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Purpose <p>The Liver Imaging Reporting and Data System (LI-RADS, LR) provides a framework for diagnosing hepatocellular carcinoma (HCC, LR-5). However, not all HCCs meet LR-5 criteria and are instead categorized as LR-M, probably or definitely malignant but not specific for HCC, necessitating biopsy for diagnosis. The purpose is to identify factors associated with HCC in LR-M observations.</p> Methods <p>This is an IRB-approved, retrospective analysis of participants from 8 institutions that had a LR-M observation on CT or MRI with corresponding histopathologic diagnosis. Demographics and biochemical data were examined. Central review using the LI-RADS v2018 algorithm was performed. Kappa statistics defined inter-reader agreement. Random forest and logistic regression analyses generated a model for HCC diagnosis.</p> Results <p>162 participants with 162 LR-M observations were included. 46% of observations (74/162) were HCC and 37% were cholangiocarcinoma (60/162). Two of 34 imaging features– observation size and intra-lesion iron– showed moderate to strong inter-reader agreement (Kappa ≥ 0.60) while the remainder showed weak or no agreement (Kappa &lt; 0.60). Random forest analysis showed biochemical features to be more predictive of HCC than imaging features. Logistic regression analysis of a model based on INR and AFP provided a 72% sensitivity and 61% specificity for HCC by Youden’s index and a 90% specificity threshold yielded 38% sensitivity, 75% positive predictive value, and 66% negative predictive value.</p> Conclusions <p>Our results show INR and AFP are associated with HCC in LR-M observations. A high-specificity threshold may assist in the non-invasive diagnosis of HCC in the appropriate setting.</p> Summary statement <p>In certain at-risk patients with a LR-M observation on diagnostic imaging, serum AFP and INR maybe useful tools for the non-invasive diagnosis of HCC.</p>

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Predictors of hepatocellular carcinoma in LR-M category lesions, a multi-institutional analysis

  • 期刊论文

  • 发表日期：

    2025年4月28日

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  • Marybeth Nedrud,
  • Tanya Wolfson,
  • Brian Allen,
  • Anum Aslam,
  • Lauren Burke,
  • Victoria Chernyak,
  • Kathryn Fowler,
  • Tyler J. Fraum,
  • Hong-Il Ha,
  • Elizabeth M. Hecht,
  • Tracy Jaffe,
  • Kevin Kalisz,
  • Andrea Siobhan Kierans,
  • Daniel R. Ludwig,
  • Jasnit S. Makkar,
  • Katrina McGinty,
  • Matthew McInnes,
  • Mishal Mendiratta-Lala,
  • Omobonike Oloruntoba,
  • Damithri Ranathunga,
  • Benjamin Wildman-Tobriner,
  • Anthony C. Gamst,
  • Diana M. Cardona,
  • Andrew Muir,
  • Mustafa Bashir

摘要

Purpose

The Liver Imaging Reporting and Data System (LI-RADS, LR) provides a framework for diagnosing hepatocellular carcinoma (HCC, LR-5). However, not all HCCs meet LR-5 criteria and are instead categorized as LR-M, probably or definitely malignant but not specific for HCC, necessitating biopsy for diagnosis. The purpose is to identify factors associated with HCC in LR-M observations.

Methods

This is an IRB-approved, retrospective analysis of participants from 8 institutions that had a LR-M observation on CT or MRI with corresponding histopathologic diagnosis. Demographics and biochemical data were examined. Central review using the LI-RADS v2018 algorithm was performed. Kappa statistics defined inter-reader agreement. Random forest and logistic regression analyses generated a model for HCC diagnosis.

Results

162 participants with 162 LR-M observations were included. 46% of observations (74/162) were HCC and 37% were cholangiocarcinoma (60/162). Two of 34 imaging features– observation size and intra-lesion iron– showed moderate to strong inter-reader agreement (Kappa ≥ 0.60) while the remainder showed weak or no agreement (Kappa < 0.60). Random forest analysis showed biochemical features to be more predictive of HCC than imaging features. Logistic regression analysis of a model based on INR and AFP provided a 72% sensitivity and 61% specificity for HCC by Youden’s index and a 90% specificity threshold yielded 38% sensitivity, 75% positive predictive value, and 66% negative predictive value.

Conclusions

Our results show INR and AFP are associated with HCC in LR-M observations. A high-specificity threshold may assist in the non-invasive diagnosis of HCC in the appropriate setting.

Summary statement

In certain at-risk patients with a LR-M observation on diagnostic imaging, serum AFP and INR maybe useful tools for the non-invasive diagnosis of HCC.