Skip to main content
SpringerLink
Log in

The role of gadoxetic acid-enhanced MRI features for predicting microvascular invasion in patients with hepatocellular carcinoma

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

Abstract

Objective

To evaluate the predictive value of gadoxetic acid-enhanced MRI features (focused on Liver Imaging Reporting and Data System (LI-RADS) v2018 features and non-LI-RADS imaging features) for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

From October 2018 to December 2020, 134 patients who underwent gadoxetic acid-enhanced MRI with a pathological diagnosis of HCC after hepatectomy were enrolled in this retrospective study. Two radiologists assessed the pre-hepatectomy LI-RADS v2018 imaging features and non-LI-RADS features to identify independent predictors of MVI of HCC with a logistic regression model.

Results

Four MRI features were found to be independent predictors of MVI: corona enhancement [odds ratio (OR) 5.787; 95% confidence interval (CI) 1.180, 28.369; p = 0.030], mosaic architecture (OR 7.097; 95% CI 1.299, 38.783; p = 0.024), nonsmooth tumor margin (OR 13.131; 95% CI 3.950, 43.649; p < 0.001), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR 33.123; 95% CI 2.897, 378.688; p = 0.005). When one of four imaging features was present, the sensitivity was 93.2% (41/44), and the specificity was 71.1% (64/90).

Conclusion

The four imaging features including corona enhancement, mosaic architecture, nonsmooth tumor margin, and peritumoral hypointensity on HBP can be used as preoperative imaging biomarkers for predicting MVI in patients at high risk for HCC. When one of the four imaging features is present, MVI can be predicted with a sensitivity > 90%.

Graphical abstract

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

Similar content being viewed by others

References

  1. Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin. 2015;65(2):87-108.

    Google Scholar 

  2. Bruix J, Gores GJ, Mazzaferro V. Hepatocellular carcinoma: clinical frontiers and perspectives. Gut. 2014;63(5):844-55.

    Article  CAS  Google Scholar 

  3. Isik B, Gonultas F, Sahin T, et al. Microvascular Venous Invasion in Hepatocellular Carcinoma: Why Do Recurrences Occur? J Gastrointest Cancer. 2020;51(4):1133-6.

    Article  Google Scholar 

  4. Yamashita Y, Tsuijita E, Takeishi K, et al. Predictors for Microinvasion of Small Hepatocellular Carcinoma ≤2 cm. Ann Surg Oncol. 2012;19(6):2027-34.

    Article  Google Scholar 

  5. Roayaie S, Blume IN, Thung SN, et al. A system of classifying microvascular invasion to predict outcome after resection in patients with hepatocellular carcinoma. Gastroenterology. 2009;137(3):850-5.

    Article  Google Scholar 

  6. Rodríguez-Perálvarez M, Luong TV, Andreana L, et al. A Systematic Review of Microvascular Invasion in Hepatocellular Carcinoma: Diagnostic and Prognostic Variability. Ann Surg Oncol. 2013;20(1):325-39.

    Article  Google Scholar 

  7. Zhang X, Li J, Shen F, et al. Significance of presence of microvascular invasion in specimens obtained after surgical treatment of hepatocellular carcinoma. J Gastroenterol Hepatol. 2018;33(2):347-54.

    Article  Google Scholar 

  8. Song L, Li J, Luo Y. The importance of a nonsmooth tumor margin and incomplete tumor capsule in predicting HCC microvascular invasion on preoperative imaging examination: a systematic review and meta-analysis. Clin Imaging. 2021;76:77-82.

    Article  Google Scholar 

  9. Lee S, Kim SH, Lee JE, et al. Preoperative gadoxetic acid–enhanced MRI for predicting microvascular invasion in patients with single hepatocellular carcinoma. J Hepatol. 2017;67(3):526-34.

    Article  CAS  Google Scholar 

  10. Wei Y, Huang Z, Tang H, et al. IVIM improves preoperative assessment of microvascular invasion in HCC. Eur Radiol. 2019;29(10):5403-14.

    Article  Google Scholar 

  11. Min JH, Lee MW, Park HS, et al. Interobserver Variability and Diagnostic Performance of Gadoxetic Acid-enhanced MRI for Predicting Microvascular Invasion in Hepatocellular Carcinoma. Radiology. 2020;297(3):573-81.

    Article  Google Scholar 

  12. Chernyak V, Fowler KJ, Kamaya A, et al. Liver Imaging Reporting and Data System (LI-RADS) Version 2018: Imaging of Hepatocellular Carcinoma in At-Risk Patients. Radiology. 2018;289(3):816-30.

    Article  Google Scholar 

  13. Zhang L, Kuang S, Chen J, et al. The Role of Preoperative Dynamic Contrast-enhanced 3.0-T MR Imaging in Predicting Early Recurrence in Patients With Early-Stage Hepatocellular Carcinomas After Curative Resection. Front Oncol. 2019;9:1336.

  14. Chernyak V, Fowler KJ, Heiken JP, et al. Use of gadoxetate disodium in patients with chronic liver disease and its implications for liver imaging reporting and data system (LI-RADS). J Magn Reson Imaging. 2019;49(5):1236-52.

    Article  Google Scholar 

  15. American College of Radiology (ACR). Liver Reporting & Data System (LI-RADS). ACR website. www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS. Published 2018.

  16. Chen J, Zhou J, Kuang S, et al. Liver Imaging Reporting and Data System Category 5: MRI Predictors of Microvascular Invasion and Recurrence After Hepatectomy for Hepatocellular Carcinoma. AJR Am J Roentgenol. 2019;213(4):821-30.

    Article  Google Scholar 

  17. Chernyak V, Tang A, Flusberg M, et al. LI-RADS® ancillary features on CT and MRI. Abdom Radiol. 2018;43(1):82-100.

    Article  Google Scholar 

  18. Choi JY, Lee JM, Sirlin CB. CT and MR imaging diagnosis and staging of hepatocellular carcinoma: part II. Extracellular agents, hepatobiliary agents, and ancillary imaging features. Radiology. 2014;273(1):30–50.

  19. Wei H, Jiang H, Liu X, et al. Can LI-RADS imaging features at gadoxetic acid-enhanced MRI predict aggressive features on pathology of single hepatocellular carcinoma? Eur J Radiol. 2020;132:109312.

  20. Wei H, Jiang H, Zheng T, et al. LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid–enhanced MRI for early recurrence risk stratification after curative resection. Eur Radiol. 2021;31(4):2289-302.

    Article  CAS  Google Scholar 

  21. Li M, Xin Y, Fu S, et al. Corona Enhancement and Mosaic Architecture for Prognosis and Selection Between of Liver Resection Versus Transcatheter Arterial Chemoembolization in Single Hepatocellular Carcinomas >5 cm Without Extrahepatic Metastases: An Imaging-Based Retrospective Study. Medicine (Baltimore). 2016;95(2):e2458.

  22. Hong SB, Choi SH, Kim SY, et al. MRI Features for Predicting Microvascular Invasion of Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis. Liver Cancer. 2021;10(2):94-106.

    Article  Google Scholar 

  23. Moon JY, Min JH, Kim YK, et al. Prognosis after Curative Resection of Single Hepatocellular Carcinoma with A Focus on LI-RADS Targetoid Appearance on Preoperative Gadoxetic Acid-Enhanced MRI. Korean J Radiol. 2021;22(11):1786-96.

    Article  Google Scholar 

  24. Kang HJ, Kim H, Lee DH, et al. Gadoxetate-enhanced MRI Features of Proliferative Hepatocellular Carcinoma Are Prognostic after Surgery. Radiology. 2021;300(3):572-82.

    Article  Google Scholar 

  25. He YZ, He K, Huang RQ, et al. Preoperative evaluation and prediction of clinical scores for hepatocellular carcinoma microvascular invasion: a single-center retrospective analysis. Ann Hepatol. 2020;19(6):654-61.

    Article  CAS  Google Scholar 

  26. Zhang L, Yu X, Wei W, et al. Prediction of HCC microvascular invasion with gadobenate-enhanced MRI: correlation with pathology. Eur Radiol. 2020;30(10):5327-36.

    Article  Google Scholar 

  27. Renzulli M, Brocchi S, Cucchetti A, et al. Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of Hepatocellular Carcinoma? Radiology. 2016;279(2):432-42.

    Article  Google Scholar 

  28. Kim YC, Kim MJ, Park YN, et al. Relationship between severity of liver dysfunction and the relative ratio of liver to aortic enhancement (RE) on MRI using hepatocyte-specific contrast. J Magn Reson Imaging. 2014;39(1):24-30.

    Article  Google Scholar 

  29. Nishie A, Kakihara D, Asayama Y, et al. Detectability of hepatocellular carcinoma on gadoxetic acid-enhanced MRI at 3 T in patients with severe liver dysfunction: clinical impact of dual-source parallel radiofrequency excitation. Clin Radiol. 2015;70(3):254-61.

    Article  CAS  Google Scholar 

  30. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394-424.

    Article  Google Scholar 

Download references

Funding

The authors did not receive any funding for this manuscript.

Author information

Author notes

  1. Hongli Yang and Ping Han have contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China

    Hongli Yang, Ping Han, Mengting Huang, Xiaofei Yue, Linxia Wu, Xin Li, Wenliang Fan, Qian Li, Guina Ma & Ping Lei

  2. Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China

    Hongli Yang, Ping Han, Mengting Huang, Xiaofei Yue, Linxia Wu, Xin Li, Wenliang Fan, Qian Li, Guina Ma & Ping Lei

Authors
  1. Hongli Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ping Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Mengting Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaofei Yue
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Linxia Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wenliang Fan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Qian Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Guina Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Ping Lei
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ping Lei.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

Our institutional review board approved this retrospective study and waived the need for informed consent. This article did not contain any studies with animals.

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

Yang, H., Han, P., Huang, M. et al. The role of gadoxetic acid-enhanced MRI features for predicting microvascular invasion in patients with hepatocellular carcinoma. Abdom Radiol 47, 948–956 (2022). https://doi.org/10.1007/s00261-021-03392-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00261-021-03392-2

Keywords

Search

Navigation