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<p>LR-M is a category within the Liver Imaging Reporting and Data System (LI-RADS) that refers to liver observations that are probably or definitely malignant but are not specific to hepatocellular carcinoma (HCC). It includes etiologies such as atypical HCC, intrahepatic cholangiocarcinoma, combined hepatocellular cholangiocarcinoma and metastases. The primary aim of LR-M is to ensure a high sensitivity for detecting all hepatic malignancies while preserving a high specificity for HCC in LR-5. The imaging criteria for LR-M encompass a variety of targetoid and non-targetoid features. LR-M is often less well understood by end-users compared to more prominent categories such as LR-4 and LR-5, which have garnered greater attention and familiarity. In this review written from an end-user perspective, we examine the critical role that LR-M plays within LI-RADS for CT/MRI, the prevalence of HCC and non-HCC malignancies in LR-M, and demonstrate how LR-M can impact prognosis and treatment outcomes. We discuss the current imaging criteria for LR-M and the challenges faced by end-users in LI-RADS v2018 for CT/MRI. Finally, we explore future directions for improving the application of LR-M in clinical practice.</p>

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LR-M for CT/MRI on LI-RADS v2018: a review of imaging criteria, performance, challenges and future directions from an end-user perspective

  • 期刊论文

  • 发表日期：

    2025年8月14日

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  • Gavin Low,
  • Tyler Pfanner,
  • Xu Jing Qian,
  • Ali Ramji,
  • Karim Samji,
  • Mitchell P. Wilson

摘要

LR-M is a category within the Liver Imaging Reporting and Data System (LI-RADS) that refers to liver observations that are probably or definitely malignant but are not specific to hepatocellular carcinoma (HCC). It includes etiologies such as atypical HCC, intrahepatic cholangiocarcinoma, combined hepatocellular cholangiocarcinoma and metastases. The primary aim of LR-M is to ensure a high sensitivity for detecting all hepatic malignancies while preserving a high specificity for HCC in LR-5. The imaging criteria for LR-M encompass a variety of targetoid and non-targetoid features. LR-M is often less well understood by end-users compared to more prominent categories such as LR-4 and LR-5, which have garnered greater attention and familiarity. In this review written from an end-user perspective, we examine the critical role that LR-M plays within LI-RADS for CT/MRI, the prevalence of HCC and non-HCC malignancies in LR-M, and demonstrate how LR-M can impact prognosis and treatment outcomes. We discuss the current imaging criteria for LR-M and the challenges faced by end-users in LI-RADS v2018 for CT/MRI. Finally, we explore future directions for improving the application of LR-M in clinical practice.