European Radiology

, Volume 29, Issue 12, pp 6447–6457 | Cite as

Combination of CT findings can reliably predict radiolucent common bile duct stones: a novel approach using a CT-based nomogram

  • Ji Hye Min
  • Kyung Sook ShinEmail author
  • Jeong Eun Lee
  • Seo-Youn Choi
  • Soohyun Ahn



To identify CT features that reliably predict the presence of radiolucent common bile duct (CBD) stones.

Materials and methods

This 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.


In 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%).


The 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.


Common bile duct calculi Diagnosis Tomography, X-ray computed Endoscopic retrograde cholangiopancreatography Nomogram 



Alkaline phosphatase


Alanine aminotransferase


Aspartate aminotransferase


Common bile duct


Confidence interval


Computed tomography


Endoscopic retrograde cholangiopancreatography


Endoscopic ultrasonography




Gamma-glutamyl transpeptidase


Intraclass correlation coefficients


Magnetic resonance cholangiopancreatography


Negative predictive value


Odds ratio


Picture archiving and communication system


Positive predictive value


Receiver operating characteristic





The authors state that this work has not received any funding.

Compliance with ethical standards


The scientific guarantor of this publication is Kyung Sook Shin in the Department of Radiology, Chungnam National University Hospital, Chungnam National University College of Medicine, Daejeon, Republic of Korea.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Two of the authors have significant statistical expertise (Seo-Youn Choi and Soohyun Ahn).

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.


• Retrospective

• Observational

• Performed at one institution

Supplementary material

330_2019_6258_MOESM1_ESM.docx (677 kb)
ESM 1 (DOCX 677 kb)


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Ji Hye Min
    • 1
  • Kyung Sook Shin
    • 2
    Email author
  • Jeong Eun Lee
    • 2
  • Seo-Youn Choi
    • 3
  • Soohyun Ahn
    • 4
  1. 1.Department of Radiology and Center for Imaging Science, Samsung Medical CenterSungkyunkwan University School of MedicineSeoulRepublic of Korea
  2. 2.Department of Radiology, Chungnam National University HospitalChungnam National University College of MedicineDaejeonRepublic of Korea
  3. 3.Department of Radiology, Bucheon HospitalSoonchunhyang University College of MedicineBucheonRepublic of Korea
  4. 4.Department of MathematicsAjou UniversitySuwonRepublic of Korea

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