fully automated quantification of epicardial adipose tissue (EAT) from multicenter cardiac CT data. MATERIALS AND
methodsIn this multicenter study, a convolutional neural network approach was trained to quantify EAT on non-contrast material-enhanced calcium-scoring CT scans from multiple cohorts, scanners, and protocols (
resultsAutomated quantification was performed in a mean (± standard deviation) time of 1.57 seconds ± 0.49, compared with 15 minutes for experts. Deep learning provided high agreement with expert manual quantification for all scans (
conclusionDeep learning allows rapid, robust, and fully automated quantification of EAT from calcium scoring CT. It performs as well as an expert reader and can be implemented for routine cardiovascular risk assessment.© RSNA, 2019See also the commentary by Schoepf and Abadia in this issue.
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