Skip to main content
SpringerLink
Log in

Liver Imaging Reporting and Data System on CT and gadoxetic acid-enhanced MRI with diffusion-weighted imaging

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

Abstract

Objectives

To assess major imaging features of Liver Imaging Reporting and Data System (LI-RADS) on contrast-enhanced CT and gadoxetic acid-enhanced MRI and to estimate whether the combination of signal intensity favouring HCC on hepatobiliary phase (HBP) and diffusion-weighted images (DWI) can act as a major feature in LI-RADS.

Methods

Four hundred twenty one patients with 445 observations were included. Major features of LI-RADS on CT and MRI as well as HBP and DWI features were assessed. Diagnostic performances of LR-5 according to LI-RADS v2014 and modified LI-RADS which incorporate combination of HBP and DWI were assessed. Pairwise comparisons of the receiver operating characteristic (ROC) curves were performed.

Results

For HCCs, capsule appearance had the highest rate of discordance between CT and MRI (32.7%), followed by washout appearance (22.2%). Specificity (75%) of LR-5 of LI-RADS v2014 was lower than that (77.1–79.2%) of modified LI-RADS. Area under the ROC curve of modified LI-RADS (0.755–0.775) was not significantly different from that of LI-RADS v 2014 (0.709) (p > 0.05).

Conclusions

There were substantial discordances between CT and MRI for capsule and washout appearances in hepatic observations, and combination of gadoxetic acid-enhanced MRI and DWI might be able to be incorporated as a major feature of LI-RADS.

Key points

• Major imaging features of LI-RADS showed substantial discordances on CT and MRI.

• An observation may be categorized differently depending on used imaging exam.

• CT and MRI should both be performed for LR-3 and LR-4 observations.

• Combination of gadoxetic acid-enhanced MRI and DWI may be a major feature.

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
Fig. 5
Fig. 6

Similar content being viewed by others

Abbreviations

AUC:

Area under the ROC curve

CCC:

Cholangiocarcinoma

CHC:

Combined hepatocellular-cholangiocarcinomas

CI:

Confidence interval

CT:

Computed tomography

DWI:

Diffusion-weighted imaging

HBP:

Hepatobiliary phase

HCC:

Hepatocellular carcinoma

LI-RADS:

Imaging reporting and data system

LR-M:

Probably malignant, not specific for HCC

MRI:

Magnetic resonance imaging

ROC curve:

Receiver operating characteristic curve

US:

Ultrasound

References

  1. Mitchell DG, Bruix J, Sherman M, Sirlin CB (2015) LI‐RADS (Liver Imaging Reporting and Data System): summary, discussion, and consensus of the LI‐RADS Management Working Group and future directions. Hepatology 61:1056–1065

    Article  PubMed  Google Scholar 

  2. Shah A, Tang A, Santillan C, Sirlin C (2015) Cirrhotic liver: what's that nodule? The LI‐RADS approach. J Magn Reson Imaging 43:281–294

    Article  PubMed  Google Scholar 

  3. Sersté T, Barrau V, Ozenne V et al (2012) Accuracy and disagreement of computed tomography and magnetic resonance imaging for the diagnosis of small hepatocellular carcinoma and dysplastic nodules: role of biopsy. Hepatology 55:800–806

    Article  PubMed  Google Scholar 

  4. Corwin MT, Fananapazir G, Jin M, Lamba R, Bashir MR (2016) Differences in liver imaging and reporting data system categorization between MRI and CT. AJR Am J Roentgenol 206:307–312

    Article  PubMed  Google Scholar 

  5. Zhang Y-D, Zhu F-P, Xu X et al (2016) Liver Imaging Reporting and Data System: substantial discordance between CT and MR for imaging classification of hepatic nodules. Acad Radiol 23:344–352

    Article  PubMed  Google Scholar 

  6. Choi D, Kim P, Rhim H (2013) Planning ultrasound for percutaneous radiofrequency ablation to treat small (≤3 cm) hepatocellular carcinomas detected on CT or MRI: a multicenter prospective study to assess factors affecting ultrasound visibility. Ultrasound Med Biol 39:S38

    Article  Google Scholar 

  7. Hope TA, Fowler KJ, Sirlin CB et al (2015) Hepatobiliary agents and their role in LI-RADS. Abdom Imaging 40:613–625

    Article  PubMed  Google Scholar 

  8. American College of Radiology (2016) Liver Imaging Reporting and Data System. www.acr.org/Quality-Safety/Resources/LIRADS. Accessed 8 June 2016

  9. Sun HY, Lee JM, Shin CI et al (2010) Gadoxetic acid-enhanced magnetic resonance imaging for differentiating small hepatocellular carcinomas (≤2 cm in diameter) from arterial enhancing pseudolesions: special emphasis on hepatobiliary phase imaging. Invest Radiol 45:96–103

    Article  CAS  PubMed  Google Scholar 

  10. Neri E, Bali M, Ba-Ssalamah A et al (2016) ESGAR consensus statement on liver MR imaging and clinical use of liver-specific contrast agents. Eur Radiol 26:921–931

    Article  CAS  PubMed  Google Scholar 

  11. Merkle EM, Zech CJ, Bartolozzi C et al (2016) Consensus report from the 7th international forum for liver magnetic resonance imaging. Eur Radiol 26:674–682

    Article  PubMed  Google Scholar 

  12. Choi SH, Byun JH, Lim Y-S et al (2016) Diagnostic criteria for hepatocellular carcinoma ≤3cm with hepatocyte-specific contrast-enhanced magnetic resonance imaging. J Hepatol 64:1099–1107

    Article  PubMed  Google Scholar 

  13. Li X, Li C, Wang R, Ren J, Yang J, Zhang Y (2015) Combined application of gadoxetic acid disodium-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) in the diagnosis of chronic liver disease-induced hepatocellular carcinoma: a meta-analysis. PLoS One 10:e0144247

    Article  PubMed  PubMed Central  Google Scholar 

  14. American Association for the Study of Liver Diseases (2017) Hepatocellular carcinoma, management. http://www.aasld.org/publications/practice-guidelines-0. Accessed 5 Jan 2017

  15. Waller LP, Deshpande V, Pyrsopoulos N (2015) Hepatocellular carcinoma: a comprehensive review. World J Hepatol 7:2648

    Article  PubMed  PubMed Central  Google Scholar 

  16. An C, Park M-S, Kim D et al (2013) Added value of subtraction imaging in detecting arterial enhancement in small (<3 cm) hepatic nodules on dynamic contrast-enhanced MRI in patients at high risk of hepatocellular carcinoma. Eur Radiol 23:924–930

    Article  PubMed  Google Scholar 

  17. Yu J-S, Kim YH, Rofsky NM (2005) Dynamic subtraction magnetic resonance imaging of cirrhotic liver: assessment of high signal intensity lesions on nonenhanced T1-weighted images. J Comput Assist Tomogr 29:51–58

    Article  PubMed  Google Scholar 

  18. Kim R, Lee JM, Shin C-I et al (2016) Differentiation of intrahepatic mass-forming cholangiocarcinoma from hepatocellular carcinoma on gadoxetic acid-enhanced liver MR imaging. Eur Radiol 26:1808–1817

    Article  PubMed  Google Scholar 

  19. Choi J-Y, Lee J-M, 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  PubMed  PubMed Central  Google Scholar 

  20. Goodwin MD, Dobson JE, Sirlin CB, Lim BG, Stella DL (2011) Diagnostic challenges and pitfalls in MR imaging with hepatocyte-specific contrast agents. Radiographics 31:1547–1568

    Article  PubMed  Google Scholar 

  21. Joo I, Lee JM, Lee DH, Jeon JH, Han JK, Choi BI (2015) Noninvasive diagnosis of hepatocellular carcinoma on gadoxetic acid-enhanced MRI: can hypointensity on the hepatobiliary phase be used as an alternative to washout? Eur Radiol 25:2859–2868

    Article  PubMed  Google Scholar 

  22. Suh YJ, Kim M-J, Choi J-Y, Park YN, Park M-S, Kim KW (2011) Differentiation of hepatic hyperintense lesions seen on gadoxetic acid-enhanced hepatobiliary phase MRI. AJR Am J Roentgenol 197:W44–W52

    Article  PubMed  Google Scholar 

  23. Taouli B, Koh D-M (2009) Diffusion-weighted MR imaging of the liver 1. Radiology 254:47–66

    Article  Google Scholar 

  24. Hwang J, Kim YK, Kim JM, Lee WJ, Choi D, Hong SS (2014) Pretransplant diagnosis of hepatocellular carcinoma by gadoxetic acid-enhanced and diffusion‐weighted magnetic resonance imaging. Liver Transpl 20:1436–1446

    PubMed  Google Scholar 

  25. Choi J-Y, Lee J-M, 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  PubMed Central  Google Scholar 

  26. Kojiro M (2006) Pathomorphologic characteristics of early-stage small hepatocellular carcinoma. In: Pathology of hepatocellular carcinoma. Oxford, Blackwell, p 31–50

  27. Takayasu K, Arii S, Sakamoto M et al (2013) Clinical implication of hypovascular hepatocellular carcinoma studied in 4,474 patients with solitary tumour equal or less than 3 cm. Liver Int 33:762–770

    Article  CAS  PubMed  Google Scholar 

  28. Darnell A, Forner A, Rimola J et al (2015) Liver imaging reporting and data system with MR imaging: evaluation in nodules 20 mm or smaller detected in cirrhosis at screening US. Radiology 275:698–707

    Article  PubMed  Google Scholar 

  29. Zhang YD, Zhu FP, Xu X et al (2015) Classifying CT/MR findings in patients with suspicion of hepatocellular carcinoma: comparison of liver imaging reporting and data system and criteria‐free Likert scale reporting models. J Magn Reson Imaging 43:373–383

    Article  PubMed  Google Scholar 

  30. Chen N, Motosugi U, Morisaka H et al (2016) Added value of a gadoxetic acid-enhanced hepatocyte-phase image to the LI-RADS system for diagnosing hepatocellular carcinoma. Magn Reson Med Sci 15:49–59

    Article  PubMed  Google Scholar 

  31. Maximin S, Ganeshan DM, Shanbhogue AK et al (2014) Current update on combined hepatocellular-cholangiocarcinoma. Eur J Radiol Open 1:40–48

    Article  PubMed  PubMed Central  Google Scholar 

  32. Aoki K, Takayasu K, Kawano T et al (1993) Combined hepatocellular carcinoma and cholangiocarcinoma: clinical features and computed tomographic findings. Hepatology 18:1090–1095

    Article  CAS  PubMed  Google Scholar 

  33. Sanada Y, Shiozaki S, Aoki H, Takakura N, Yoshida K, Yamaguchi Y (2005) A clinical study of 11 cases of combined hepatocellular–cholangiocarcinoma: assessment of enhancement patterns on dynamics computed tomography before resection. Hepatol Res 32:185–195

    Article  PubMed  Google Scholar 

  34. Huppertz A, Haraida S, Kraus A et al (2005) Enhancement of focal liver lesions at gadoxetic acid–enhanced MR imaging: correlation with histopathologic findings and spiral CT—initial observations 1. Radiology 234:468–478

    Article  PubMed  Google Scholar 

  35. Huang B, Wu L, Lu X-Y et al (2016) Small intrahepatic cholangiocarcinoma and hepatocellular carcinoma in cirrhotic livers may share similar enhancement patterns at multiphase dynamic MR imaging. Radiology 281:150–157

    Article  PubMed  Google Scholar 

  36. Padhani AR, Liu G, Mu-Koh D et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Barral M, Taouli B, Guiu B et al (2014) Diffusion-weighted MR imaging of the pancreas: current status and recommendations. Radiology 274:45–63

    Article  Google Scholar 

Download references

Acknowledgements

The authors thank Seon Woo Kim, Ph.D. in statistics, Samsung Medical Center, Sungkyunkwan University School of Medicine for his advice with statistics.

Author information

Authors and Affiliations

  1. Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-Ro Gangnam-gu, Seoul, 06351, Republic of Korea

    Dong Ik Cha, Kyung Mi Jang, Seong Hyun Kim, Tae Wook Kang & Kyoung Doo Song

Authors
  1. Dong Ik Cha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kyung Mi Jang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Seong Hyun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tae Wook Kang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kyoung Doo Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Kyung Mi Jang.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Kyung Mi Jang.

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.

Funding

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

Statistics and biometry

Seon Woo Kim, Ph.D. in statistics, kindly provided statistical advice for this manuscript.

Ethical approval

Institutional review board approval was obtained.

Informed consent

Written informed consent was waived by the institutional review board.

Methodology

• retrospective

• diagnostic or prognostic study

• performed at one institution

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM 1

(DOCX 17 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cha, D.I., Jang, K.M., Kim, S.H. et al. Liver Imaging Reporting and Data System on CT and gadoxetic acid-enhanced MRI with diffusion-weighted imaging. Eur Radiol 27, 4394–4405 (2017). https://doi.org/10.1007/s00330-017-4804-1

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-017-4804-1

Keywords

Search

Navigation