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    Article

    Liver imaging: it is time to adopt standardized terminology

    Liver imaging plays a vital role in the management of patients at risk for hepatocellular carcinoma (HCC); however, progress in the field is challenged by nonuniform and inconsistent terminology in the publish...

    Victoria Chernyak, An Tang, Richard K. G. Do, Aya Kamaya, Yuko Kono in European Radiology (2022)

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    Deep convolutional neural network applied to the liver imaging reporting and data system (LI-RADS) version 2014 category classification: a pilot study

    To develop a deep convolutional neural network (CNN) model to categorize multiphase CT and MRI liver observations using the liver imaging reporting and data system (LI-RADS) (version 2014).

    Rikiya Yamashita, Amber Mittendorf, Zhe Zhu, Kathryn J. Fowler in Abdominal Radiology (2020)

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    Article

    LI-RADS® algorithm: CT and MRI

    The Liver Imaging Reporting and Data System (LI-RADS®) is an imaging-based diagnostic system applicable in patients at high risk of hepatocellular carcinoma (HCC). In LI-RADS, each liver observation is assigned a...

    Victoria Chernyak, Cynthia S. Santillan, Demetri Papadatos in Abdominal Radiology (2018)

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    Article

    Hepatocarcinogenesis and LI-RADS

    Hepatocarcinogenesis is a multi-step process characterized by progressive cellular and molecular dedifferentiation of hepatocytes and culminating in the emergence of hepatocellular carcinoma (HCC). Knowledge o...

    Kazim H. Narsinh, Jennifer Cui, Demetri Papadatos, Claude B. Sirlin in Abdominal Radiology (2018)

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    Article

    Comparative 13-year meta-analysis of the sensitivity and positive predictive value of ultrasound, CT, and MRI for detecting hepatocellular carcinoma

    To compare the per-lesion sensitivity and positive predictive value (PPV) of ultrasonography (US), computed tomography (CT), and magnetic resonance imaging (MRI) for the diagnosis of hepatocellular carcinoma (...

    Robert F. Hanna, Vesselin Z. Miloushev, An Tang, Lee A. Finklestone in Abdominal Radiology (2016)