ArticleEuropean radiology2019
Combination of CT findings can reliably predict radiolucent common bile duct stones: a novel approach using a CT-based nomogram.
Article in European radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Machine learning prediction of common bile duct stones using synthetic data to guide emergency ERCP decisions.Scientific reports · 2026Article
- Construction and validation of a diagnostic model for acute suppurative cholecystitis in older patients: LASSO-Logistic regression analysis using readily available clinical indicators.BMC geriatrics · 2026Article
- Deep learning enables accurate diagnosis of acute cholecystitis and prediction of suppuration using noncontrast CT.iScience · 2025Article
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5 authors.
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Abstract
objectivesTo identify CT features that reliably predict the presence of radiolucent common bile duct (CBD) stones. MATERIALS AND
methodsThis retrospective study included 112 patients (mean age, 60.6 years) with clinically suspected CBD stones that were not visible on CT. All patients had undergone CT followed by endoscopic retrograde cholangiopancreatography (ERCP) to confirm the presence (n = 66) or absence (n = 46) of CBD stones. Two radiologists independently evaluated the CT images. Univariable and multivariable logistic regression analyses were performed to identify demographic, laboratory, and CT predictors for CBD stones. We developed a nomogram based on these results and assessed its performance.
resultsIn the multivariate analysis, CBD diameter ≥ 8 mm (odds ratio [OR], 10.12; p < 0.001), pericholecystic fat infiltration (OR, 3.76, p = 0.014), and papillitis (OR, 2.85; p < 0.049) were independent CT predictors of CBD stones. Combination of all three features had a specificity of 100%. Of these features, CBD diameter ≥ 8 mm was the best single predictor. The CT-based nomogram had an area under the curve (AUC) of 0.847 (95% confidence interval [CI], 0.777-0.916) and an accuracy of 77.7% (95% CI, 69.1-84.4%).
conclusionsThe combination of significant CT features (CBD diameter ≥ 8 mm, pericholecystic fat infiltration, and papillitis) translated into a nomogram allows a reliable estimation of CBD stone presence. It may serve as a decision support tool to determine whether to proceed to further diagnostic tests or treatment option. KEY POINTS: • CBD diameter ≥ 8 mm (odds ratio [OR] = 10.12, p < 0.001), pericholecystic fat infiltration (OR = 3.76, p = 0.014), and papillitis (OR = 2.85, p = 0.049) were independent predictors of radiolucent CBD stones. • A CBD diameter ≥ 8 mm was the best predictor of CBD stones. • A nomogram based on a combination of these three CT signs predicted the presence of CBD stones and helped classify patients that should go immediately to ERCP, those who require a further investigation, and those who can safely be managed conservatively.
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