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Distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma by computed tomography and magnetic resonance imaging using the Bayesian method: a bi-center study

  • Hepatobiliary-Pancreas
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

To determine imaging hallmarks for distinguishing intrahepatic mass-forming biliary carcinomas (IMBCs) from hepatocellular carcinoma (HCC) and to validate their diagnostic ability using Bayesian statistics.

Methods

Study 1 retrospectively identified clinical and imaging hallmarks that distinguish IMBCs (n = 41) from HCC (n = 247) using computed tomography (CT) and magnetic resonance imaging (MRI). Study 2 retrospectively assessed the diagnostic ability of these hallmarks to distinguish IMBCs (n = 37) from HCC (n = 111) using Bayesian statistics with images obtained from a different institution. We also assessed the diagnostic ability of the hallmarks in the patient subgroup with high diagnostic confidence (≥ 80% of post-test probability). Two radiologists independently evaluated the imaging findings in studies 1 and 2.

Results

In study 1, arterial phase peritumoral parenchymal enhancement on CT/MRI, delayed enhancement on CT/MRI, diffusion-weighted imaging peripheral hyperintensity, and bile duct dilatation were hallmarks indicating IMBCs, whereas chronic liver disease, non-rim arterial phase hyperenhancement on CT/MRI, enhancing capsule on CT/MRI, and opposed-phase signal drop were hallmarks indicating HCC (p = 0.001–0.04). In study 2, Bayesian statistics-based post-test probability combining all hallmark features had a diagnostic accuracy of 89.2% (132/148) in distinguishing IMBCs from HCC for both readers. In the high diagnostic confidence subgroup (n = 120 and n = 124 for readers 1 and 2, respectively), the accuracy improved (95.0% (114/120) and 93.5% (116/124) for readers 1 and 2, respectively).

Conclusions

Combined interpretation of CT and MRI to identify hallmark features is useful in discriminating IMBCs from HCCs. High post-test probability by Bayesian statistics allows for a more reliable non-invasive diagnosis.

Key Points

• Combined interpretation of CT and MRI to identify hallmark features was useful in discriminating intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma.

• Bayesian method-based post-test probability combining all hallmark features determined in study 1 showed high (> 90%) sensitivity and specificity for distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma.

• If the post-test probability or the confidence was ≥ 80% when combining the imaging features of CT and MRI, the high specificity of > 95% was achieved without any loss of sensitivity to distinguish hepatocellular carcinoma from intrahepatic mass-forming biliary carcinomas.

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Abbreviations

APHE:

Arterial phase hyperenhancement

CT:

Computed tomography

DWI:

Diffusion-weighted image

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

IMBC:

Intrahepatic mass-forming biliary carcinoma

MRI:

Magnetic resonance imaging

PVP:

Portal venous phase

T1WI:

T1-weighted image

T2WI:

T2-weighted image

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

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Authors

Corresponding author

Correspondence to Shintaro Ichikawa.

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Guarantor

The scientific guarantor of this publication is Utaroh Motosugi.

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

One of the authors (Daiki Tamada in University of Yamanashi) has significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• cross sectional study

• multicenter study

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Ichikawa, S., Isoda, H., Shimizu, T. et al. Distinguishing intrahepatic mass-forming biliary carcinomas from hepatocellular carcinoma by computed tomography and magnetic resonance imaging using the Bayesian method: a bi-center study. Eur Radiol 30, 5992–6002 (2020). https://doi.org/10.1007/s00330-020-06972-w

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  • DOI: https://doi.org/10.1007/s00330-020-06972-w

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