Skip to main content
SpringerLink
Log in

Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology

  • Hepatobiliary-Pancreas
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Purpose

To assess the accuracy of gadobenate-enhanced MRI for predicting microvascular invasion (MVI) in patients operated for hepatocellular carcinoma (HCC).

Methods

The 164 patients who met the inclusion criteria were assigned to one of two groups: the MVI-positive group and the MVI-negative group. Imaging results were compared between the two groups using the Kruskal test, chi-square test, independent sample t test, and logistic regression analysis.

Results

Differences in the capsule (p = 0.037) and margin (p = 0.004) of the tumor, rim enhancement (p = 0.002), peritumoral enhancement in the arterial phase (p < 0.001), and peritumoral hypointensity in the hepatobiliary phase (HBP) (p < 0.001) were statistically significant. The results of multivariate analysis identified rim enhancement in the arterial phase (odds ratio (OR) = 2.115; 95% confidence interval (CI), 1.002–4.464; p = 0.049) and peritumoral hypointensity in the HBP (OR = 5.836; 95% CI, 2.442–13.948; p < 0.001) as independent risk factors for MVI. Use of the two predictors in combination identified 32.79% (20/61) of HCCs with MVI with a specificity of 95.15% (98/103).

Conclusions

Rim enhancement in the arterial phase and peritumoral hypointensity in the HBP were identified as independent risk factors for MVI in patients with HCC.

Key Points

• Rim enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for microvascular invasion in patients with HCC.

• Use of the two predictors in combination had a sensitivity of 32.79% and a specificity of 95.15% for predicting microvascular invasion.

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.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Abbreviations

ADC:

Apparent diffusion coefficient

AFP:

Alpha-fetoprotein

DCE:

Dynamic contrast-enhanced

Gd-BOPTA:

Gadobenate dimeglumine

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

MVI:

Microvascular invasion

PIVKA-II:

Protein Induced by Vitamin K Absence or Antagonist-II

SI:

Signal intensity

References

  1. Banerjee S, Wang DS, Kim HJ et al (2015) A computed tomography radiogenomic biomarker predicts microvascular invasion and clinical outcomes in hepatocellular carcinoma. Hepatology 62:792–800

    Article  Google Scholar 

  2. Lee S, Kim KW, Jeong WK et al (2019) Gadoxetic acid–enhanced MRI as a predictor of recurrence of HCC after liver transplantation. Eur Radiol 30:987–995

    Article  Google Scholar 

  3. Wei Y, Huang ZX, Tang HH et al (2019) IVIM improves preoperative assessment of microvascular invasion in HCC. Eur Radiol 29:5403–5414

    Article  Google Scholar 

  4. Feng ST, Jia YM, Liao B et al (2019) Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI. Eur Radiol 29:4648–4659

    Article  Google Scholar 

  5. Ahn SY, Lee JM, Joo I et al (2015) Prediction of microvascular invasion of hepatocellular carcinoma using gadoxetic acid-enhanced MR and (18) FFDG PET/CT. Abdom Imaging 40:843–851

    Article  Google Scholar 

  6. Renzulli M, Brocchi S, Cucchetti A et al (2016) Can current preoperative imaging be used to detect microvascular invasion of hepatocellular carcinoma? Radiology 279:432–442

    Article  Google Scholar 

  7. An C, Kim DW, Park YN, Chung YE, Rhee H, Kim MJ (2015) Single hepatocellular carcinoma: preoperative MR imaging to predict early recurrence after curative resection. Radiology 276:433–443

  8. 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 

  9. Lee S, Kim SH, Lee JE (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 

  10. Kim JY, Kim MJ, Kim KA, Jeong HT, Park YN (2012) Hyperintense HCC on hepatobiliary phase images of gadoxetic acid-enhanced MRI: correlation with clinical and pathological features. Eur J Radiol 81:3877–3882

  11. Kim KA, Kim MJ, Jeon HM et al (2012) Prediction of microvascular invasion of hepatocellular carcinoma: usefulness of peritumoral hypointensity seen on gadoxetate disodium-enhanced hepatobiliary phase images. J Magn Reson Imaging 35:629–634

    Article  Google Scholar 

  12. Suh YJ, Kim MJ, Choi JY, Park MS, Kim KW (2012) Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging. Liver Transpl 18:1171–1178

  13. Xu P, Zeng M, Liu K, Shan Y, Xu C, Lin J (2014) Microvascular invasion in small hepatocellular carcinoma: is it predictable with preoperative diffusion-weighted imaging? J Gastroenterol Hepatol 29:330–336

  14. Okamura S, Sumie S, Tonan T et al (2016) Diffusion weighted magnetic resonance imaging predicts malignant potential in small hepatocellular carcinoma. Dig Liver Dis 48:945–952

    Article  Google Scholar 

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

    Article  Google Scholar 

  16. Reeder SB, Sirlin CB (2010) Quantification of liver fat with magnetic resonance imaging. Magn Reson Imaging Clin N Am 18:337–357

    Article  Google Scholar 

  17. Choi JY, Lee JM, Sirlin CB (2014) CT and MR imaging diagnosis and staging of hepatocellular carcinoma: part II. Extracellular agents, hepatobiliary agents, and ancillary imaging features. Radiology 273:30–50

    Article  Google Scholar 

  18. 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 

  19. Bosman F, Carneiro F, Hruban R (2010) WHO classification tumours of the digestive system. IARC Press, Lyon

    Google Scholar 

  20. Zhang J, Liu XJ, Zhang HP et al (2019) Texture analysis based on preoperative magnetic resonance imaging (MRI) and conventional MRI features for predicting the early recurrence of single hepatocellular carcinoma after hepatectomy. Acad Radiol 26:1164–1173

    Article  Google Scholar 

  21. Ng IO, Lai EC, Ng MM, Fan ST (1992) Tumor encapsulation in hepatocellular carcinoma. A pathologic study of 189 cases. Cancer 70:45–49

  22. Nakashima Y, Nakashima O, Tanaka M, Okuda K, Nakashima M, Kojiro M (2003) Portal vein invasion and intrahepatic micrometastasis in small hepatocellular carcinoma by gross type. Hepatol Res 26:142–147

  23. Eguchi S, Takatsuki M, Hidaka M et al (2010) Predictor for histological microvascular invasion of hepatocellular carcinoma: a lesson from 229 consecutive cases of curative liver resection. World J Surg 34:1034–1038

  24. Nagano Y, Shimada H, Takeda K et al (2008) Predictive factors of microvascular invasion in patients with hepatocellular carcinoma larger than 5 cm. World J Surg 32:2218–2222

    Article  Google Scholar 

  25. Chou CT, Chen RC, Lee CW et al (2012) Prediction of microvascular invasion of hepatocellular carcinoma by preoperative CT imaging. Br J Radiol 85:778–783

    Article  Google Scholar 

  26. Wu TH, Hatano E, Yamanaka K et al (2016) A non-smooth tumor margin on preoperative imaging predicts microvascular invasion of hepatocellular carcinoma. Surg Today 46:1275–1281

    Article  CAS  Google Scholar 

  27. Hu HT, Wang Z, Huang XW et al (2018) Ultrasound-based radiomics score: a potential biomarker for the prediction of microvascular invasion in hepatocellular carcinoma. Eur Radiol 29:2890–2901

    Article  Google Scholar 

  28. Miyata R, Tanimoto A, Wakabayashi G et al (2006) Accuracy of preoperative prediction of microinvasion of portal vein in hepatocellular carcinoma using superparamagnetic iron oxide–enhanced magnetic resonance imaging and computed tomography during hepatic angiography. J Gastroenterol 41:987–995

    Article  Google Scholar 

Download references

Acknowledgments

We would like to thank the whole study team at 4 hospitals, for continuous support.

Funding

This study has received funding from the Natural Science Foundation of Guangdong Province (2018A030313951), the Foundation of President of Nanfang Hospital (2017C011), the National Science and Technology Major Project (2018ZX10302207-004), the China Medical Research Fund of Guangdong Province (A2017496).

Author information

Author notes

  1. Ling Zhang and Xian Yu contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China

    Ling Zhang

  2. Department of Gastrointestinal Surgery, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, 400030, China

    Xian Yu

  3. Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China

    WenXin Wei

  4. Department of Radiology, Eastern Hepatobiliary Surgery Hospital, Second Military Medical University, Shanghai, 200438, China

    XingPeng Pan, Lun Lu, JinJu Xia, Wei Zheng, Ningyang Jia & Lei Huo

Authors
  1. Ling Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xian Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. WenXin Wei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. XingPeng Pan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lun Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. JinJu Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wei Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Ningyang Jia
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Lei Huo
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Ningyang Jia or Lei Huo.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Chenguang 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

Professor Cairong Zhu kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was not required for this study because Gd-BOPTA had been widely used in MRI scan as a contrast agent.

Ethical approval

Institutional Review Board approval was obtained.

Methodology

• retrospective

• diagnostic 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.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhang, L., Yu, X., Wei, W. et al. Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology. Eur Radiol 30, 5327–5336 (2020). https://doi.org/10.1007/s00330-020-06895-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-020-06895-6

Keywords

Search

Navigation