European Radiology

, Volume 26, Issue 2, pp 539–546 | Cite as

The diagnostic efficacy of quantitative liver MR imaging with diffusion-weighted, SWI, and hepato-specific contrast-enhanced sequences in staging liver fibrosis—a multiparametric approach

  • Diana Feier
  • Csilla Balassy
  • Nina Bastati
  • Romana Fragner
  • Friedrich Wrba
  • Ahmed Ba-Ssalamah
Magnetic Resonance



To assess the diagnostic efficacy of multiparametric MRI using quantitative measurements of the apparent diffusion coefficient (ADC) of the liver parenchyma on diffusion-weighted imaging (DWI), signal intensity (SI) on susceptibility-weighted imaging (SWI), and gadoxetic acid-enhanced T1-weighted imaging during the hepatobiliary phase for the staging of liver fibrosis.

Materials and Methods

Seventy-seven patients underwent a 3T MRI examination, including DWI/SWI sequences and gadoxetic acid-enhanced T1-weighted MRI. Liver fibrosis according to liver biopsy was staged using the Metavir fibrosis score: F0 (n = 21, 27.3 %); F1 (n = 7, 9.1 %); F2 (n = 8, 10.4 %); F3 (n = 12, 15.6 %); and F4 (n = 29, 37.7 %). SI of the liver was defined using region-of-interest measurements to calculate the ADC values, the relative enhancement (RE) in the hepatobiliary phase, and the liver-to-muscle ratio (LMR) measurements for SWI.


The values of RE, LMR, and ADC measurements were statistically significantly different among the five fibrosis stages (p < 0.004). Combining the three parameters in a multiparametric approach, the AUC for detecting F1 stage or greater (≥ F1) was 94 %, for F2 or greater (≥F2) was 95 %, for F3 or greater (≥F3) was 90 %, and for stage F4 was 93 %.


Multiparametric MRI is an efficient non-invasive diagnostic tool for the staging of liver fibrosis.

Key Points

Multiparametric MRI has high accuracy in predicting moderate or greater liver fibrosis.

Relative enhancement post- gadoxetic acid is an independent predictor of liver fibrosis.

Liver SWI signal intensity and ADC values enhance the diagnostic ability.


Liver fibrosis Multiparametric MR imaging Staging Quantitative 



The scientific guarantor of this publication is Associate Professor Ahmed Ba-Ssalamah, MD. 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. The authors state that this work has not received any funding. One of the authors has significant statistical expertise. Institutional review board approval was obtained. Written informed consent was waived by the institutional review board.

Some study subjects or cohorts have been previously reported in the following: Balassy C, Feier D, Peck-Radosavljevic M, et al. Susceptibility-weighted MR Imaging in the Grading of Liver Fibrosis: A Feasibility Study. Radiology. 2014;270(1):149-58, and Feier D, Balassy C, Bastati N, et al. Liver Fibrosis: Histopathologic and Biochemical Influences on Diagnostic Efficacy of Hepatobiliary Contrast-enhanced MR Imaging in Staging. Radiology. 2013.

Methodology: retrospective, diagnostic study, performed at one institution.


  1. 1.
    Blachier M, Leleu H, Peck-Radosavljevic M et al (2013) The burden of liver disease in Europe: a review of available epidemiological data. J Hepatol 58:593–608PubMedCrossRefGoogle Scholar
  2. 2.
    Okazaki H, Ito K, Fujita T et al (2000) Discrimination of alcoholic from virus-induced cirrhosis on MR imaging. AJR Am J Roentgenol 175:1677–1681PubMedCrossRefGoogle Scholar
  3. 3.
    Rockey DC (2006) Hepatic fibrosis, stellate cells, and portal hypertension. Clin Liver Dis 10:459–479, vii–viii PubMedCrossRefGoogle Scholar
  4. 4.
    Cadranel JF, Rufat P, Degos F (2000) Practices of liver biopsy in France: results of a prospective nationwide survey. For the Group of Epidemiology of the French Association for the Study of the Liver (AFEF). Hepatology 32:477–481PubMedCrossRefGoogle Scholar
  5. 5.
    Wang Y, Ganger DR, Levitsky J et al (2011) Assessment of chronic hepatitis and fibrosis: comparison of MR elastography and diffusion-weighted imaging. AJR Am J Roentgenol 196:553–561PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Pasquinelli F, Belli G, Mazzoni LN et al (2012) MR-diffusion imaging in assessing chronic liver diseases: does a clinical role exist? Radiol Med 117:242–253PubMedCrossRefGoogle Scholar
  7. 7.
    Bonekamp S, Torbenson MS, Kamel IR (2011) Diffusion-weighted magnetic resonance imaging for the staging of liver fibrosis. J Clin Gastroenterol 45:885–892PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Hagiwara M, Rusinek H, Lee VS et al (2008) Advanced liver fibrosis: diagnosis with 3D whole-liver perfusion MR imaging—initial experience. Radiology 246:926–934PubMedCrossRefGoogle Scholar
  9. 9.
    Lim AK, Patel N, Eckersley RJ et al (2011) A comparison of 31P magnetic resonance spectroscopy and microbubble-enhanced ultrasound for characterizing hepatitis c-related liver disease. J Viral Hepat 18:e530–e534PubMedCrossRefGoogle Scholar
  10. 10.
    Wood JC (2011) Impact of iron assessment by MRI. Hematol Am Soc Hematol Educ Program 2011:443–450CrossRefGoogle Scholar
  11. 11.
    Nishie A, Asayama Y, Ishigami K et al (2012) MR prediction of liver fibrosis using a liver-specific contrast agent: superparamagnetic iron oxide versus Gd-EOB-DTPA. J Magn Reson Imaging 36:664–671PubMedCrossRefGoogle Scholar
  12. 12.
    Chen BB, Hsu CY, Yu CW et al (2012) Dynamic contrast-enhanced magnetic resonance imaging with Gd-EOB-DTPA for the evaluation of liver fibrosis in chronic hepatitis patients. Eur Radiol 22:171–180PubMedCrossRefGoogle Scholar
  13. 13.
    Motosugi U, Ichikawa T, Oguri M et al (2011) Staging liver fibrosis by using liver-enhancement ratio of gadoxetic acid-enhanced MR imaging: comparison with aspartate aminotransferase-to-platelet ratio index. Magn Reson Imaging 29:1047–1052PubMedCrossRefGoogle Scholar
  14. 14.
    Balassy C, Feier D, Peck-Radosavljevic M et al (2014) Susceptibility-weighted MR Imaging in the Grading of Liver Fibrosis: a Feasibility Study. Radiology 270:149–158PubMedCrossRefGoogle Scholar
  15. 15.
    Rockey DC, Caldwell SH, Goodman ZD et al (2009) Liver biopsy. Hepatology 49:1017–1044PubMedCrossRefGoogle Scholar
  16. 16.
    Dai Y, Zeng M, Li R et al (2011) Improving detection of siderotic nodules in cirrhotic liver with a multi-breath-hold susceptibility-weighted imaging technique. J Magn Reson Imaging 34:318–325PubMedCrossRefGoogle Scholar
  17. 17.
    DeLong ER, DeLong DM, Clarke-Pearson DL (1988) Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics 44:837–845PubMedCrossRefGoogle Scholar
  18. 18.
    Shiffman ML, Sterling RK, Contos M et al (2014) Long term changes in liver histology following treatment of chronic hepatitis C virus. Ann Hepatol 13:340–349PubMedGoogle Scholar
  19. 19.
    Taouli B, Koh DM (2010) Diffusion-weighted MR imaging of the liver. Radiology 254:47–66PubMedCrossRefGoogle Scholar
  20. 20.
    Aube C, Racineux PX, Lebigot J et al (2004) Diagnosis and quantification of hepatic fibrosis with diffusion weighted MR imaging: preliminary results. J Radiol 85:301–306PubMedCrossRefGoogle Scholar
  21. 21.
    Girometti R, Furlan A, Bazzocchi M et al (2007) Diffusion-weighted MRI in evaluating liver fibrosis: a feasibility study in cirrhotic patients. Radiol Med 112:394–408PubMedCrossRefGoogle Scholar
  22. 22.
    Lewin M, Poujol-Robert A, Boelle PY et al (2007) Diffusion-weighted magnetic resonance imaging for the assessment of fibrosis in chronic hepatitis C. Hepatology 46:658–665PubMedCrossRefGoogle Scholar
  23. 23.
    Ichikawa T, Haradome H, Hachiya J et al (1999) Diffusion-weighted MR imaging with single-shot echo-planar imaging in the upper abdomen: preliminary clinical experience in 61 patients. Abdom Imaging 24:456–461PubMedCrossRefGoogle Scholar
  24. 24.
    Chen X, Qin L, Pan D et al (2014) Liver diffusion-weighted MR imaging: reproducibility comparison of ADC measurements obtained with multiple breath-hold, free-breathing, respiratory-triggered, and navigator-triggered techniques. Radiology 271:113–125PubMedCrossRefGoogle Scholar
  25. 25.
    Kim YK, Lee MW, Lee WJ et al (2012) Diagnostic accuracy and sensitivity of diffusion-weighted and of gadoxetic acid-enhanced 3-T MR imaging alone or in combination in the detection of small liver metastasis (</= 1.5 cm in diameter). Invest Radiol 47:159–166PubMedGoogle Scholar
  26. 26.
    Choi JS, Kim MJ, Choi JY et al (2010) Diffusion-weighted MR imaging of liver on 3.0-Tesla system: effect of intravenous administration of gadoxetic acid disodium. Eur Radiol 20:1052–1060PubMedCrossRefGoogle Scholar
  27. 27.
    Chen W, DelProposto Z, Wu D et al (2012) Improved siderotic nodule detection in cirrhosis with susceptibility-weighted magnetic resonance imaging: a prospective study. PLoS One 7:e36454PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Ridolfi F, Abbattista T, Busilacchi P, Brunelli E (2012) Contrast-enhanced ultrasound evaluation of hepatic microvascular changes in liver diseases. World J Gastroenterol 18:5225–5230PubMedPubMedCentralGoogle Scholar
  29. 29.
    Tamada T, Ito K, Higaki A et al (2011) Gd-EOB-DTPA-enhanced MR imaging: evaluation of hepatic enhancement effects in normal and cirrhotic livers. Eur J Radiol 80:e311–e316PubMedCrossRefGoogle Scholar
  30. 30.
    Feier D, Balassy C, Bastati N et al (2013) Liver fibrosis: histopathologic and biochemical influences on diagnostic efficacy of hepatobiliary contrast-enhanced MR imaging in staging. Radiology 269:460–468PubMedCrossRefGoogle Scholar
  31. 31.
    Tsuda N, Matsui O (2010) Cirrhotic rat liver: reference to transporter activity and morphologic changes in bile canaliculi—gadoxetic acid-enhanced MR imaging. Radiology 256:767–773PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2015

Authors and Affiliations

  • Diana Feier
    • 1
    • 2
  • Csilla Balassy
    • 1
  • Nina Bastati
    • 1
  • Romana Fragner
    • 1
  • Friedrich Wrba
    • 3
  • Ahmed Ba-Ssalamah
    • 1
  1. 1.Department of Biomedical Imaging and Image-guided TherapyMedical University of Vienna, General Hospital of Vienna (AKH)ViennaAustria
  2. 2.Department of RadiologyIuliu Hatieganu University of Medicine and Pharmacy, Cluj-Napoca, Emergency County HospitalCluj-NapocaRomania
  3. 3.Department of PathologyMedical University of Vienna, General Hospital of Vienna (AKH)ViennaAustria

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