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. 2020 Nov;30(11):5992-6002. doi: 10.1007/s00330-020-06972-w. Epub 2020 Jun 4.

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.

Keywords: Bayesian method; Hepatocellular carcinoma; Intrahepatic cholangiocarcinoma; Magnetic resonance imaging; Multidetector computed tomography.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Bayes Theorem
  • Bile Duct Neoplasms / diagnostic imaging*
  • Bile Ducts, Intrahepatic / diagnostic imaging*
  • Carcinoma, Hepatocellular / diagnostic imaging*
  • Cholangiocarcinoma / diagnostic imaging*
  • Contrast Media
  • Diagnosis, Differential*
  • Diffusion Magnetic Resonance Imaging
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Liver Neoplasms / diagnostic imaging*
  • Machine Learning
  • Magnetic Resonance Imaging / methods
  • Male
  • Middle Aged
  • Retrospective Studies
  • Sensitivity and Specificity
  • Tomography, X-Ray Computed / methods

Substances

  • Contrast Media