Skip to main content
Log in

Preoperative prediction of pathologic grade of HCC on gadobenate dimeglumine-enhanced dynamic MRI

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Purpose

To evaluate the value of gadobenate dimeglumine–enhanced MRI in predicting the pathologic grade of hepatocellular carcinoma (HCC).

Materials and methods

Patients with pathologically proven HCC who underwent preoperative gadobenate dimeglumine–enhanced dynamic MRI were included. Two radiologists blinded to pathology results evaluated images in consensus. Lesions were evaluated quantitatively in terms of ratio of enhancement (RE), and qualitatively based on image features related to tumor aggressiveness. Logistic regression and ROC analyses were used to determine the value of these parameters to predict pathologic grade.

Results

In total, 221 patients (194 males, 27 females, aged 52.9 ± 11.7 years) with 49 poorly differentiated HCCs and 172 well/moderately differentiated HCCs were evaluated. Features significantly related to poorer pathologic grade at univariate analysis included lower RE in the early arterial phase (EAP) (p = 0.001), nonsmooth margins (p = 0.001), absence of capsule (p < 0.001), arterial peritumoral hyperenhancement (p < 0.001), higher AFP (p = 0.004), multiple tumors (p = 0.026), and larger tumor size (p = 0.028). At multivariate analysis, lower RE (EAP) (OR = 0.144, p = 0.002), absence of capsule (OR = 0.281, p = 0.004), and arterial peritumoral hyperenhancement (OR = 4.117, p < 0.001) were independent predictive factors for poorer pathologic grade. ROC analysis showed lower RE (EAP) was predictive of poorer pathologic grade (AUC = 0.667). AUC increased to 0.797 when combined with absence of capsule and presence of peritumoral hyperenhancement.

Conclusions

Lower RE (EAP), absence of capsule, and arterial peritumoral hyperenhancement were predictive biomarkers for poorer pathologic grade of HCC on gadobenate dimeglumine–enhanced dynamic MRI.

Key Points

• Gadobenate dimeglumine–enhanced dynamic MRI was a useful quantitative biomarker for preoperative prediction of pathologic grade in patients with HCC.

• Lower RE in the early arterial phase, absence of capsule, and arterial peritumoral hyperenhancement were potential imaging indicators for preoperative prediction of poorer pathologic grade of HCC on gadobenate dimeglumine–enhanced MRI.

• A lower RE in the early arterial phase was effective at predicting poorer pathologic grade of HCCs but prediction is improved when combined with absence of capsule and presence of peritumoral hyperenhancement.

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
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

AP:

Arterial phase

DCE:

Dynamic contrast enhancement

DP:

Delayed phase

EAP:

Early arterial phase

EPVP:

Early portal venous phase

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

LAP:

Late arterial phase

LPVP:

Late portal venous phase

MD:

Moderate differentiation

PD:

Poor differentiation

PVP:

Portal venous phase

RE:

Ratio of enhancement

SBRT:

Stereotactic body radiation therapy

SI:

Signal intensity

TACE:

Transarterial chemoembolization

TARE:

Transarterial radioembolization

WD:

Well differentiation

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A (2018) Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 68:394–424

    Article  Google Scholar 

  2. Forner A, Reig M, Bruix J (2018) Hepatocellular carcinoma. Lancet 391:1301–1314

    Article  Google Scholar 

  3. Marrero JA, Kulik LM, Sirlin CB 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 

  4. Villanueva A (2019) Hepatocellular Carcinoma. N Engl J Med 380:1450–1462

    Article  CAS  Google Scholar 

  5. Kwon SK, Yun SS, Kim HJ, Lee DS (2014) The risk factors of early recurrence after hepatectomy in hepatocellular carcinoma. Ann Surg Treat Res 86:283–288

    Article  CAS  Google Scholar 

  6. Regimbeau JM, Abdalla EK, Vauthey JN et al (2004) Risk factors for early death due to recurrence after liver resection for hepatocellular carcinoma: Results of a multicenter study. J Surg Oncol 85:36–41

    Article  Google Scholar 

  7. Ng IO, Lai EC, Fan ST, Ng MM, So MK (1995) Prognostic significance of pathologic features of hepatocellular carcinoma. A multivariate analysis of 278 patients. Cancer 76:2443–2448

    Article  CAS  Google Scholar 

  8. Jonas S, Bechstein WO, Steinmuller T et al (2001) Vascular invasion and histopathologic grading determine outcome after liver transplantation for hepatocellular carcinoma in cirrhosis. Hepatology 33:1080–1086

    Article  CAS  Google Scholar 

  9. Zhou L, Rui JA, Zhou WX, Wang SB, Chen SG, Qu Q (2017) Edmondson-Steiner grade: A crucial predictor of recurrence and survival in hepatocellular carcinoma without microvascular invasio. Pathol Res Pract 213:824–830

    Article  Google Scholar 

  10. Ren Z, He S, Fan X et al (2017) Survival prediction model for postoperative hepatocellular carcinoma patients. Medicine (Baltimore) 96:e7902

    Article  Google Scholar 

  11. Stigliano R, Marelli L, Yu D, Davies N, Patch D, Burroughs AK (2007) Seeding following percutaneous diagnostic and therapeutic approaches for hepatocellular carcinoma. What is the risk and the outcome? Seeding risk for percutaneous approach of HCC. Cancer Treat Rev 33:437–447

    Article  CAS  Google Scholar 

  12. Kim TH, Kim SY, Tang A, Lee JM (2019) Comparison of international guidelines for noninvasive diagnosis of hepatocellular carcinoma: 2018 update. Clin Mol Hepatol 25:245–263

    Article  Google Scholar 

  13. Huang X, Xiao Z, Zhang Y et al (2018) Hepatocellular carcinoma: Retrospective evaluation of the correlation between gadobenate dimeglumine-enhanced magnetic resonance imaging and pathologic grade. J Comput Assist Tomogr 42:365–372

    Article  Google Scholar 

  14. Tahir B, Sandrasegaran K, Ramaswamy R et al (2011) Does the hepatocellular phase of gadobenate dimeglumine help to differentiate hepatocellular carcinoma in cirrhotic patients according to histological grade? Clin Radiol 66:845–852

    Article  CAS  Google Scholar 

  15. Choi YS, Rhee H, Choi JY et al (2013) Histological characteristics of small hepatocellular carcinomas showing atypical enhancement patterns on gadoxetic acid-enhanced MR imaging. J Magn Reson Imaging 37:1384–1391

    Article  Google Scholar 

  16. Jin YJ, Cho SG, Lee KY, Kim JM, Lee JW (2017) Association between relative liver enhancement on gadoxetic acid enhanced magnetic resonance images and histologic grade of hepatocellular carcinoma. Medicine (Baltimore) 96:e7580

    Article  CAS  Google Scholar 

  17. Chou YC, Lao IH, Hsieh PL et al (2019) Gadoxetic acid-enhanced magnetic resonance imaging can predict the pathologic stage of solitary hepatocellular carcinoma. World J Gastroenterol 25:2636–2649

    Article  Google Scholar 

  18. Choi JW, Lee JM, Kim SJ et al (2013) Hepatocellular carcinoma: Imaging patterns on gadoxetic acid-enhanced MR images and their value as an imaging biomarker. Radiology 267:776–786

    Article  Google Scholar 

  19. Kitao A, Matsui O, Yoneda N et al (2012) Hypervascular hepatocellular carcinoma: Correlation between biologic features and signal intensity on gadoxetic acid-enhanced MR images. Radiology 265:780–789

    Article  Google Scholar 

  20. Ariizumi S, Kitagawa K, Kotera Y et al (2011) A non-smooth tumor margin in the hepatobiliary phase of gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging predicts microscopic portal vein invasion, intrahepatic metastasis, and early recurrence after hepatectomy in patients with hepatocellular carcinoma. J Hepatobiliary Pancreat Sci 18:575–585

    Article  Google Scholar 

  21. Costa AF, Thipphavong S, Arnason T, Stueck AE, Clarke SE (2018) Fat-containing liver lesions on imaging: Detection and differential diagnosis. AJR Am J Roentgenol 210:68–77

    Article  Google Scholar 

  22. WHO Classification of tumors: Digestive system tumours. 5th ed. Lyon, France. Available via https://whobluebooks.iarc.fr/publications/index.php. Accessed 19 January 2021.

  23. Bedossa P, Poynard T (1996) An algorithm for the grading of activity in chronic hepatitis C. The METAVIR Cooperative Study Group. Hepatology 24:289–293

    Article  CAS  Google Scholar 

  24. Kim SS, Lee S, Bae H et al (2020) Extended application of subtraction arterial phase imaging in LI-RADS version 2018: A strategy to improve the diagnostic performance for hepatocellular carcinoma on gadoxetate disodium-enhanced MRI. Eur Radiol. https://doi.org/10.1007/s00330-020-07229-2

  25. Stocker D, Becker AS, Barth BK et al (2020) Does quantitative assessment of arterial phase hyperenhancement and washout improve LI-RADS v2018-based classification of liver lesions? Eur Radiol 30:2922–2933

    Article  Google Scholar 

  26. Vogl TJ, Stupavsky A, Pegios W et al (1997) Hepatocellular carcinoma: Evaluation with dynamic and static gadobenate dimeglumine-enhanced MR imaging and histopathologic correlation. Radiology 205:721–728

    Article  CAS  Google Scholar 

  27. Nathan H, Schulick RD, Choti MA, Pawlik TM (2009) Predictors of survival after resection of early hepatocellular carcinoma. Ann Surg 249:799–805

    Article  Google Scholar 

  28. Asayama Y, Yoshimitsu K, Nishihara Y et al (2008) Arterial blood supply of hepatocellular carcinoma and histologic grading: Radiologic-pathologic correlation. AJR Am J Roentgenol 190:W28–W34

    Article  Google Scholar 

  29. Kim DK, An C, Chung YE et al (2019) Hepatobiliary versus extracellular MRI contrast agents in hepatocellular carcinoma detection: Hepatobiliary phase features in relation to disease-free survival. Radiology 293:594–604

    Article  Google Scholar 

  30. Ayyappan AP, Jhaveri KS (2010) CT and MRI of hepatocellular carcinoma: An update. Expert Rev Anticancer Ther 10:507–519

    Article  Google Scholar 

  31. Lim JH, Choi D, Park CK, Lee WJ, Lim HK (2006) Encapsulated hepatocellular carcinoma: CT-pathologic correlations. Eur Radiol 16:2326–2333

    Article  Google Scholar 

  32. Kim H, Park MS, Choi JY et al (2009) Can microvessel invasion of hepatocellular carcinoma be predicted by pre-operative MRI? Eur Radiol 19:1744–1751

    Article  Google Scholar 

  33. Nishie A, Yoshimitsu K, Asayama Y et al (2008) Radiologic detectability of minute portal venous invasion in hepatocellular carcinoma. AJR Am J Roentgenol 190:81–87

    Article  Google Scholar 

  34. Gao SX, Liao R, Wang HQ, Liu D, Luo F (2019) A nomogram predicting microvascular invasion risk in BCLC 0/A hepatocellular carcinoma after curative resection. Biomed Res Int 2019:9264137

  35. Lee S, Kim SH, Lee JE, Sinn DH, Park CK (2017) Preoperative gadoxetic acid-enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma. J Hepatol 67:526–534

    Article  CAS  Google Scholar 

  36. Witjes CD, Willemssen FE, Verheij J et al (2012) Histological differentiation grade and microvascular invasion of hepatocellular carcinoma predicted by dynamic contrast-enhanced MRI. J Magn Reson Imaging 36:641–647

    Article  Google Scholar 

  37. Zhou L, Rui JA, Wang SB, Chen SG, Qu Q (2014) Risk factors of microvascular invasion, portal vein tumor thrombosis and poor post-resectional survival in HBV-related hepatocellular carcinoma. Hepatogastroenterology 61:1696–1703

    PubMed  Google Scholar 

Download references

Funding

The authors state that this study has received funding by the National Natural Science Foundation of China grant 91959118 (JW), Science and Technology Program of Guangzhou, China grant 201704020016 (JW), SKY Radiology Department International Medical Research Foundation of China Z-2014-07-1912-15 (JW), Clinical Research Foundation of the 3rd Affiliated Hospital of Sun Yat-Sen University YHJH201901 (JW), and Key Research and Development Program of Guangdong Province 2019B020235002 (JW).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jin Wang.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Jin Wang.

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

No complex statistical methods were necessary for this paper.

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.

Supplementary Information

ESM 1

(DOCX 23 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rong, D., Liu, W., Kuang, S. et al. Preoperative prediction of pathologic grade of HCC on gadobenate dimeglumine-enhanced dynamic MRI. Eur Radiol 31, 7584–7593 (2021). https://doi.org/10.1007/s00330-021-07891-0

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-021-07891-0

Keywords

Navigation