Skip to main content
Log in

Liver Imaging Reporting and Data System (LI-RADS) v2018: diagnostic value of ancillary features favoring malignancy in hypervascular observations ≥ 10 mm at intermediate (LR-3) and high probability (LR-4) for hepatocellular carcinoma

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

This study was conducted in order to assess the diagnostic accuracy of LI-RADS v2018 ancillary features (AFs) favoring malignancy applied to LR-3 and LR-4 observations on gadoxetate-enhanced MRI.

Methods

In this retrospective dual-institution study, we included consecutive patients at high risk for hepatocellular carcinoma (HCC) imaged with gadoxetate disodium-enhanced MRI between 2009 and 2014 fulfilling the following criteria: (i) at least one LR-3 or LR-4 observation ≥ 10 mm; (ii) nonrim arterial phase hyperenhancement; and (iii) confirmation of benignity or malignancy by pathology or imaging follow-up. We compared the distribution of AFs between HCCs and benign observations and the diagnostic performance for the diagnosis of HCC using univariate and multivariate analyses. Significance was set at p value < 0.05.

Results

Two hundred five observations were selected in 155 patients (108 M, 47 F) including 167 (81.5%) LR-3 and 38 (18.5%) LR-4. There were 126 (61.5%) HCCs and 79 (28.5%) benign lesions. A significantly larger number of AFs favoring malignancy were found in LR-3 and LR-4 lesions that progressed to HCC compared to benign lesions (p < 0.001 and p = 0.003, respectively). The most common AFs favoring malignancy in HCCs were hepatobiliary phase (HBP) hypointensity (p < 0.001), transitional phase hypointensity (p < 0.001), and mild–moderate T2 hyperintensity (p < 0.001). Sensitivity and specificity of AFs for the diagnosis of HCC ranged 0.8–76.2% and 86.1–100%, respectively. HBP hypointensity yielded the highest sensitivity but also the lowest specificity and was the only AF remaining independently associated with the diagnosis of HCC at multivariate logistic regression analysis (OR 14.83, 95% CI 5.81–42.76, p < 0.001).

Conclusions

Among all AFs, HBP hypointensity yields the highest sensitivity for the diagnosis of HCC.

Key Points

• LR-3 and LR-4 observations diagnosed as HCC have a significantly higher number of ancillary features favoring malignancy compared to observations proven to be benign.

• The presence of three or more ancillary features favoring malignancy has a high specificity (96.2%) for the diagnosis of HCC.

• Among all ancillary features favoring malignancy, hepatobiliary phase hypointensity yields the highest sensitivity, but also the lowest specificity for the diagnosis of HCC.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

3D:

Three-dimensional

AFs:

Ancillary features

AP:

Arterial phase

APHE:

Arterial phase hyperenhancement

AUC:

Area-under-the-curve

DWI:

Diffusion-weighted images

FSE:

Fast spin echo

GRE:

Gradient-recalled echo

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

IQR:

Interquartile range

LI-RADS:

Liver Imaging Reporting and Data System

MRI:

Magnetic resonance imaging

NPV:

Negative predictive values

OATP:

Organic anion transporting polypeptide

PPV:

Positive predictive value

PVP:

Portal venous phase

ROC:

Receiver operating characteristic

TP:

Transitional phase

VIBE:

Volumetric interpolated breath-hold examination

References

  1. American College of Radiology. CT/MRI Liver imaging reporting and data system v2018 core. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/CT-MRI-LI-RADS-v2018. Accessed June 2019

  2. Chernyak V, Fowler KJ, Kamaya A et al (2018) Liver Imaging Reporting and Data System (LI-RADS) version 2018: imaging of hepatocellular carcinoma in at-risk patients. Radiology 289:816–830

    Article  Google Scholar 

  3. Fowler KJ, Tang A, Santillan C et al (2018) Interreader reliability of LI-RADS version 2014 algorithm and imaging features for diagnosis of hepatocellular carcinoma: a large international multireader study. Radiology 286:173–185

    Article  Google Scholar 

  4. Marrero JA, Kulik LM, Sirlin C 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

    Article  Google Scholar 

  5. Tang A, Bashir MR, Corwin MT et al (2018) Evidence supporting LI-RADS major features for CT- and MR imaging-based diagnosis of hepatocellular carcinoma: a systematic review. Radiology 286:29–48

    Article  Google Scholar 

  6. Chernyak V, Tang A, Flusberg M et al (2018) LI-RADS® ancillary features on CT and MRI. Abdom Radiol (NY) 43:82–100

    Article  Google Scholar 

  7. Cerny M, Bergeron C, Billiard JS et al (2018) LI-RADS for MR imaging diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Radiology 288:118–128

    Article  Google Scholar 

  8. Alhasan A, Cerny M, Olivié D et al (2019) LI-RADS for CT diagnosis of hepatocellular carcinoma: performance of major and ancillary features. Abdom Radiol (NY) 44:517–528

    Article  Google Scholar 

  9. Min JH, Kim JM, Kim YK et al (2018) Prospective intraindividual comparison of magnetic resonance imaging with gadoxetic acid and extracellular contrast for diagnosis of hepatocellular carcinomas using the liver imaging reporting and data system. Hepatology 68:2254–2266

    Article  CAS  Google Scholar 

  10. Granata V, Fusco R, Avallone A et al (2017) Critical analysis of the major and ancillary imaging features of LI-RADS on 127 proven HCCs evaluated with functional and morphological MRI: lights and shadows. Oncotarget 8:51224–51237

    Article  Google Scholar 

  11. Ronot M, Fouque O, Esvan M, Lebigot J, Aubé C, Vilgrain V (2018) Comparison of the accuracy of AASLD and LI-RADS criteria for the non-invasive diagnosis of HCC smaller than 3 cm. J Hepatol 68:715–723

    Article  Google Scholar 

  12. Choi SH, Byun JH, Kim SY et al (2016) Liver imaging reporting and data system v2014 with gadoxetate disodium-enhanced magnetic resonance imaging: validation of LI-RADS category 4 and 5 criteria. Invest Radiol 51:483–490

    Article  CAS  Google Scholar 

  13. Joo I, Lee JM, Lee DH, Ahn SJ, Lee ES, Han JK (2017) Liver imaging reporting and data system v2014 categorization of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: comparison with multiphasic multidetector computed tomography. J Magn Reson Imaging 45:731–740

    Article  Google Scholar 

  14. Ludwig DR, Fraum TJ, Cannella R et al (2019) Hepatocellular carcinoma (HCC) versus non-HCC: accuracy and reliability of Liver Imaging Reporting and Data System v2018. Abdom Radiol (NY) 44:2116–2132

    Article  Google Scholar 

  15. Cerny M, Chernyak V, Olivié D et al (2018) LI-RADS version 2018 ancillary features at MRI. Radiographics 38:1973–2001

    Article  Google Scholar 

  16. Vernuccio F, Cannella R, Meyer M et al (2019) LI-RADS: diagnostic performance of hepatobiliary phase hypointensity and major imaging features of LR-3 and LR-4 lesions measuring 10-19 mm with arterial phase hyperenhancement. AJR Am J Roentgenol 213:W57–W65

    Article  Google Scholar 

  17. Joo I, Lee JM, Lee DH, Jeon JH, Han JK (2019) Retrospective validation of a new diagnostic criterion for hepatocellular carcinoma on gadoxetic acid-enhanced MRI: can hypointensity on the hepatobiliary phase be used as an alternative to washout with the aid of ancillary features? Eur Radiol 29:1724–1732

    Article  Google Scholar 

  18. Kim DH, Choi SH, Kim SY, Kim MJ, Lee SS, Byun JH (2019) Gadoxetic acid-enhanced MRI of hepatocellular carcinoma: value of washout in transitional and hepatobiliary phases. Radiology 291:651–657

    Article  Google Scholar 

  19. Kim SS, Kim SH, Song KD, Choi SY, Heo NH (2019) Value of gadoxetic acid-enhanced MRI and diffusion-weighted imaging in the differentiation of hypervascular hyperplastic nodule from small (<3 cm) hypervascular hepatocellular carcinoma in patients with alcoholic liver cirrhosis: a retrospective case-control study. J Magn Reson Imaging. https://doi.org/10.1002/jmri.26768

  20. Cho YK, Kim JW, Kim MY, Cho HJ (2018) Non-hypervascular hypointense nodules on hepatocyte phase gadoxetic acid-enhanced MR images: transformation of MR hepatobiliary hypointense nodules into hypervascular hepatocellular carcinomas. Gut Liver 12:79–85

    Article  Google Scholar 

  21. Briani C, Di Pietropaolo M, Marignani M et al (2018) Non-hypervascular hypointense nodules at gadoxetic acid MRI: hepatocellular carcinoma risk assessment with emphasis on the role of diffusion-weighted imaging. J Gastrointest Cancer 49:302–310

    Article  CAS  Google Scholar 

  22. Cha DI, Jang KM, Kim SH, Kang TW, Song KD (2017) Liver Imaging Reporting and Data System on CT and gadoxetic acid-enhanced MRI with diffusion-weighted imaging. Eur Radiol 27:4394–4405

    Article  Google Scholar 

  23. Kamath A, Roudenko A, Hecht E et al (2019) CT/MR LI-RADS 2018: clinical implications and management recommendations. Abdom Radiol (NY) 44:1306–1322

    Article  Google Scholar 

  24. Kim YY, An C, Kim S, Kim MJ (2018) Diagnostic accuracy of prospective application of the Liver Imaging Reporting and Data System (LI-RADS) in gadoxetate-enhanced MRI. Eur Radiol 28:2038–2046

    Article  Google Scholar 

  25. Hong CW, Park CC, Mamidipalli A et al (2019) Longitudinal evolution of CT and MRI LI-RADS v2014 category 1, 2, 3, and 4 observations. Eur Radiol. https://doi.org/10.1007/s00330-019-06058-2

  26. Choi SH, Byun JH, Lim YS et al (2018) Liver Imaging Reporting and Data System: patient outcomes for category 4 and 5 nodules. Radiology 287:515–524

    Article  Google Scholar 

  27. Choi JY, Cho HC, Sun M, Kim HC, Sirlin CB (2013) Indeterminate observations (liver imaging reporting and data system category 3) on MRI in the cirrhotic liver: fate and clinical implications. AJR Am J Roentgenol 201:993–1001

    Article  Google Scholar 

  28. Tanabe M, Kanki A, Wolfson T et al (2016) Imaging outcomes of liver imaging reporting and data system version 2014 category 2, 3, and 4 observations detected at CT and MR imaging. Radiology 281:129–139

    Article  Google Scholar 

  29. Burke LM, Sofue K, Alagiyawanna M et al (2016) Natural history of liver imaging reporting and data system category 4 nodules in MRI. Abdom Radiol (NY) 41:1758–1766

    Article  Google Scholar 

  30. van der Pol CB, Lim CS, Sirlin CB 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

    Article  Google Scholar 

  31. Sofue K, Burke LMB, Nilmini V et al (2017) Liver imaging reporting and data system category 4 observations in MRI: risk factors predicting upgrade to category 5. J Magn Reson Imaging 46:783–792

    Article  Google Scholar 

  32. Song JS, Choi EJ, Hwang SB, Hwang HP, Choi H (2019) LI-RADS v2014 categorization of hepatocellular carcinoma: intraindividual comparison between gadopentetate dimeglumine-enhanced MRI and gadoxetic acid-enhanced MRI. Eur Radiol 29:401–410

    Article  Google Scholar 

  33. Kierans AS, Makkar J, Guniganti P et al (2018) Validation of Liver Imaging Reporting and Data System 2017 (LI-RADS) criteria for imaging diagnosis of hepatocellular carcinoma. J Magn Reson Imaging 49:e205–e215

    Article  Google Scholar 

  34. Fraum TJ, Tsai R, Rohe E, Ludwig DR et al (2018) Differentiation of hepatocellular carcinoma from other hepatic malignancies in patients at risk: diagnostic performance of the Liver Imaging Reporting and Data System Version 2014. Radiology 286:158–172

    Article  Google Scholar 

Download references

Funding

The authors state that this work has not received any funding.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Alessandro Furlan.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Alessandro Furlan.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Daniele Marin: research support from Siemens Healthineers; and Alessandro Furlan: royalties from Elsevier/Amirsys and consultant for Bracco.

Statistics and biometry

Two of the authors (Hersh Sagreiya and Kingshuk Roy Choudhury) have significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

We would like to specify that 104/155 patients were included in a previous study (title: LI-RADS: diagnostic performance of hepatobiliary phase hypointensity and major imaging features of LR-3 and LR-4 lesions measuring 10–19 mm with arterial phase hyperenhancement) where we reported the diagnostic performance of the HBP hypointensity and major features in LR-3 and LR-4 observations with APHE measuring 10–19 mm and classified according to LI-RADS v2017. Conversely, in this study, we aim at investigating the diagnostic performance of all AFs favoring malignancy, not only HBP hypointensity, for the diagnosis of HCC using the LI-RADS v2018.

Methodology

• Retrospective

• Diagnostic or prognostic study

• Multicenter study

Additional information

Publisher’s note

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

Electronic supplementary material

ESM 1

(DOCX 25 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cannella, R., Vernuccio, F., Sagreiya, H. et al. Liver Imaging Reporting and Data System (LI-RADS) v2018: diagnostic value of ancillary features favoring malignancy in hypervascular observations ≥ 10 mm at intermediate (LR-3) and high probability (LR-4) for hepatocellular carcinoma. Eur Radiol 30, 3770–3781 (2020). https://doi.org/10.1007/s00330-020-06698-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-020-06698-9

Keywords

Navigation