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<Articles JournalTitle="Acta Medica Iranica">
  <Article>
    <Journal>
      <PublisherName>Tehran University of Medical Sciences</PublisherName>
      <JournalTitle>Acta Medica Iranica</JournalTitle>
      <Issn>0044-6025</Issn>
      <Volume>63</Volume>
      <Issue>2</Issue>
      <PubDate PubStatus="epublish">
        <Year>2025</Year>
        <Month>07</Month>
        <Day>09</Day>
      </PubDate>
    </Journal>
    <title locale="en_US">Assessment of LI-RADS Efficacy in the Classification of Hepatocellular Carcinoma and Benign Liver Nodules Using DCE-MRI Features and ADC MRI</title>
    <FirstPage>120</FirstPage>
    <LastPage>126</LastPage>
    <AuthorList>
      <Author>
        <FirstName>Suhail Najm</FirstName>
        <LastName>Alareer Hayder</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq.</affiliation>
      </Author>
      <Author>
        <FirstName>Hussein</FirstName>
        <LastName>Abed Dakhil</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq</affiliation>
      </Author>
      <Author>
        <FirstName>Mustafa Moahmmed Hammood</FirstName>
        <LastName>Alshammri</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq</affiliation>
      </Author>
      <Author>
        <FirstName>Moamil Ali</FirstName>
        <LastName>Makki</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq</affiliation>
      </Author>
      <Author>
        <FirstName>M.M</FirstName>
        <LastName>Abou Halaka</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq</affiliation>
      </Author>
      <Author>
        <FirstName>Basman</FirstName>
        <LastName>Radhi Majeed</LastName>
        <affiliation locale="en_US">Department of Radiology Technologies, College of Health &amp; Medical Technology, Al-Ayen Iraqi University, Thi-Qar, Iraq</affiliation>
      </Author>
    </AuthorList>
    <History>
      <PubDate PubStatus="received">
        <Year>2025</Year>
        <Month>01</Month>
        <Day>04</Day>
      </PubDate>
      <PubDate PubStatus="accepted">
        <Year>2025</Year>
        <Month>04</Month>
        <Day>10</Day>
      </PubDate>
    </History>
    <abstract locale="en_US">The Liver Imaging Reporting and Data System (LI-RADS) is a widely utilized tool for classifying liver lesions, particularly in patients at risk for hepatocellular carcinoma (HCC). This study aims to assess the efficacy of LI-RADS in distinguishing between HCC and benign liver nodules by leveraging dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) features and apparent diffusion coefficient (ADC) values derived from MRI. Between October 2023 and March 2024, 43 patients with suspected HCC underwent MRI evaluation, including DCE-MRI and DWI sequences. The diagnostic performance of various MRI sequences was analyzed, focusing on their ability to differentiate HCC from benign lesions. The diagnostic efficacy of DCE-MRI and ADC in differentiation was evaluated using statistical analyses, such as t-tests and receiver operating characteristic (ROC) curve analysis. SPSS VER 16 was used to analyze the collected data. The study findings reveal that the DCE-MRI arterial phase demonstrated perfect diagnostic accuracy with an area under the curve (AUC) of 1.00, achieving 100% sensitivity and specificity. T2-weighted imaging also exhibited diagnostic solid performance, with an AUC of 0.801, while ADC values from DWI sequences showed limited efficacy in differentiating HCC from benign lesions (AUC=0.512). These findings indicate that DCE-MRI significantly enhances the accuracy of LI-RADS in classifying HCC versus benign liver nodules. This study highlights the importance of incorporating advanced imaging features into LI-RADS to improve the diagnostic precision of liver lesion evaluation in clinical practice.</abstract>
    <web_url>https://acta.tums.ac.ir/index.php/acta/article/view/11452</web_url>
  </Article>
</Articles>
