Skip to main content
SpringerLink
Log in

Evaluation of treatment response in hepatocellular carcinoma in the explanted liver with Liver Imaging Reporting and Data System version 2017

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

A Correction to this article was published on 23 November 2020

This article has been updated

Abstract

Objective

To investigate the performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 treatment response algorithm for predicting hepatocellular carcinoma (HCC) viability after locoregional therapy (LRT) using the liver explant as reference.

Methods

One hundred fourteen patients with 206 HCCs who underwent liver transplantation (LT) after LRT for HCCs were included in this retrospective study. Two radiologists independently evaluated tumor viability using the LI-RADS and modified RECIST (mRECIST) with CT and MRI, respectively. The sensitivity and specificity of arterial phase hyperenhancement (APHE) and LR-TR viable criteria (any of three findings: APHE, washout, and enhancement pattern similar to pretreatment imaging) were compared using logistic regression. Receiver operating characteristics (ROC) analysis was used to compare the diagnostic performance between LI-RADS and mRECIST and between CT and MRI.

Results

The sensitivity and specificity for diagnosing viable tumor were not significantly different between APHE alone and LR-TR viable criteria on CT (p = 0.054 and p = 0.317) and MRI (p = 0.093 and p = 0.603). On CT, the area under the ROC curve (AUC) of LI-RADS was significantly higher than that of mRECIST (0.733 vs. 0.657, p < 0.001). On MRI, there was no significant difference in AUCs between LI-RADS and mRECIST (0.802 vs. 0.791, p = 0.500). Intra-individual comparison of CT and MRI showed comparable AUCs using LI-RADS (0.783 vs. 0.795, p = 0.776).

Conclusions

LI-RADS v2017 treatment response algorithm showed better diagnostic performance than mRECIST on CT. With LI-RADS, CT and MRI were comparable to diagnose tumor viability of HCC after LRT.

Key Points

• Using Liver Imaging Reporting and Data System (LI-RADS) v2017 treatment response algorithm, the viability of hepatocellular carcinoma (HCC) after locoregional therapy (LRT) can be accurately diagnosed.

• LI-RADS v2017 treatment response algorithm is superior to modified Response Evaluation Criteria in Solid Tumors for evaluating HCC viability using CT.

• Either CT or MRI can be performed to assess tumor viability after LRT using LI-RADS v2017 treatment response algorithm.

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

Access this article

Log in via an institution

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

Similar content being viewed by others

Change history

  • 23 November 2020

    The original version of this article, published on 15 August 2019, unfortunately contained a mistake.

Abbreviations

APHE:

Arterial phase hyperenhancement

CT:

Computed tomography

EASL:

European Association for the Study of the Liver

GEE:

Generalized estimating equation

HCC:

Hepatocellular carcinoma

LI-RADS:

Liver Imaging Reporting and Data System

LRT:

Locoregional therapy

LT:

Liver transplantation

mRECIST:

Modified Response Criteria in Solid Tumors

MRI:

Magnetic resonance imaging

PACS:

Picture archiving and communication system

RFA:

Radiofrequency ablation

TACE:

Transarterial chemoembolization

WHO:

World Health Organization

References

  1. Yao FY, Fidelman N (2016) Reassessing the boundaries of liver transplantation for hepatocellular carcinoma: where do we stand with tumor down-staging? Hepatology 63:1014–1025

    Article  Google Scholar 

  2. Miller AB, Hoogstraten B, Staquet M, Winkler A (1981) Reporting results of cancer treatment. Cancer 47:207–214

    Article  CAS  Google Scholar 

  3. Therasse P, Arbuck SG, Eisenhauer EA et al (2000) New guidelines to evaluate the response to treatment in solid tumors. J Natl Cancer Inst 92:205–216

    Article  CAS  Google Scholar 

  4. Bruix J, Sherman M, Llovet JM et al (2001) Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference. European Association for the Study of the Liver. J Hepatol 35:421–430

    Article  CAS  Google Scholar 

  5. Lencioni R, Llovet JM (2010) Modified RECIST (mRECIST) assessment for hepatocellular carcinoma. Semin Liver Dis 30:52–60

    Article  CAS  Google Scholar 

  6. Shim JH, Lee HC, Kim SO et al (2012) Which response criteria best help predict survival of patients with hepatocellular carcinoma following chemoembolization? A validation study of old and new models. Radiology 262:708–718

    Article  Google Scholar 

  7. Jung ES, Kim JH, Yoon EL et al (2013) Comparison of the methods for tumor response assessment in patients with hepatocellular carcinoma undergoing transarterial chemoembolization. J Hepatol 58:1181–1187

    Article  Google Scholar 

  8. Kim HD, Shim JH, Kim GA et al (2015) Optimal methods for measuring eligibility for liver transplant in hepatocellular carcinoma patients undergoing transarterial chemoembolization. J Hepatol 62:1076–1084

    Article  Google Scholar 

  9. Gordic S, Corcuera-Solano I, Stueck A et al (2017) Evaluation of HCC response to locoregional therapy: validation of MRI-based response criteria versus explant pathology. J Hepatol 67:1213–1221

    Article  Google Scholar 

  10. American College of Radiology. Liver imaging reporting and data system (LI-RADS). American College of Radiology. Web site. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS/CT-MRI-LI-RADS-v2017. Accessed 1 June 2017

  11. Kielar A, Fowler KJ, Lewis S et al (2018) Locoregional therapies for hepatocellular carcinoma and the new LI-RADS treatment response algorithm. Abdom Radiol (NY) 43:218–230

    Article  Google Scholar 

  12. Seo N, Kim MS, Park MS et al (2019) Optimal criteria for hepatocellular carcinoma diagnosis using CT in patients undergoing liver transplantation. Eur Radiol 29:1022–1031

    Article  Google Scholar 

  13. Luca A, Caruso S, Milazzo M et al (2010) Multidetector-row computed tomography (MDCT) for the diagnosis of hepatocellular carcinoma in cirrhotic candidates for liver transplantation: prevalence of radiological vascular patterns and histological correlation with liver explants. Eur Radiol 20:898–907

    Article  Google Scholar 

  14. Elsayes KM, Hooker JC, Agrons MM et al (2017) 2017 version of LI-RADS for CT and MR imaging: an update. Radiographics 37:1994–2017

    Article  Google Scholar 

  15. Edmondson HA, Steiner PE (1954) Primary carcinoma of the liver: a study of 100 cases among 48,900 necropsies. Cancer 7:462–503

    Article  CAS  Google Scholar 

  16. Hillis SL, Berbaum KS, Metz CE (2008) Recent developments in the Dorfman-Berbaum-Metz procedure for multireader ROC study analysis. Acad Radiol 15:647–661

    Article  Google Scholar 

  17. Landis JR, Koch GG (1977) The measurement of observer agreement for categorical data. Biometrics 33:159–174

    Article  CAS  Google Scholar 

  18. American College of Radiology. Liver Imaging Reporting and Data System. https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS. Accessed 6 May 2019

  19. Bargellini I, Vignali C, Cioni R et al (2010) Hepatocellular carcinoma: CT for tumor response after transarterial chemoembolization in patients exceeding Milan criteria--selection parameter for liver transplantation. Radiology 255:289–300

    Article  Google Scholar 

  20. Hunt SJ, Yu W, Weintraub J, Prince MR, Kothary N (2009) Radiologic monitoring of hepatocellular carcinoma tumor viability after transhepatic arterial chemoembolization: estimating the accuracy of contrast-enhanced cross-sectional imaging with histopathologic correlation. J Vasc Interv Radiol 20:30–38

    Article  Google Scholar 

  21. Kloeckner R, Otto G, Biesterfeld S, Oberholzer K, Dueber C, Pitton MB (2010) MDCT versus MRI assessment of tumor response after transarterial chemoembolization for the treatment of hepatocellular carcinoma. Cardiovasc Intervent Radiol 33:532–540

    Article  Google Scholar 

  22. Shim JH, Han S, Shin YM et al (2013) Optimal measurement modality and method for evaluation of responses to transarterial chemoembolization of hepatocellular carcinoma based on enhancement criteria. J Vasc Interv Radiol 24:316–325

    Article  Google Scholar 

  23. 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 

  24. Cha DI, Lee MW, Kim YK et al (2014) Assessing patients with hepatocellular carcinoma meeting the Milan criteria: is liver 3 tesla MR with gadoxetic acid necessary in addition to liver CT? J Magn Reson Imaging 39:842–852

    Article  Google Scholar 

  25. Kakihara D, Nishie A, Harada N et al (2014) Performance of gadoxetic acid-enhanced MRI for detecting hepatocellular carcinoma in recipients of living-related-liver-transplantation: comparison with dynamic multidetector row computed tomography and angiography-assisted computed tomography. J Magn Reson Imaging 40:1112–1120

    Article  Google Scholar 

Download references

Funding

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

Author information

Authors and Affiliations

  1. Department of Radiology, Severance Hospital, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea

    Nieun Seo, Mi-Suk Park, Jin-Young Choi & Myeong-Jin Kim

  2. Department of Surgery, Yonsei University College of Medicine, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea

    Myoung Soo Kim

  3. Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Richard K. G. Do

  4. Department of Radiology, Research Institute of Radiological Science, Yonsei Biomedical Research Institute, 50 Yonsei-ro, Seodaemun-gu, Seoul, 03722, South Korea

    Kyunghwa Han

Authors
  1. Nieun Seo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Myoung Soo Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mi-Suk Park
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jin-Young Choi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Richard K. G. Do
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kyunghwa Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Myeong-Jin Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Mi-Suk Park.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Mi-Suk Park.

Conflict of interest

The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Statistics and biometry

Kyunghwa Han performed statistical analysis, who is one of the coauthors.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• Retrospective

• Diagnostic or prognostic study

• Performed at one institution

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 19 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Seo, N., Kim, M.S., Park, MS. et al. Evaluation of treatment response in hepatocellular carcinoma in the explanted liver with Liver Imaging Reporting and Data System version 2017. Eur Radiol 30, 261–271 (2020). https://doi.org/10.1007/s00330-019-06376-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-019-06376-5

Keywords

Search

Navigation