Skip to main content
SpringerLink
Log in

Intravoxel incoherent motion model-based liver lesion characterisation from three b-value diffusion-weighted MRI

  • Magnetic Resonance
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objective

To evaluate intravoxel incoherent motion (IVIM) model-based liver lesion characterisation from three b-value diffusion-weighted imaging (DWI).

Methods

The 1.5-T DWI data from a respiratory gated spin-echo echo-planar magnetic resonance imaging sequence (b = 0, 50, 800 s/mm2) were retrospectively analysed in 38 patients with different liver lesions. Conventional apparent diffusion coefficient ADC = ADC(0,800) as well as IVIM-based parameters D′ = ADC(50,800), ADC_low = ADC(0,50), and f′ were calculated voxel-wise. Sixty-one regions of interest in hepatocellular carcinomas (HCCs, n = 24), haemangiomas (HEMs, n = 11), focal nodular hyperplasias (FNHs, n = 11), and healthy liver tissue (REFs, n = 15) were analysed. Group differences were investigated using Student’s t-test and receiver-operating characteristic (ROC) analysis.

Results

Mean values ± standard deviations of ADC, D′, ADC_low (in 10-5 mm2/s), and f′ (in %) for REFs/FNHs/HEMs/HCCs were 130 ± 11/143 ± 27/168 ± 16/113 ± 25, 104 ± 12/123 ± 25/162 ± 18/102 ± 23, 518 ± 66/437 ± 97/268 ± 69/283 ± 120, and 18 ± 3/14 ± 4/6 ± 3/9 ± 5, respectively. Differences between lesions and REFs were more significant for IVIM-based parameters than for conventional ADC. ROC analysis showed the best discriminability between HCCs and FNHs for ADC_low and f′ and between HEMs and FNHs or HCCs for D′.

Conclusion

Three instead of two b-value DWI enables a numerically stable and voxel-wise IVIM-based analysis for improved liver lesion characterisation with tolerable acquisition time.

Key Points

• Quantitative analysis of diffusion-weighted MRI helps liver lesion characterisation.

• Analysis of intravoxel incoherent motion is superior to apparent diffusion coefficient determination.

• Only three b-values enable separation of diffusion and microcirculation effects.

• The method presented is numerically stable, with voxel-wise results and short acquisition times.

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

    PubMed  CAS  Google Scholar 

  2. Taouli B, Koh DM (2010) Diffusion-weighted MR imaging of the liver. Radiology 254:47–66

    Article  PubMed  Google Scholar 

  3. Taouli B (2012) Diffusion-weighted MR imaging for liver lesion characterization: A critical look. Radiology 262:378–380

    Article  PubMed  Google Scholar 

  4. Sinkus R, Van Beers BE, Vilgrain V, DeSouza N, Waterton JC (2012) Apparent diffusion coefficient from magnetic resonance imaging as a biomarker in oncology drug development. Eur J Cancer 48:425–431

    Article  PubMed  CAS  Google Scholar 

  5. Takahara T, Kwee TC (2012) Low b-value diffusion-weighted imaging: Emerging applications in the body. J Magn Reson Imaging 35:1266–1273

    Article  PubMed  Google Scholar 

  6. Kwee TC, Takahara T (2011) Diffusion-weighted MRI for detecting liver metastases: Importance of the b-value. Eur Radiol 21:150

    Article  PubMed  Google Scholar 

  7. Goshima S, Kanematsu M, Kondo H et al (2008) Diffusion-weighted imaging of the liver: Optimizing b value for the detection and characterization of benign and malignant hepatic lesions. J Magn Reson Imaging 28:691–697

    Article  PubMed  Google Scholar 

  8. Parikh T, Drew SJ, Lee VS et al (2008) Focal liver lesion detection and characterization with diffusion-weighted MR imaging: Comparison with standard breath-hold T2-weighted imaging. Radiology 246:812–822

    Article  PubMed  Google Scholar 

  9. Gourtsoyianni S, Papanikolaou N, Yarmenitis S, Maris T, Karantanas A, Gourtsoyiannis N (2008) Respiratory gated diffusion-weighted imaging of the liver: value of apparent diffusion coefficient measurements in the differentiation between most commonly encountered benign and malignant focal liver lesions. Eur Radiol 18:486–492

    Article  PubMed  Google Scholar 

  10. Coenegrachts K, Delanote J, Ter BL et al (2007) Improved focal liver lesion detection: comparison of single-shot diffusion-weighted echoplanar and single-shot T2 weighted turbo spin echo techniques. Br J Radiol 80:524–531

    Article  PubMed  CAS  Google Scholar 

  11. Koh DM, Collins DJ, Orton MR (2011) Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. AJR Am J Roentgenol 196:1351–1361

    Article  PubMed  Google Scholar 

  12. Guiu B, Cercueil JP (2011) Liver diffusion-weighted MR imaging: The tower of Babel? Eur Radiol 21:463–467

    Article  PubMed  Google Scholar 

  13. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 168:497–505

    PubMed  Google Scholar 

  14. Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M (1986) MR imaging of intravoxel incoherent motions: Application to diffusion and perfusion in neurologic disorders. Radiology 161:401–407

    PubMed  Google Scholar 

  15. Yamada I, Aung W, Himeno Y, Nakagawa T, Shibuya H (1999) Diffusion coefficients in abdominal organs and hepatic lesions: Evaluation with intravoxel incoherent motion echo-planar MR imaging. Radiology 210:617–623

    PubMed  CAS  Google Scholar 

  16. Le Bihan D (2008) Intravoxel incoherent motion perfusion MR imaging: A wake-up call. Radiology 249:748–752

    Article  PubMed  Google Scholar 

  17. Dyvorne HA, Galea N, Nevers T et al (2013) Diffusion-weighted imaging of the liver with multiple b values: Effect of diffusion gradient polarity and breathing acquisition on image quality and intravoxel incoherent motion parameters—a pilot study. Radiology 266:920–929

    Google Scholar 

  18. Andreou A, Koh DM, Collins DJ et al (2013) Measurement reproducibility of perfusion fraction and pseudodiffusion coefficient derived by intravoxel incoherent motion diffusion-weighted MR imaging in normal liver and metastases. Eur Radiol 23:428–434

    Article  PubMed  CAS  Google Scholar 

  19. Leitao HS, Doblas S, D’Assignies G et al (2013) Fat deposition decreases diffusion parameters at MRI: a study in phantoms and patients with liver steatosis. Eur Radiol 23:461–467

    Article  PubMed  Google Scholar 

  20. Guiu B, Petit JM, Capitan V et al (2012) Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: A 3.0-T MR study. Radiology 265:96–103

    Article  PubMed  Google Scholar 

  21. Lee JT, Liau J, Murphy P, Schroeder ME, Sirlin CB, Bydder M (2012) Cross-sectional investigation of correlation between hepatic steatosis and IVIM perfusion on MR imaging. Magn Reson Imaging 30:572–578

    Article  PubMed  Google Scholar 

  22. Dijkstra H, Baron P, Kappert P, Oudkerk M, Sijens PE (2012) Effects of microperfusion in hepatic diffusion weighted imaging. Eur Radiol 22:891–899

    Article  PubMed  Google Scholar 

  23. Lewin M, Arrive L, Lacombe C et al (2010) Diffusion-weighted MR imaging of liver pathology: Principles and clinical applications. J Radiol 91:11–26

    Article  PubMed  CAS  Google Scholar 

  24. Luciani A, Vignaud A, Cavet M et al (2008) Liver cirrhosis: intravoxel incoherent motion MR imaging–pilot study. Radiology 249:891–899

    Article  PubMed  Google Scholar 

  25. Patel J, Sigmund EE, Rusinek H, Oei M, Babb JS, Taouli B (2010) Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast-enhanced MRI alone and in combination: preliminary experience. J Magn Reson Imaging 31:589–600

    Article  PubMed  Google Scholar 

  26. Bruix J, Sherman M (2011) Management of hepatocellular carcinoma: An update. Hepatology 53:1020–1022

    Article  PubMed  Google Scholar 

  27. Steudel A, Träber F, Reiser M (1993) Hepatic tumors: relaxometry and quantitative tissue characterization with magnetic resonance imaging. Frontiers Eur Radiol 9:45–61

    Article  Google Scholar 

  28. Stanisz GJ, Odrobina EE, Pun J et al (2005) T1, T2 relaxation and magnetization transfer in tissue at 3T. Magn Reson Med 54:507–512

    Article  PubMed  Google Scholar 

  29. Lewin M, Fartoux L, Vignaud A, Arrive L, Menu Y, Rosmorduc O (2011) The diffusion-weighted imaging perfusion fraction f is a potential marker of sorafenib treatment in advanced hepatocellular carcinoma: A pilot study. Eur Radiol 21:281–290

    Article  PubMed  Google Scholar 

  30. Lemke A, Stieltjes B, Schad LR, Laun FB (2011) Toward an optimal distribution of b values for intravoxel incoherent motion imaging. Magn Reson Imaging 29:766–776

    Article  PubMed  Google Scholar 

  31. Cho GY, Kim S, Jensen JH, Storey P, Sodickson DK, Sigmund EE (2012) A versatile flow phantom for intravoxel incoherent motion MRI. Magn Reson Med 67:1710–1720

    Article  PubMed  Google Scholar 

  32. Koh DM, Blackledge M, Collins DJ et al (2009) Reproducibility and changes in the apparent diffusion coefficients of solid tumours treated with combretastatin A4 phosphate and bevacizumab in a two-centre phase I clinical trial. Eur Radiol 19:2728–2738

    Article  PubMed  Google Scholar 

  33. Coenegrachts K, Delanote J, Ter BL et al (2009) Evaluation of true diffusion, perfusion factor, and apparent diffusion coefficient in non-necrotic liver metastases and uncomplicated liver hemangiomas using black-blood echo planar imaging. Eur J Radiol 69:131–138

    Article  PubMed  Google Scholar 

  34. Schraml C, Schwenzer NF, Martirosian P et al (2009) Diffusion-weighted MRI of advanced hepatocellular carcinoma during sorafenib treatment: initial results. AJR Am J Roentgenol 193:W301–W307

    Article  PubMed  Google Scholar 

  35. 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 18:477–485

    Article  PubMed  Google Scholar 

  36. Moteki T, Horikoshi H (2006) Evaluation of hepatic lesions and hepatic parenchyma using diffusion-weighted echo-planar MR with three values of gradient b-factor. J Magn Reson Imaging 24:637–645

    Article  PubMed  Google Scholar 

  37. Aoyagi T, Shuto K, Okazumi S et al (2012) Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis. Eur Radiol 22:1172–1177

    Article  PubMed  Google Scholar 

  38. Le Bihan D, Turner R (1992) The capillary network: A link between IVIM and classical perfusion. Magn Reson Med 27:171–178

    Article  PubMed  Google Scholar 

  39. Duong TQ, Kim SG (2000) In vivo MR measurements of regional arterial and venous blood volume fractions in intact rat brain. Magn Reson Med 43:393–402

    Article  PubMed  CAS  Google Scholar 

  40. Coenegrachts K (2009) Magnetic resonance imaging of the liver: New imaging strategies for evaluating focal liver lesions. World J Radiol 1:72–85

    Article  PubMed  Google Scholar 

  41. Ichikawa T, Haradome H, Hachiya J, Nitatori T, Araki T (1998) Diffusion-weighted MR imaging with a single-shot echoplanar sequence: Detection and characterization of focal hepatic lesions. AJR Am J Roentgenol 170:397–402

    Article  PubMed  CAS  Google Scholar 

  42. Xing D, Papadakis NG, Huang CL, Lee VM, Carpenter TA, Hall LD (1997) Optimised diffusion-weighting for measurement of apparent diffusion coefficient (ADC) in human brain. Magn Reson Imaging 15:771–784

    Article  PubMed  CAS  Google Scholar 

  43. Lemke A, Laun FB, Simon D, Stieltjes B, Schad LR (2010) An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen. Magn Reson Med 64:1580–1585

    Article  PubMed  Google Scholar 

  44. Kartalis N, Loizou L, Edsborg N, Segersvard R, Albiin N (2012) Optimising diffusion-weighted MR imaging for demonstrating pancreatic cancer: A comparison of respiratory-triggered, free-breathing and breath-hold techniques. Eur Radiol 22:2186–2192

    Article  PubMed  Google Scholar 

  45. Taouli B, Sandberg A, Stemmer A et al (2009) Diffusion-weighted imaging of the liver: Comparison of navigator triggered and breathhold acquisitions. J Magn Reson Imaging 30:561–568

    Article  PubMed  Google Scholar 

  46. Kwee TC, Takahara T, Niwa T et al (2009) Influence of cardiac motion on diffusion-weighted magnetic resonance imaging of the liver. MAGMA 22:319–325

    Article  PubMed  CAS  Google Scholar 

  47. Nasu K, Kuroki Y, Sekiguchi R, Kazama T, Nakajima H (2006) Measurement of the apparent diffusion coefficient in the liver: Is it a reliable index for hepatic disease diagnosis? Radiat Med 24:438–444

    Article  PubMed  CAS  Google Scholar 

  48. Mürtz P, Flacke S, Träber F, van den Brink JS, Gieseke J, Schild HH (2002) Abdomen: diffusion-weighted MR imaging with pulse-triggered single-shot sequences. Radiology 224:258–264

    Article  PubMed  Google Scholar 

  49. Hollingsworth KG, Lomas DJ (2006) Influence of perfusion on hepatic MR diffusion measurement. NMR Biomed 19:231–235

    Article  PubMed  CAS  Google Scholar 

  50. Bilgili MY (2012) Reproducibility of apparent diffusion coefficients measurements in diffusion-weighted MRI of the abdomen with different b values. Eur J Radiol 81:2066–2068

    Article  PubMed  Google Scholar 

  51. Rosenkrantz AB, Oei M, Babb JS, Niver BE, Taouli B (2011) Diffusion-weighted imaging of the abdomen at 3.0 Tesla: Image quality and apparent diffusion coefficient reproducibility compared with 1.5 Tesla. J Magn Reson Imaging 33:128–135

    Article  PubMed  Google Scholar 

  52. Braithwaite AC, Dale BM, Boll DT, Merkle EM (2009) Short- and midterm reproducibility of apparent diffusion coefficient measurements at 3.0-T diffusion-weighted imaging of the abdomen. Radiology 250:459–465

    Article  PubMed  Google Scholar 

  53. Kwee TC, Takahara T, Koh DM, Nievelstein RA, Luijten PR (2008) Comparison and reproducibility of ADC measurements in breathhold, respiratory triggered, and free-breathing diffusion-weighted MR imaging of the liver. J Magn Reson Imaging 28:1141–1148

    Article  PubMed  Google Scholar 

  54. Kim SY, Soo LS, Bumwoo P et al (2012) Reproducibility of measurement of apparent diffusion coefficients of malignant hepatic tumors: Effect of DWI techniques and calculation methods. J Magn Reson Imaging 36:1131–1138

    Article  PubMed  Google Scholar 

  55. Kim SY, Lee SS, Byun JH et al (2010) Malignant hepatic tumors: short-term reproducibility of apparent diffusion coefficients with breath-hold and respiratory-triggered diffusion-weighted MR imaging. Radiology 255:815–823

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Radiology, University of Bonn, Bonn, Germany

    A.-H. Penner, A. M. Sprinkart, G. M. Kukuk, J. Gieseke, H. H. Schild, W. A. Willinek & P. Mürtz

  2. Institute of Medical Engineering, Ruhr-University Bochum, Bochum, Germany

    A. M. Sprinkart

  3. Department of Pathology, University of Bonn, Bonn, Germany

    I. Gütgemann

  4. Philips Healthcare, Best, The Netherlands

    J. Gieseke

  5. Radiologische Klinik der Universität Bonn, Sigmund-Freud-Straße 25, 53105, Bonn, Germany

    P. Mürtz

Authors
  1. A.-H. Penner
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. A. M. Sprinkart
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. M. Kukuk
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. I. Gütgemann
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. J. Gieseke
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. H. H. Schild
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. W. A. Willinek
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. P. Mürtz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to P. Mürtz.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Penner, AH., Sprinkart, A.M., Kukuk, G.M. et al. Intravoxel incoherent motion model-based liver lesion characterisation from three b-value diffusion-weighted MRI. Eur Radiol 23, 2773–2783 (2013). https://doi.org/10.1007/s00330-013-2869-z

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00330-013-2869-z

Keywords

Search

Navigation