ArticleEuropean heart journal2025
Deep learning-quantified body composition from positron emission tomography/computed tomography and cardiovascular outcomes: a multicentre study.
Article in European heart journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Correlation Between Epicardial Adipose Tissue and PET Cardiac Perfusion: A Systematic Review.Medical sciences (Basel, Switzerland) · 2026Pooled it
- PRIME 2.0: Proposed Requirements for Cardiovascular Imaging-Related Multimodal-AI Evaluation: An Updated Checklist.JACC. Cardiovascular imaging · 2026Guideline
- Prognostic impact of epicardial fat volume, anatomical and functional imaging across the cardiovascular risk spectrum in patients with suspected coronary artery disease: a single-center retrospective cohort study.Quantitative imaging in medicine and surgery · 2026Article
- Mediastinal adipose tissue as an active player in cardiovascular disease: a multimodality imaging narrative review.Quantitative imaging in medicine and surgery · 2026Review
- Role of systemic and epicardial adipose tissue in cardiometabolic disease.Nature reviews. Cardiology · 2026Review
- Assessment of Lean body mass using whole-body low-dose Ct from Pet/Ct to identify cancer Cachexia.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- Virtual myocardial blood flow and flow reserve from static PET imaging using artificial intelligence.medRxiv : the preprint server for health sciences · 2026Article
- Association of PREVENT risk model with body fat distribution and subclinical left ventricular dysfunction.American journal of preventive cardiology · 2026Article
- Association of skeletal muscle index and intermuscular adipose tissue index measured by non-contrast chest CT with major adverse cardiovascular events in patients with coronary artery disease: a nested case-control study in a Chinese population.Frontiers in cardiovascular medicine · 2026Article
- CT-derived myosteatosis for baseline risk stratification of cardiotoxicity in patients with diffuse large B-cell lymphoma receiving anthracyclines.BMC medical imaging · 2025Article
- The REgistry of Flow and Perfusion Imaging for Artificial Intelligence with positron emission tomography (REFINE PET):Rationale and design.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2025Article
- Total-body positron emission tomography: Investigating mechanisms in cardiovascular-kidney-metabolic syndrome.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2025Review
- Bone Mineral Density and Intermuscular Fat Derived from Computed Tomography Images Using Artificial Intelligence Are Associated with Fracture Healing.Bioengineering (Basel, Switzerland) · 2025Article
- Associations between cardiac adipose tissue and abdominal visceral fat and muscle based on computed tomography area and density.Scientific reports · 2025Article
Corrections and comments
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Authors and funding
14 authors.
Funding
Abstract
BACKGROUND AND
aimsPositron emission tomography (PET)/computed tomography (CT) myocardial perfusion imaging (MPI) is a vital diagnostic tool, especially in patients with cardiometabolic syndrome. Low-dose CT scans are routinely performed with PET for attenuation correction and potentially contain valuable data about body tissue composition. Deep learning and image processing were combined to automatically quantify skeletal muscle (SM), bone and adipose tissue from these scans and then evaluate their associations with death or myocardial infarction (MI).
methodsIn PET MPI from three sites, deep learning quantified SM, bone, epicardial adipose tissue (EAT), subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and intermuscular adipose tissue (IMAT). Sex-specific thresholds for abnormal values were established. Associations with death or MI were evaluated using unadjusted and multivariable models adjusted for clinical and imaging factors.
resultsThis study included 10 085 patients, with median age 68 (interquartile range 59-76) and 5767 (57%) male. Body tissue segmentations were completed in 102 ± 4 s. Higher VAT density was associated with an increased risk of death or MI in both unadjusted [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.37-1.43] and adjusted (HR 1.24, 95% CI 1.19-1.28) analyses, with similar findings for IMAT, SAT, and EAT. Patients with elevated VAT density and reduced myocardial flow reserve had a significantly increased risk of death or MI (adjusted HR 2.49, 95% CI 2.23-2.77).
conclusionsVolumetric body tissue composition can be obtained rapidly and automatically from standard cardiac PET/CT. This new information provides a detailed, quantitative assessment of sarcopenia and cardiometabolic health for physicians.
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