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Comparison between modified Dixon MRI techniques, MR spectroscopic relaxometry, and different histologic quantification methods in the assessment of hepatic steatosis

  • Hepatobiliary-Pancreas
  • Published:
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Abstract

Objectives

To compare systematically quantitative MRI, MR spectroscopy (MRS), and different histological methods for liver fat quantification in order to identify possible incongruities.

Methods

Fifty-nine consecutive patients with liver disorders were examined on a 3 T MRI system. Quantitative MRI was performed using a dual- and a six-echo variant of the modified Dixon (mDixon) sequence, calculating proton density fat fraction (PDFF) maps, in addition to single-voxel MRS. Histological fat quantification included estimation of the percentage of hepatocytes containing fat vesicles as well as semi-automatic quantification (qHisto) using tissue quantification software.

Results

In 33 of 59 patients, the hepatic fat fraction was >5 % as determined by MRS (maximum 45 %, mean 17 %). Dual-echo mDixon yielded systematically lower PDFF values than six-echo mDixon (mean difference 1.0 %; P < 0.001). Six-echo mDixon correlated excellently with MRS, qHisto, and the estimated percentage of hepatocytes containing fat vesicles (R = 0.984, 0.967, 0.941, respectively, all P < 0.001). Mean values obtained by the estimated percentage of hepatocytes containing fat were higher by a factor of 2.5 in comparison to qHisto. Six-echo mDixon and MRS showed the best agreement with values obtained by qHisto.

Conclusions

Six-echo mDixon, MRS, and qHisto provide the most robust and congruent results and are therefore most appropriate for reliable quantification of liver fat.

Key Points

• Six-echo mDixon correlates excellently with MRS, qHisto, and the estimated percentage of fat-containing hepatocytes.

• Six-echo mDixon, MRS, and qHisto provide the most robust and congruent results.

• Dual-echo mDixon yields systematically lower PDFF values than six-echo mDixon.

• The percentage of fat-containing hepatocytes is 2.5-fold higher than fat fraction determined by qHisto.

• Performance characteristics and systematic differences of the various methods should be considered.

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References

  1. Blachier M, Leleu H, Peck-Radosavljevic M, Valla DC, Roudot-Thoraval F (2013) The burden of liver disease in Europe: a review of available epidemiological data. J Hepatol 58:593–608

    Article  PubMed  Google Scholar 

  2. Cairns SR, Peters TJ (1983) Biochemical analysis of hepatic lipid in alcoholic and diabetic and control subjects. Clin Sci (Lond) 65:645–652

    Article  CAS  Google Scholar 

  3. Brunt EM, Neuschwander-Tetri BA, Burt AD (2012) Fatty liver disease: alcoholic and non-alcoholic. In: Burt AD, Portmann BC, Ferell LD (eds) MacSween's Pathology of the Liver. Churchill Livingstone Elsevier, Toronto, pp 293–359

    Chapter  Google Scholar 

  4. Lee RG (1994) Fatty change and steatohepatitis. In: Lee RG (ed) Diagnostic liver pathology. Mosby, St. Louis, pp 167–194

    Google Scholar 

  5. Neuschwander-Tetri BA, Caldwell SH (2003) Nonalcoholic steatohepatitis: summary of an AASLD Single Topic Conference. Hepatology 37:1202–1219

    Article  PubMed  Google Scholar 

  6. Chalasani N, Younossi Z, Lavine JE et al (2012) The diagnosis and management of non-alcoholic fatty liver disease: practice Guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association. Hepatology 55:2005–2023

    Article  PubMed  Google Scholar 

  7. Reid AE (2010) Nonalcoholic fatty liver disease. In: Feldman M, Friedman LS, Brandt LJ (eds) Sleisenger and Fordtran's gastrointestinal and liver disease. Saunders Elsevier, Philadelphia, pp 1401–1412

    Chapter  Google Scholar 

  8. Strassburg CP, Manns MP (2006) Approaches to liver biopsy techniques–revisited. Semin Liver Dis 26:318–327

    Article  PubMed  Google Scholar 

  9. Hatfield MK, Beres RA, Sane SS, Zaleski GX (2008) Percutaneous imaging-guided solid organ core needle biopsy: coaxial versus noncoaxial method. AJR Am J Roentgenol 190:413–417

    Article  PubMed  Google Scholar 

  10. Bravo AA, Sheth SG, Chopra S (2001) Liver biopsy. N Engl J Med 344:495–500

    Article  CAS  PubMed  Google Scholar 

  11. Ratziu V, Charlotte F, Heurtier A et al (2005) Sampling Variability of Liver Biopsy in Nonalcoholic Fatty Liver Disease. Gastroenterology 128:1898–1906

    Article  PubMed  Google Scholar 

  12. Bohte AE, van Werven JR, Bipat S, Stoker J (2011) The diagnostic accuracy of US, CT, MRI and 1H-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis. Eur Radiol 21:87–97

    Article  PubMed Central  PubMed  Google Scholar 

  13. Reeder SB, Cruite I, Hamilton G, Sirlin CB (2011) Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging 34:729–749

    Article  PubMed  Google Scholar 

  14. Banerjee R, Pavlides M, Tunnicliffe EM et al (2014) Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. J Hepatol 60:69–77

    Article  PubMed Central  PubMed  Google Scholar 

  15. McPherson S, Jonsson JR, Cowin GJ et al (2009) Magnetic resonance imaging and spectroscopy accurately estimate the severity of steatosis provided the stage of fibrosis is considered. J Hepatol 51:389–397

    Article  PubMed  Google Scholar 

  16. Valls C, Iannacconne R, Alba E et al (2006) Fat in the liver: diagnosis and characterization. Eur Radiol 16:2292–2308

    Article  PubMed  Google Scholar 

  17. Berglund J, Ahlstrom H, Johansson L, Kullberg J (2011) Two-point dixon method with flexible echo times. Magn Reson Med 65:994–1004

    Article  PubMed  Google Scholar 

  18. Eggers H, Brendel B, Duijndam A, Herigault G (2011) Dual-echo Dixon imaging with flexible choice of echo times. Magn Reson Med 65:96–107

    Article  PubMed  Google Scholar 

  19. Idilman IS, Aniktar H, Idilman R et al (2013) Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology 267:767–775

    Article  PubMed  Google Scholar 

  20. Reeder SB (2013) Emerging quantitative magnetic resonance imaging biomarkers of hepatic steatosis. Hepatology 58:1877–1880

    Article  CAS  PubMed  Google Scholar 

  21. Reeder SB, Sirlin CB (2010) Quantification of liver fat with magnetic resonance imaging. Magn Reson Imaging Clin N Am 18:337-–357, ix

    Article  PubMed Central  PubMed  Google Scholar 

  22. Dixon WT (1984) Simple proton spectroscopic imaging. Radiology 153:189–194

    Article  CAS  PubMed  Google Scholar 

  23. Eggers H, Perkins TG, Hussain SM (2011) Influence of Spectral Model and Signal Decay on Hepatic Fat Fraction Measurements at 3 T with Dual-Echo Dixon Imaging. Proc Int Soc Magn Reson Med 19:573

    Google Scholar 

  24. Yu H, Shimakawa A, McKenzie CA, Brodsky E, Brittain JH, Reeder SB (2008) Multiecho water-fat separation and simultaneous R2* estimation with multifrequency fat spectrum modeling. Magn Reson Med 60:1122–1134

    Article  PubMed Central  PubMed  Google Scholar 

  25. Tang A, Tan J, Sun M et al (2013) Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology 267:422–431

    Article  PubMed Central  PubMed  Google Scholar 

  26. Noureddin M, Lam J, Peterson MR et al (2013) Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology 58:1930–1940

    Article  CAS  PubMed  Google Scholar 

  27. Kleiner DE, Brunt EM, Van Natta M et al (2005) Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41:1313–1321

    Article  PubMed  Google Scholar 

  28. Brunt EM, Janney CG, Di Bisceglie AM, Neuschwander-Tetri BA, Bacon BR (1999) Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am J Gastroenterol 94:2467–2474

    Article  CAS  PubMed  Google Scholar 

  29. d'Assignies G, Kauffmann C, Boulanger Y et al (2011) Simultaneous assessment of liver volume and whole liver fat content: a step towards one-stop shop preoperative MRI protocol. Eur Radiol 21:301–309

    Article  PubMed  Google Scholar 

  30. Lin ZH, Xin YN, Dong QJ et al (2011) Performance of the aspartate aminotransferase-to-platelet ratio index for the staging of hepatitis C-related fibrosis: an updated meta-analysis. Hepatology 53:726–736

    Article  PubMed  Google Scholar 

  31. Frahm J, Merboldt K, Hänicke W (1987) Localized proton spectroscopy using stimulated echoes. J Magn Reson 72:502–508

    CAS  Google Scholar 

  32. Vanhamme L, van den Boogaart A, Van Huffel S (1997) Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 129:35–43

    Article  CAS  PubMed  Google Scholar 

  33. Naressi A, Couturier C, Castang I, de Beer R, Graveron-Demilly D (2001) Java-based graphical user interface for MRUI, a software package for quantitation of in vivo/medical magnetic resonance spectroscopy signals. Comput Biol Med 31:269–286

    Article  CAS  PubMed  Google Scholar 

  34. Ren J, Dimitrov I, Sherry AD, Malloy CR (2008) Composition of adipose tissue and marrow fat in humans by 1H NMR at 7 Tesla. J Lipid Res 49:2055–2062

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  35. Hamilton G, Yokoo T, Bydder M et al (2011) In vivo characterization of the liver fat (1)H MR spectrum. NMR Biomed 24:784–790

    Article  PubMed  Google Scholar 

  36. Johnson NA, Walton DW, Sachinwalla T et al (2008) Noninvasive assessment of hepatic lipid composition: Advancing understanding and management of fatty liver disorders. Hepatology 47:1513–1523

    Article  CAS  PubMed  Google Scholar 

  37. Vuppalanchi R, Cummings OW, Saxena R et al (2007) Relationship among histologic, radiologic, and biochemical assessments of hepatic steatosis: a study of human liver samples. J Clin Gastroenterol 41:206–210

    Article  PubMed  Google Scholar 

  38. Henninger B, Kremser C, Rauch S et al (2013) Evaluation of liver fat in the presence of iron with MRI using T2* correction: a clinical approach. Eur Radiol 23:1643–1649

    Article  PubMed  Google Scholar 

  39. Lee SS, Lee Y, Kim N et al (2011) Hepatic fat quantification using chemical shift MR imaging and MR spectroscopy in the presence of hepatic iron deposition: validation in phantoms and in patients with chronic liver disease. J Magn Reson Imaging 33:1390–1398

    Article  PubMed  Google Scholar 

  40. Kang BK, Yu ES, Lee SS et al (2012) Hepatic fat quantification: a prospective comparison of magnetic resonance spectroscopy and analysis methods for chemical-shift gradient echo magnetic resonance imaging with histologic assessment as the reference standard. Invest Radiol 47:368–375

    Article  CAS  PubMed  Google Scholar 

  41. Hines CD, Frydrychowicz A, Hamilton G et al (2011) T(1) independent, T(2) (*) corrected chemical shift based fat-water separation with multi-peak fat spectral modeling is an accurate and precise measure of hepatic steatosis. J Magn Reson Imaging 33:873–881

    Article  PubMed Central  PubMed  Google Scholar 

  42. Koelblinger C, Krssak M, Maresch J et al (2012) Hepatic steatosis assessment with 1H-spectroscopy and chemical shift imaging at 3.0 T before hepatic surgery: reliable enough for making clinical decisions? Eur J Radiol 81:2990–2995

    Article  PubMed  Google Scholar 

  43. Hu HH, Kim HW, Nayak KS, Goran MI (2010) Comparison of fat-water MRI and single-voxel MRS in the assessment of hepatic and pancreatic fat fractions in humans. Obesity (Silver Spring) 18:841–847

    Article  Google Scholar 

  44. El-Badry AM, Breitenstein S, Jochum W et al (2009) Assessment of hepatic steatosis by expert pathologists: the end of a gold standard. Ann Surg 250:691–697

    Article  PubMed  Google Scholar 

  45. Marsman H, Matsushita T, Dierkhising R et al (2004) Assessment of donor liver steatosis: pathologist or automated software? Hum Pathol 35:430–435

    Article  CAS  PubMed  Google Scholar 

  46. Kremer GJ, Kößling FK, Lange HJ, N. V (1969) Fat content of the liver: a chemical and histological study. Dtsch Med Wochenschr 94:163-169

  47. Szczepaniak LS, Babcock EE, Schick F et al (1999) Measurement of intracellular triglyceride stores by H spectroscopy: validation in vivo. Am J Physiol 276:977–989

    Google Scholar 

Download references

Acknowledgments

The scientific guarantor of this publication is Guido M. Kukuk, Department of Radiology, University of Bonn. The authors of this manuscript declare relationships with the following companies: Holger Eggers is employee of Philips Research, Hamburg, Germany. Jürgen Gieseke is employee of Philips Healthcare, Best, the Netherlands. Both authors had no control of inclusion of any data and of data analysis. All other 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 obtained from all patients in this study. Methodology: prospective, diagnostic or prognostic study, performed at one institution.

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Authors and Affiliations

  1. Department of Radiology, University of Bonn, Sigmund-Freud-Straße 25, 53127, Bonn, Germany

    Guido M. Kukuk, Alois M. Sprinkart, Jürgen Gieseke, Wolfgang Block, Winfried A. Willinek, Hans H. Schild & Frank Träber

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

    Kanishka Hittatiya & Hans-Peter Fischer

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

    Alois M. Sprinkart

  4. Philips Research Europe, Hamburg, Germany

    Holger Eggers

  5. Philips Healthcare, Best, The Netherlands

    Jürgen Gieseke

  6. Department of Internal Medicine I, University of Bonn, Bonn, Germany

    Philipp Moeller, Ulrich Spengler & Jonel Trebicka

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  1. Guido M. Kukuk
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Correspondence to Guido M. Kukuk.

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Kukuk, G.M., Hittatiya, K., Sprinkart, A.M. et al. Comparison between modified Dixon MRI techniques, MR spectroscopic relaxometry, and different histologic quantification methods in the assessment of hepatic steatosis. Eur Radiol 25, 2869–2879 (2015). https://doi.org/10.1007/s00330-015-3703-6

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  • DOI: https://doi.org/10.1007/s00330-015-3703-6

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