Hepatic and abdominal adiposity in type 2 diabetes as assessed with machine learning on computed tomography scans

Aims The 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 Methods Deep 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. Results Diabetic patients had greater HS (SHAD −4.49 vs. −6.88 Hounsfield units, p = 1.34 × 10 −8 ), steatosis prevalence (41.8% vs. 27.7%, p = 4.85 × 10 −9 ) and VSR (0.62 vs. 0.55, p = 1.69 × 10 −3 ) than nondiabetics. In multivariate analyses adjusting for age, sex, race and body mass index (BMI), diabetes was independently associated with SHAD (odds ratios [OR] 1.04, 95% confidence interval [1.02–1.05]), SV (OR 4.53 [1.89–10.99]) and VSR (OR 2.87, [1.96–4.20]). Combined regression analysis showed no relationship between splenomegaly and type 2 diabetes once controlling for hepatic factors (OR 1.08, [0.95–1.23]), but uncovered a stronger VSR correlation (OR 1.40, [1.20–1.63]) than BMI (OR 1.14, [1.01–1.29]). Conclusions Hepatic 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.