ArticleDiabetes, obesity & metabolism2026
Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.
Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans.Diabetes, obesity & metabolism · 2026Article
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14 authors.
Funding
Abstract
aimsThe combined assessment of multiple abdominal imaging traits in relation to type 2 diabetes remains incompletely characterised. The study examines these relationships on computed tomography (CT) scans from a large-scale, racially diverse, disease-focused medical biobank. MATERIALS AND
methodsDeep learning algorithms were applied to patients with abdominal CT scans in the Penn Medicine BioBank to quantify image-derived phenotypes, including spleen-hepatic attenuation difference (SHAD) for hepatic steatosis (HS), liver and spleen volumes (SV), abdominal visceral and subcutaneous adipose tissue (VAT and SAT, respectively) and visceral-to-subcutaneous ratio (VSR). One thousand five hundred and ninety-four patients (62 years, 49.4% male, 59.3% White), comprising 950 nondiabetics and 644 diabetics, were included in analysis with diabetes status determined by a 6.5% haemoglobin A1c cutoff.
resultsDiabetic patients had greater HS (SHAD -4.49 vs. -6.88 Hounsfield units, p = 1.34 × 10
conclusionsHepatic steatosis, hepatomegaly and visceral adiposity on CT are associated with type 2 diabetes. Hepatic changes may influence spleen size effects on diabetes. VSR can serve as an alternative to traditional obesity metrics to accurately reflect diabetes risk.
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