Skip to main content
Log in

New strategy for Liver Imaging Reporting and Data System category M to improve diagnostic performance of MRI for hepatocellular carcinoma ≤ 3.0 cm

  • Hepatobiliary
  • Published:
Abdominal Radiology Aims and scope Submit manuscript

Abstract

Purpose

We aimed to determine a new strategy for Liver Imaging Reporting and Data System category M (LR-M) criteria to improve the diagnosis of HCC ≤ 3.0 cm on magnetic resonance imaging (MRI).

Methods

A total of 463 pathologically confirmed hepatic observations ≤ 3.0 cm (375 HCCs, 32 other malignancies, 56 benignities) in 384 patients at risk of HCC who underwent gadoxetate-enhanced MRI were retrospectively analyzed. Two radiologists evaluated the presence of major, ancillary, and LR-M features according to LI-RADS v2018. Of the ten LR-M features, those significantly associated with non-HCC malignancy were identified using multivariable logistic regression analysis, and new LR-M criteria for improving the diagnosis of HCC were investigated. Generalized estimating equations were used to compare sensitivity and specificity of LR-5 for diagnosing HCC using the new LR-M criteria with values calculated using the original LR-M criteria. p < 0.05 was considered to indicate a significant difference.

Results

Of ten LR-M features, rim arterial-phase hyperenhancement, delayed central enhancement, targetoid restriction, and targetoid transitional-phase/hepatobiliary-phase appearance were independently significantly associated with non-HCC malignancy (adjusted odds ratio ≥ 6.2; p ≤ 0.02). Using the new LR-M criteria (two or more of these significant features), the sensitivity of LR-5 for diagnosing HCC was higher than that with the original LR-M criteria (69% [95% confidence interval 64–73%] vs. 65% [61–70%], p = 0.002), whereas the specificity was similar (90% [82–95%] vs. 92% [83–96%], p = 0.28).

Conclusion

The new LR-M criteria (two or more significant features) can improve the sensitivity of LR-5 for diagnosing HCC ≤ 3.0 cm, without compromising specificity.

Graphical abstract

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig.1
Fig. 2

Similar content being viewed by others

Abbreviations

APHE:

Arterial-phase hyperenhancement

CCA:

Intrahepatic cholangiocarcinoma

cHCC-CCA:

Combined hepatocellular-cholangiocarcinoma

CT:

Computed tomography

HBP:

Hepatobiliary-phase

HCC:

Hepatocellular carcinoma

LI-RADS:

Liver Imaging Reporting and Data System

MRI:

Magnetic resonance imaging

NPV:

Negative predictive value

OR:

Odds ratio

PPV:

Positive predictive value

TP:

Transitional phase

References

  1. Mitchell DG, Bruix J, Sherman M, Sirlin CB. (2015) LI-RADS (Liver Imaging Reporting and Data System): summary, discussion, and consensus of the LI-RADS Management Working Group and future directions. Hepatology 61:1056-1065. https://doi.org/10.1002/hep.27304

    Article  PubMed  Google Scholar 

  2. Marrero JA, Kulik LM, Sirlin CB, Zhu AX, Finn RS, Abecassis MM, et al. (2018) Diagnosis, Staging, and Management of Hepatocellular Carcinoma: 2018 Practice Guidance by the American Association for the Study of Liver Diseases. Hepatology 68:723-750. https://doi.org/10.1002/hep.29913

    Article  PubMed  Google Scholar 

  3. American College of Radiology. (2018) CT/MRI LI-RADS v2018. Available via https://www.acrorg/-/media/ACR/Files/RADS/LI-RADS/LI-RADS-2018-Corepdf

  4. Huang B, Wu L, Lu XY, Xu F, Liu CF, Shen WF, et al. (2016) Small Intrahepatic Cholangiocarcinoma and Hepatocellular Carcinoma in Cirrhotic Livers May Share Similar Enhancement Patterns at Multiphase Dynamic MR Imaging. Radiology 281:150-157. https://doi.org/10.1148/radiol.2016151205

    Article  PubMed  Google Scholar 

  5. Fowler KJ, Sheybani A, Parker RA, 3rd, Doherty S, E MB, Chapman WC, et al. (2013) Combined hepatocellular and cholangiocarcinoma (biphenotypic) tumors: imaging features and diagnostic accuracy of contrast-enhanced CT and MRI. AJR Am J Roentgenol 201:332-339. https://doi.org/10.2214/ajr.12.9488

    Article  PubMed  Google Scholar 

  6. Bridgewater J, Galle PR, Khan SA, Llovet JM, Park JW, Patel T, et al. (2014) Guidelines for the diagnosis and management of intrahepatic cholangiocarcinoma. J Hepatol 60:1268-1289. https://doi.org/10.1016/j.jhep.2014.01.021

    Article  PubMed  Google Scholar 

  7. Fowler KJ, Potretzke TA, Hope TA, Costa EA, Wilson SR. (2018) LI-RADS M (LR-M): definite or probable malignancy, not specific for hepatocellular carcinoma. Abdom Radiol (NY) 43:149-157. https://doi.org/10.1007/s00261-017-1196-2

    Article  Google Scholar 

  8. Choi SH, Byun JH, Lim YS, Yu E, Lee SJ, Kim SY, et al. (2016) Diagnostic criteria for hepatocellular carcinoma ⩽3 cm with hepatocyte-specific contrast-enhanced magnetic resonance imaging. J Hepatol 64:1099-1107. https://doi.org/10.1016/j.jhep.2016.01.018

    Article  PubMed  Google Scholar 

  9. Park MJ, Kim YK, Lee MW, Lee WJ, Kim YS, Kim SH, et al. (2012) Small hepatocellular carcinomas: improved sensitivity by combining gadoxetic acid-enhanced and diffusion-weighted MR imaging patterns. Radiology 264:761-770. https://doi.org/10.1148/radiol.12112517

    Article  PubMed  Google Scholar 

  10. Kim DH, Choi SH, Park SH, Kim KW, Byun JH, Kim SY, et al. (2019) Meta-analysis of the accuracy of Liver Imaging Reporting and Data System category 4 or 5 for diagnosing hepatocellular carcinoma. Gut 68:1719-1721. https://doi.org/10.1136/gutjnl-2019-318555

    Article  PubMed  Google Scholar 

  11. van der Pol CB, Lim CS, Sirlin CB, McGrath TA, Salameh JP, Bashir MR, et al. (2019) Accuracy of the Liver Imaging Reporting and Data System in Computed Tomography and Magnetic Resonance Image Analysis of Hepatocellular Carcinoma or Overall Malignancy-A Systematic Review. Gastroenterology 156:976-986. https://doi.org/10.1053/j.gastro.2018.11.020

    Article  PubMed  Google Scholar 

  12. Kim DH, Choi SH, Park SH, Kim KW, Byun JH, Kim SY, et al. (2020) Liver imaging reporting and data system category M: A systematic review and meta-analysis. Liver Int 40:1477-1487. https://doi.org/10.1111/liv.14420

    Article  PubMed  Google Scholar 

  13. Kim MY, Joo I, Kang HJ, Bae JS, Jeon SK, Lee JM. (2020) LI-RADS M (LR-M) criteria and reporting algorithm of v2018: diagnostic values in the assessment of primary liver cancers on gadoxetic acid-enhanced MRI. Abdom Radiol (NY) 45:2440-2448. https://doi.org/10.1007/s00261-020-02545-z

    Article  Google Scholar 

  14. Park HJ, Kim YK, Cha DI, Ko SE, Kim S, Lee ES, et al. (2020) Targetoid hepatic observations on gadoxetic acid-enhanced MRI using LI-RADS version 2018: emphasis on hepatocellular carcinomas assigned to the LR-M category. Clin Radiol 75:478.e413-478.e423. https://doi.org/10.1016/j.crad.2020.01.002

    Article  Google Scholar 

  15. Shao S, Liang Y, Kuang S, Chen J, Shan Q, Yang H, et al. (2020) Diagnostic performance of LI-RADS version 2018 in differentiating hepatocellular carcinoma from other hepatic malignancies in patients with hepatitis B virus infection. Bosn J Basic Med Sci 20:401–410. https://doi.org/10.17305/bjbms.2019.4576

  16. Kim SS, Lee S, Choi JY, Lim JS, Park MS, Kim MJ. (2020) Diagnostic performance of the LR-M criteria and spectrum of LI-RADS imaging features among primary hepatic carcinomas. Abdom Radiol (NY) 45:3743-3754. https://doi.org/10.1007/s00261-020-02562-y

    Article  Google Scholar 

  17. Llovet JM, Fuster J, Bruix J. (2004) The Barcelona approach: diagnosis, staging, and treatment of hepatocellular carcinoma. Liver Transpl 10:S115-120. https://doi.org/10.1002/lt.20034

    Article  PubMed  Google Scholar 

  18. Lu DS, Yu NC, Raman SS, Limanond P, Lassman C, Murray K, et al. (2005) Radiofrequency ablation of hepatocellular carcinoma: treatment success as defined by histologic examination of the explanted liver. Radiology 234:954-960. https://doi.org/10.1148/radiol.2343040153

    Article  PubMed  Google Scholar 

  19. Bland JM. (2004) Cluster randomised trials in the medical literature: two bibliometric surveys. BMC Med Res Methodol 4:21. https://doi.org/10.1186/1471-2288-4-21

    Article  PubMed  PubMed Central  Google Scholar 

  20. Zhang Z. (2018) Estimating the optimal cutoff point for logistic regression. Open Access Theses & Dissertations. https://digitalcommons.utep.edu/open_etd/1565

  21. Kim YY, Kim MJ, Kim EH, Roh YH, An C. (2019) Hepatocellular Carcinoma versus Other Hepatic Malignancy in Cirrhosis: Performance of LI-RADS Version 2018. Radiology 291:72-80. https://doi.org/10.1148/radiol.2019181995

    Article  PubMed  Google Scholar 

  22. Kobayashi M, Ikeda K, Saitoh S, Suzuki F, Tsubota A, Suzuki Y, et al. (2000) Incidence of primary cholangiocellular carcinoma of the liver in japanese patients with hepatitis C virus-related cirrhosis. Cancer 88:2471-2477. https://doi.org/10.1002/1097-0142(20000601)88:11<2471::aid-cncr7>3.0.co;2-t

    Article  CAS  PubMed  Google Scholar 

  23. Ferlan-Marolt V, Markovic S. (1986) Clinicomorphological manifestations of primary liver carcinoma (PLC) in liver cirrhosis. Cancer Detect Prev 9:491-493.

    CAS  PubMed  Google Scholar 

  24. Livraghi T, Meloni F, Di Stasi M, Rolle E, Solbiati L, Tinelli C, et al. (2008) Sustained complete response and complications rates after radiofrequency ablation of very early hepatocellular carcinoma in cirrhosis: Is resection still the treatment of choice? Hepatology 47:82-89. https://doi.org/10.1002/hep.21933

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

This study was financially supported by Bayer Korea, but the authors had complete control of the data and information submitted for publication at all times.

Funding

This study was financially supported by Bayer Korea, but the authors had complete control of the data and information submitted for publication at all times.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jae Ho Byun.

Ethics declarations

Conflict of interest

Sang Hyun Choi is an advisory board member of Bayer Korea and receives research funding from Bayer Korea, but the authors had complete control of the data and information submitted for publication at all times. The other authors have nothing to declare.

Ethical approval

This retrospective study was approved by institutional review board of Asan Medical Center (IRB No. 2019-1556).

Informed consent

The IRB waived informed consent for this study.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (DOCX 22 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jang, J.K., Choi, S.H., Byun, J.H. et al. New strategy for Liver Imaging Reporting and Data System category M to improve diagnostic performance of MRI for hepatocellular carcinoma ≤ 3.0 cm. Abdom Radiol 47, 2289–2298 (2022). https://doi.org/10.1007/s00261-022-03538-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-022-03538-w

Keywords

Navigation