• European radiology · Nov 2020

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

    • Shintaro Ichikawa, Hiroyoshi Isoda, Tatsuya Shimizu, Daiki Tamada, Kojiro Taura, Kaori Togashi, Hiroshi Onishi, and Utaroh Motosugi.
    • Department of Radiology, University of Yamanashi, 1110 Shimokato, Chuo-shi, Yamanashi, 409-3898, Japan. sichikawa@yamanashi.ac.jp.
    • Eur Radiol. 2020 Nov 1; 30 (11): 5992-6002.

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

      Pubmed     Full text   Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.