European Radiology

, Volume 22, Issue 10, pp 2169–2177 | Cite as

MR elastography of liver tumours: value of viscoelastic properties for tumour characterisation

  • Philippe Garteiser
  • Sabrina Doblas
  • Jean-Luc Daire
  • Mathilde Wagner
  • Helena Leitao
  • Valérie Vilgrain
  • Ralph Sinkus
  • Bernard E. Van Beers



To assess the value of the viscoelastic parameters in the characterisation of liver tumours at MR elastography.

Patients and methods

Ninety-four patients with liver tumours >1 cm prospectively underwent MR elastography using 50-Hz mechanical waves and a full three-directional motion-sensitive sequence. The model-free viscoelastic parameters (the complex shear modulus and its real and imaginary parts, i.e. the storage and loss moduli) were calculated in 72 lesions after exclusion of cystic, treated or histopathologically undetermined tumours.


We observed higher absolute shear modulus and loss modulus in malignant versus benign tumours (3.38 ± 0.26 versus 2.41 ± 0.15 kPa, P < 0.01 and 2.25 ± 0.26 versus 1.05 ± 0.13 kPa, P < 0.001, respectively). Moreover, the loss modulus of hepatocellular carcinomas was significantly higher than in benign hepatocellular tumours. The storage modulus did not differ significantly between malignant and benign tumours. The area under the receiver-operating characteristic curve of loss modulus was significantly larger than that of the absolute shear modulus and storage modulus when comparing malignant and benign lesions.


The increased loss modulus is a better discriminator between benign and malignant tumours than the increased storage modulus or absolute value of the shear modulus.

Key Points

Magnetic Resonance elastography is a new method of assessing the liver.

Increased loss modulus is an indicator of malignancy in hepatic tumours.

Loss modulus is a better discriminator than absolute shear modulus values.

The viscoelastic properties of lesions offer promise for characterising liver tumours.


MR elastography Liver neoplasms Hepatocellular carcinoma Visco-elasticity Stiffness 



Absolute value of the complex-valued shear modulus


Storage modulus


Loss modulus


Hepatocellular carcinoma


Focal nodular hyperplasia


Intraclass correlation coefficient


Magnetic resonance


Region of interest


Receiver-operating characteristics


Area under the receiver-operating characteristic curve

Supplementary material

330_2012_2474_MOESM1_ESM.pptx (1.1 mb)
ESM Fig. 5 T2-weighted images, loss modulus (G″) maps and time-resolved maps of displacement in the horizontal direction of metastasis (A, D and G), HCC (B, E and H) and FNH (C, F and I). The loss modulus of HCC (2.89 kPa) is higher than that of the FNH (0.49 kPa) (PPTX 1081 kb)


  1. 1.
    Taouli B, Losada M, Holland A, Krinsky G (2004) Magnetic resonance imaging of hepatocellular carcinoma. Gastroenterology 127:S144–152PubMedCrossRefGoogle Scholar
  2. 2.
    Bahirwani R, Reddy KR (2008) Review article: the evaluation of solitary liver masses. Aliment Pharmacol Ther 28:953–965PubMedGoogle Scholar
  3. 3.
    Bruegel M, Holzapfel K, Gaa J et al (2008) Characterization of focal liver lesions by ADC measurements using a respiratory triggered diffusion-weighted single-shot echo-planar MR imaging technique. Eur Radiol 18:477–485PubMedCrossRefGoogle Scholar
  4. 4.
    Silva AC, Evans JM, McCullough AE, Jatoi MA, Vargas HE, Hara AK (2009) MR imaging of hypervascular liver masses: a review of current techniques. Radiographics 29:385–402PubMedCrossRefGoogle Scholar
  5. 5.
    Kudo M (2010) Will Gd-EOB-MRI change the diagnostic algorithm in hepatocellular carcinoma? Oncology 78:87–93PubMedCrossRefGoogle Scholar
  6. 6.
    Bruix J, Sherman M (2005) Management of hepatocellular carcinoma. Hepatology 42:1208–1236PubMedCrossRefGoogle Scholar
  7. 7.
    Muthupillai R, Lomas DJ, Rossman PJ, Greenleaf JF, Manduca A, Ehman RL (1995) Magnetic resonance elastography by direct visualization of propagating acoustic strain waves. Science 269:1854–1857PubMedCrossRefGoogle Scholar
  8. 8.
    Sinkus R, Tanter M, Xydeas T, Catheline S, Bercoff J, Fink M (2005) Viscoelastic shear properties of in vivo breast lesions measured by MR elastography. Magn Reson Imaging 23:159–165PubMedCrossRefGoogle Scholar
  9. 9.
    Asbach P, Klatt D, Schlosser B et al (2010) Viscoelasticity-based staging of hepatic fibrosis with multifrequency MR elastography. Radiology 257:80–86PubMedCrossRefGoogle Scholar
  10. 10.
    Sinkus R, Lorenzen J, Schrader D, Lorenzen M, Dargatz M, Holz D (2000) High-resolution tensor MR elastography for breast tumour detection. Phys Med Biol 45:1649–1664PubMedCrossRefGoogle Scholar
  11. 11.
    Huwart L, Peeters F, Sinkus R et al (2006) Liver fibrosis: non-invasive assessment with MR elastography. NMR Biomed 19:173–179PubMedCrossRefGoogle Scholar
  12. 12.
    Yin M, Talwalkar JA, Glaser KJ et al (2007) Assessment of hepatic fibrosis with magnetic resonance elastography. Clin Gastroenterol Hepatol 5:e1202CrossRefGoogle Scholar
  13. 13.
    Huwart L, Sempoux C, Vicaut E et al (2008) Magnetic resonance elastography for the noninvasive staging of liver fibrosis. Gastroenterology 135:32–40PubMedCrossRefGoogle Scholar
  14. 14.
    Venkatesh SK, Yin M, Glockner JF et al (2008) MR elastography of liver tumors: preliminary results. AJR Am J Roentgenol 190:1534–1540PubMedCrossRefGoogle Scholar
  15. 15.
    Manduca A, Oliphant TE, Dresner MA et al (2001) Magnetic resonance elastography: non-invasive mapping of tissue elasticity. Med Image Anal 5:237–254PubMedCrossRefGoogle Scholar
  16. 16.
    Mariappan YK, Glaser KJ, Ehman RL (2010) Magnetic resonance elastography: a review. Clin Anat 23:497–511PubMedCrossRefGoogle Scholar
  17. 17.
    Bavu E, Gennisson JL, Couade M et al (2011) Noninvasive in vivo liver fibrosis evaluation using supersonic shear imaging: a clinical study on 113 hepatitis C virus patients. Ultrasound Med Biol 37:1361–1373PubMedCrossRefGoogle Scholar
  18. 18.
    Ronot M, Bahrami S, Calderaro J et al (2011) Hepatocellular adenomas: accuracy of magnetic resonance imaging and liver biopsy in subtype classification. Hepatology 53:1182–1191PubMedCrossRefGoogle Scholar
  19. 19.
    Bruix J, Sherman M, Llovet JM et al (2001) Clinical management of hepatocellular carcinoma. Conclusions of the Barcelona-2000 EASL conference. J Hepatol 35:421–430PubMedCrossRefGoogle Scholar
  20. 20.
    Bruix J, Sherman M (2011) Management of hepatocellular carcinoma: an update. Hepatology 53:1020–1022PubMedCrossRefGoogle Scholar
  21. 21.
    Sinkus R, Tanter M, Catheline S et al (2005) Imaging anisotropic and viscous properties of breast tissue by magnetic resonance-elastography. Magn Reson Med 53:372–387PubMedCrossRefGoogle Scholar
  22. 22.
    Padhani AR, Liu G, Koh DM et al (2009) Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia 11:102–125PubMedGoogle Scholar
  23. 23.
    Zweig MH, Campbell G (1993) Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin Chem 39:561–577PubMedGoogle Scholar
  24. 24.
    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
  25. 25.
    International Working Party (1995) Terminology of nodular hepatocellular lesions. Hepatology 22:983–993Google Scholar
  26. 26.
    Fahey BJ, Nelson RC, Bradway DP, Hsu SJ, Dumont DM, Trahey GE (2008) In vivo visualization of abdominal malignancies with acoustic radiation force elastography. Phys Med Biol 53:279–293PubMedCrossRefGoogle Scholar
  27. 27.
    Cho SH, Lee JY, Han JK, Choi BI (2010) Acoustic radiation force impulse elastography for the evaluation of focal solid hepatic lesions: preliminary findings. Ultrasound Med Biol 36:202–208PubMedCrossRefGoogle Scholar
  28. 28.
    Tseng Y, Fedorov E, McCaffery JM, Almo SC, Wirtz D (2001) Micromechanics and ultrastructure of actin filament networks crosslinked by human fascin: a comparison with alpha-actinin. J Mol Biol 310:351–366PubMedCrossRefGoogle Scholar
  29. 29.
    Giancotti FG, Ruoslahti E (1999) Integrin signaling. Science 285:1028–1032PubMedCrossRefGoogle Scholar
  30. 30.
    Weaver VM, Roskelley CD (1997) Extracellular matrix: the central regulator of cell and tissue homeostasis. Trends Cell Biol 7:40–42PubMedCrossRefGoogle Scholar
  31. 31.
    Bilston LE (2002) The effect of perfusion on soft tissue mechanical properties: a computational model. Comput Methods Biomech Biomed Engin 5:283–290PubMedCrossRefGoogle Scholar
  32. 32.
    Fukumura D, Jain RK (2007) Tumor microvasculature and microenvironment: targets for anti-angiogenesis and normalization. Microvasc Res 74:72–84PubMedCrossRefGoogle Scholar
  33. 33.
    Gialeli C, Theocharis AD, Karamanos NK (2011) Roles of matrix metalloproteinases in cancer progression and their pharmacological targeting. FEBS J 278:16–27PubMedCrossRefGoogle Scholar
  34. 34.
    Siegmann KC, Xydeas T, Sinkus R, Kraemer B, Vogel U, Claussen CD (2010) Diagnostic value of MR elastography in addition to contrast-enhanced MR imaging of the breast-initial clinical results. Eur Radiol 20:318–325PubMedCrossRefGoogle Scholar
  35. 35.
    Garteiser P, Doblas S, Daire J-L, et al (2011) Combining biomechanical and diffusion data into a composite biomarker for the determination of hepatic tumor malignancy. Proceedings of the 2011 conference of the European Society of Magnetic Resonance in Medicine and Biology 28Google Scholar
  36. 36.
    Mariappan YK, Rossman PJ, Glaser KJ, Manduca A, Ehman RL (2009) Magnetic resonance elastography with a phased-array acoustic driver system. Magn Reson Med 61:678–685PubMedCrossRefGoogle Scholar
  37. 37.
    Asbach P, Klatt D, Hamhaber U et al (2008) Assessment of liver viscoelasticity using multifrequency MR elastography. Magn Reson Med 60:373–379PubMedCrossRefGoogle Scholar
  38. 38.
    Berry GP, Bamber JC, Armstrong CG, Miller NR, Barbone PE (2006) Towards an acoustic model-based poroelastic imaging method: I. Theoretical foundation. Ultrasound Med Biol 32:547–567PubMedCrossRefGoogle Scholar
  39. 39.
    Berry GP, Bamber JC, Miller NR, Barbone PE, Bush NL, Armstrong CG (2006) Towards an acoustic model-based poroelastic imaging method: II. experimental investigation. Ultrasound Med Biol 32:1869–1885PubMedCrossRefGoogle Scholar
  40. 40.
    Klatt D, Hamhaber U, Asbach P, Braun J, Sack I (2007) Noninvasive assessment of the rheological behavior of human organs using multifrequency MR elastography: a study of brain and liver viscoelasticity. Phys Med Biol 52:7281–7294PubMedCrossRefGoogle Scholar
  41. 41.
    Konofagou EE, Harrigan TP, Ophir J, Krouskop TA (2001) Poroelastography: imaging the poroelastic properties of tissues. Ultrasound Med Biol 27:1387–1397PubMedCrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2012

Authors and Affiliations

  • Philippe Garteiser
    • 1
  • Sabrina Doblas
    • 1
  • Jean-Luc Daire
    • 1
  • Mathilde Wagner
    • 1
  • Helena Leitao
    • 2
  • Valérie Vilgrain
    • 1
  • Ralph Sinkus
    • 1
  • Bernard E. Van Beers
    • 1
  1. 1.Department of RadiologyUniversity Paris Diderot, Sorbonne Paris Cité, INSERM UMR 773, University Hospitals Paris Nord Val de SeineClichy CedexFrance
  2. 2.Department of RadiologyHospital of the University of CoimbraCoimbraPortugal

Personalised recommendations