Skip to main content
SpringerLink
Log in

MRI imaging features for predicting macrotrabecular-massive subtype hepatocellular carcinoma: a systematic review and meta-analysis

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

Abstract

Purpose

To identify significant MRI features associated with macrotrabecular-massive hepatocellular carcinoma (MTM-HCC), and to assess the distribution of Liver Imaging Radiology and Data System (LI-RADS, LR) category assignments.

Methods

PubMed and EMBASE were searched up to March 28, 2023. Random-effects model was constructed to calculate pooled diagnostic odds ratios (DORs) and 95% confidence intervals (CIs) for each MRI feature for differentiating MTM-HCC from NMTM-HCC. The pooled proportions of LI-RADS category assignments in MTM-HCC and NMTM-HCC were compared using z-test.

Results

Ten studies included 1978 patients with 2031 HCCs (426 (20.9%) MTM-HCC and 1605 (79.1%) NMTM-HCC). Six MRI features showed significant association with MTM-HCC: tumor in vein (TIV) (DOR = 2.4 [95% CI, 1.6–3.5]), rim arterial phase hyperenhancement (DOR =2.6 [95% CI, 1.4–5.0]), corona enhancement (DOR = 2.6 [95% CI, 1.4–4.5]), intratumoral arteries (DOR = 2.6 [95% CI, 1.1–6.3]), peritumoral hypointensity on hepatobiliary phase (DOR = 2.2 [95% CI, 1.5–3.3]), and necrosis (DOR = 4.2 [95% CI, 2.0–8.5]). The pooled proportions of LI-RADS categories in MTM-HCC were LR-3, 0% [95% CI, 0–2%]; LR-4, 11% [95% CI, 6–16%]; LR-5, 63% [95% CI, 55–71%]; LR-M, 12% [95% CI, 6–19%]; and LR-TIV, 13% [95% CI, 6–22%]. In NMTM-HCC, the pooled proportions of LI-RADS categories were LR-3, 1% [95% CI, 0–2%]; LR-4, 8% [95% CI, 3–15%]; LR-5, 77% [95% CI, 71–82%]; LR-M, 5% [95% CI, 3–7%]; and LR-TIV, 6% [95% CI, 2–11%]. MTM-HCC had significantly lower proportion of LR-5 and higher proportion of LR-M and LR-TIV categories.

Conclusions

Six MRI features showed significant association with MTM-HCC. Additionally, compared to NMTM-HCC, MTM-HCC are more likely to be categorized LR-M and LR-TIV and less likely to be categorized LR-5.

Clinical relevance statement

Several MR imaging features can suggest macrotrabecular-massive hepatocellular carcinoma subtype, which can assist in guiding treatment plans and identifying potential candidates for clinical trials of new treatment strategies.

Key Points

• Macrotrabecular-massive hepatocellular carcinoma is a subtype of HCC characterized by its aggressive nature and unfavorable prognosis.

• Tumor in vein, rim arterial phase hyperenhancement, corona enhancement, intratumoral arteries, peritumoral hypointensity on hepatobiliary phase, and necrosis on MRI are indicative of macrotrabecular-massive hepatocellular carcinoma.

• Various MRI characteristics can be utilized for the diagnosis of the macrotrabecular-massive hepatocellular carcinoma subtype. This can prove beneficial in guiding treatment decisions and identifying potential candidates for clinical trials involving novel treatment approaches.

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

Abbreviations

APHE:

Arterial phase hyperenhancement

CI:

Confidence interval

DOR:

Diagnostic odds ratio

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

LIRADS, LR:

Liver Imaging Reporting and Data System

MTM-HCC:

Macrotrabecular-massive hepatocellular carcinoma

NMTM-HCC:

Non-macrotrabecular-massive hepatocellular carcinoma

QUADAS-2:

Quality Assessment of Diagnostic Accuracy Studies 2

TIV:

Tumor in vein

WHO:

World Health Organization

References

  1. Philips CA, Rajesh S, Nair DC, Ahamed R, Abduljaleel JK, Augustine P (2021) Hepatocellular Carcinoma in 2021: an exhaustive update. Cureus 13:e19274

    PubMed  PubMed Central  Google Scholar 

  2. Nagtegaal ID, Odze RD, Klimstra D et al (2020) The 2019 WHO classification of tumours of the digestive system. Histopathology 76:182–188

    Article  PubMed  Google Scholar 

  3. Ziol M, Poté N, Amaddeo G et al (2018) Macrotrabecular-massive hepatocellular carcinoma: a distinctive histological subtype with clinical relevance. Hepatology 68:103–112

    Article  PubMed  Google Scholar 

  4. Kumar D, Hafez O, Jain D, Zhang X (2021) Can primary hepatocellular carcinoma histomorphology predict extrahepatic metastasis? Hum Pathol 113:39–46

    Article  PubMed  Google Scholar 

  5. (2018) EASL Clinical Practice Guidelines: management of hepatocellular carcinoma. J Hepatol 69:182-236

  6. 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  PubMed  Google Scholar 

  7. Yang Y, Mao S, Fang J et al (2023) Macrotrabecular-massive subtype-based nomogram to predict early recurrence of hepatocellular carcinoma after surgery. Eur J Gastroenterol Hepatol 35:505–511

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Yang Y, Sun JH, Tan XY et al (2023) MTM-HCC at previous liver resection as a predictor of overall survival in salvage liver transplantation. Dig Dis Sci 68:2768–2777

    Article  PubMed  Google Scholar 

  9. Liu LL, Zhang SW, Chao X et al (2021) Coexpression of CMTM6 and PD-L1 as a predictor of poor prognosis in macrotrabecular-massive hepatocellular carcinoma. Cancer Immunol Immunother 70:417–429

    Article  CAS  PubMed  Google Scholar 

  10. Bilal Masokano I, Pei Y, Chen J et al (2022) Development and validation of MRI-based model for the preoperative prediction of macrotrabecular hepatocellular carcinoma subtype. Insights Imaging 13:201

    Article  PubMed  PubMed Central  Google Scholar 

  11. Cannella R, DioguardiBurgio M, Beaufrère A et al (2021) Imaging features of histological subtypes of hepatocellular carcinoma: implication for LI-RADS. JHEP Rep 3:100380

    Article  PubMed  PubMed Central  Google Scholar 

  12. Chen J, Xia C, Duan T et al (2021) Macrotrabecular-massive hepatocellular carcinoma: imaging identification and prediction based on gadoxetic acid-enhanced magnetic resonance imaging. Eur Radiol 31:7696–7704

    Article  CAS  PubMed  Google Scholar 

  13. Kang HJ, Kim H, Lee DH et al (2021) Gadoxetate-enhanced MRI features of proliferative hepatocellular carcinoma are prognostic after surgery. Radiology 300:572–582

    Article  PubMed  Google Scholar 

  14. Liang Y, Xu F, Wang Z et al (2022) A gadoxetic acid-enhanced MRI-based multivariable model using LI-RADS v2018 and other imaging features for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma. Eur J Radiol 153:110356

    Article  PubMed  Google Scholar 

  15. Mulé S, GallettoPregliasco A, Tenenhaus A et al (2020) Multiphase liver MRI for identifying the macrotrabecular-massive subtype of hepatocellular carcinoma. Radiology 295:562–571

    Article  PubMed  Google Scholar 

  16. Mulé S, Serhal A, Pregliasco AG et al (2023) MRI features associated with HCC histologic subtypes: a western American and European bicenter study. Eur Radiol 33:1342–1352

    Article  PubMed  Google Scholar 

  17. Rhee H, Cho ES, Nahm JH et al (2021) Gadoxetic acid-enhanced MRI of macrotrabecular-massive hepatocellular carcinoma and its prognostic implications. J Hepatol 74:109–121

    Article  CAS  PubMed  Google Scholar 

  18. Yang L, Wang M, Zhu Y et al (2023) Corona enhancement combined with microvascular invasion for prognosis prediction of macrotrabecular-massive hepatocellular carcinoma subtype. Front Oncol 13:1138848

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Zhu Y, Weng S, Li Y et al (2021) A radiomics nomogram based on contrast-enhanced MRI for preoperative prediction of macrotrabecular-massive hepatocellular carcinoma. Abdom Radiol (NY) 46:3139–3148

    Article  PubMed  Google Scholar 

  20. American College of Radiology (ACR). Liver Imaging Reporting and Data System version 2018. ACR web site. Available via https://www.acr.org/Clinical-Resources/Reporting-and-Data-Systems/LI-RADS. Accessed April 28 2023

  21. Salameh JP, Bossuyt PM, McGrath TA et al (2020) Preferred reporting items for systematic review and meta-analysis of diagnostic test accuracy studies (PRISMA-DTA): explanation, elaboration, and checklist. BMJ 370:m2632

    Article  PubMed  Google Scholar 

  22. Whiting PF, Rutjes AW, Westwood ME et al (2011) QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med 155:529–536

    Article  PubMed  Google Scholar 

  23. Reitsma JB, Glas AS, Rutjes AW, Scholten RJ, Bossuyt PM, Zwinderman AH (2005) Bivariate analysis of sensitivity and specificity produces informative summary measures in diagnostic reviews. J Clin Epidemiol 58:982–990

    Article  PubMed  Google Scholar 

  24. Higgins JP, Thompson SG, Deeks JJ, Altman DG (2003) Measuring inconsistency in meta-analyses. BMJ 327:557–560

    Article  PubMed  PubMed Central  Google Scholar 

  25. McInnes MDF, Moher D, Thombs BD et al (2018) Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies: the PRISMA-DTA statement. JAMA 319:388–396

    Article  PubMed  Google Scholar 

  26. Cha H, Choi JY, Park YN et al (2023) Comparison of imaging findings of macrotrabecular-massive hepatocellular carcinoma using CT and gadoxetic acid-enhanced MRI. Eur Radiol 33:1364–1377

    Article  CAS  PubMed  Google Scholar 

  27. Fowler KJ, Bashir MR, Fetzer DT et al (2023) Universal liver imaging Lexicon: imaging atlas for research and clinical practice. Radiographics 43:e239001

    Article  PubMed  Google Scholar 

  28. Kim KR, Moon HE, Kim KW (2002) Hypoxia-induced angiogenesis in human hepatocellular carcinoma. J Mol Med (Berl) 80:703–714

    Article  CAS  PubMed  Google Scholar 

  29. Villa E, Critelli R, Lei B et al (2016) Neoangiogenesis-related genes are hallmarks of fast-growing hepatocellular carcinomas and worst survival Results from a prospective study. Gut 65:861–869

    Article  CAS  PubMed  Google Scholar 

  30. Renne SL, Woo HY, Allegra S et al (2020) Vessels encapsulating tumor clusters (VETC) is a powerful predictor of aggressive hepatocellular carcinoma. Hepatology 71:183–195

    Article  CAS  PubMed  Google Scholar 

  31. Feng Z, Li H, Zhao H et al (2021) Preoperative CT for characterization of aggressive macrotrabecular-massive subtype and vessels that encapsulate tumor clusters pattern in hepatocellular carcinoma. Radiology 300:219–229

    Article  PubMed  Google Scholar 

  32. Choi JY, Lee JM, Sirlin CB (2014) CT and MR imaging diagnosis and staging of hepatocellular carcinoma: part I. Development, growth, and spread: key pathologic and imaging aspects. Radiology 272:635–654

    Article  PubMed  Google Scholar 

  33. Yang H, Han P, Huang M et al (2022) The role of gadoxetic acid-enhanced MRI features for predicting microvascular invasion in patients with hepatocellular carcinoma. Abdom Radiol (NY) 47:948–956

    Article  PubMed  Google Scholar 

  34. 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  PubMed  Google Scholar 

  35. (2018) https://www.acr.org/-/media/ACR/Files/RADS/LI-RADS/LI-RADS-2018-Core.pdf?la=en. The American College of Radiology LI-RADS v2018 Core

  36. Fowler KJ, Burgoyne A, Fraum TJ et al (2021) Pathologic, molecular, and prognostic radiologic features of hepatocellular carcinoma. Radiographics 41:1611–1631

    Article  PubMed  Google Scholar 

  37. Ronot M, Chernyak V, Burgoyne A et al (2023) Imaging to predict prognosis in hepatocellular carcinoma: current and future perspectives. Radiology 307:e221429

    Article  PubMed  Google Scholar 

Download references

Funding

This research was funded in part through the NIH/NCI Cancer Center Support Grant P30 CA008748.

Author information

Authors and Affiliations

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

    Tae-Hyung Kim, Richard K. Do & Victoria Chernyak

  2. Department of Radiology, NYU Langone Health, New York, NY, USA

    Sungmin Woo

  3. Department of Radiology, Seoul National University Hospital, Seoul, South Korea

    Dong Ho Lee

  4. Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea

    Dong Ho Lee

Authors
  1. Tae-Hyung Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sungmin Woo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dong Ho Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Richard K. Do
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Victoria Chernyak
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Victoria Chernyak.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Victoria Chernyak, MD, MS.

Conflict of interest

Richard K. Do is currently consultant to Bayer Healthcare and to GE Healthcare and advisory board member to Ascelia Pharma.

Victoria Chernyak is currently consultant to Bayer Healthcare and to Giliad.

Victoria Chernyak is also a member of the European Radiology Editorial Board. They have not taken part in the review or selection process of this article.

Dong Ho Lee receives research grants from Canon medical systems.

All other authors have no conflict of interest to declare.

Statistics and biometry

One of the authors (Tae-Hyung Kim) has significant statistical expertise.

Informed consent

Written informed consent was not required for this study because it was systematic review and meta-analysis.

Ethical approval

Institutional Review Board approval was not required because it was systematic review and meta-analysis.

Study subjects or cohorts overlap

As this was a systematic review and meta-analysis, we utilized previously published articles to synthesize results.

Methodology

• multicentre study

Additional information

Publisher's Note

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

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 462 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kim, TH., Woo, S., Lee, D.H. et al. MRI imaging features for predicting macrotrabecular-massive subtype hepatocellular carcinoma: a systematic review and meta-analysis. Eur Radiol (2024). https://doi.org/10.1007/s00330-024-10671-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00330-024-10671-1

Keywords

Search

Navigation