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MRI-derived proton density fat fraction

  • Special Feature: Review Article
  • Quantitative assessment of liver steatosis using ultrasound
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Abstract

Reflecting the growing interest in early diagnosis of nonalcoholic fatty liver disease in recent years, the development of noninvasive and reliable fat quantification methods is required. Fat quantification by magnetic resonance imaging (MRI), especially MRI-derived proton density fat fraction (MRI-PDFF) obtained by quantitative chemical shift imaging such as the multi-point Dixon method, is highly correlated with histological evaluation and fat quantification with MR spectroscopy (MRS). In recent years, MRI-PDFF has been increasingly used as a reference standard for image-based fat quantification instead of MRS because it is possible to evaluate the whole liver with a single breath-hold. Furthermore, recent advances in MR imaging have led to the application of multiparametric MRI for the diagnosis of nonalcoholic fatty liver disease with specific liver tissue quantification of fat, iron, and fibrosis. One of the advantages of multiparametric MRI is that whole organ imaging to exclude sampling variability and organ-specific tissue quantification can be done simultaneously. Therefore, multiparametric MRI methods offer an attractive option for noninvasive and comprehensive liver assessment beyond the quantitative assessment of liver steatosis. In this review article, we mainly focus on a technical explanation and clinical interpretation of MRI-PDFF in the quantitative assessment of liver steatosis. Furthermore, we would like to mention future perspectives of MR imaging of the liver in relation to elastography and other specific multiparametric MRI methods such as R2* and T1 mapping.

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References

  1. Younossi ZM, Koenig AB, Abdelatif D, et al. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology. 2016;64:73–84.

    Article  Google Scholar 

  2. Estes C, Anstee QM, Arias-Loste MT, et al. Modeling NAFLD disease burden in China, France, Germany, Italy, Japan, Spain, United Kingdom, and United States for the period 2016–2030. J Hepatol. 2018;69:896–904.

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  4. Ratziu V, Charlotte F, Heurtier A, et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology. 2005;128:1898–906.

    Article  Google Scholar 

  5. Marchesini G, Day CP, Dufour JF, et al. EASL-EASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016;64:1388–402.

  6. Pavlides M, Banerjee R, Tunnicliffe EM, et al. Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int. 2017;37:1065–73.

    Article  CAS  Google Scholar 

  7. Schaapman JJ, Tushuizen ME, Coenraad MJ, et al. Multiparametric MRI in patients with nonalcoholic fatty liver disease. J Magn Reson Imaging. 2021;53:1623–31.

    Article  Google Scholar 

  8. Reeder SB, Cruite I, Hamilton G, et al. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging. 2011;34:729–49.

    Article  Google Scholar 

  9. Dixon WT. Simple proton spectroscopic imaging. Radiology. 1984;153:189–94.

    Article  CAS  Google Scholar 

  10. Reeder SB, McKenzie CA, Pineda AR, et al. Water-fat separation with IDEAL gradient-echo imaging. J Magn Reson Imaging. 2007;25:644–52.

    Article  Google Scholar 

  11. Bydder M, Yokoo T, Hamilton G, et al. Relaxation effects in the quantification of fat using gradient echo imaging. Magn Reson Imaging. 2008;26:347–59.

    Article  Google Scholar 

  12. Liu CY, McKenzie CA, Yu H, et al. Fat quantification with IDEAL gradient echo imaging: correction of bias from T(1) and noise. Magn Reson Med. 2007;58:354–64.

    Article  Google Scholar 

  13. George DK, Goldwurm S, MacDonald GA, et al. Increased hepatic iron concentration in nonalcoholic steatohepatitis is associated with increased fibrosis. Gastroenterology. 1998;114:311–8.

    Article  CAS  Google Scholar 

  14. Yu H, McKenzie CA, Shimakawa A, et al. Multiecho reconstruction for simultaneous water-fat decomposition and T2* estimation. J Magn Reson Imaging. 2007;26:1153–61.

    Article  Google Scholar 

  15. Chebrolu VV, Hines CD, Yu H, et al. Independent estimation of T2* for water and fat for improved accuracy of fat quantification. Magn Reson Med. 2010;63:849–57.

    Article  Google Scholar 

  16. Yokoo T, Bydder M, Hamilton G, et al. Nonalcoholic fatty liver disease: diagnostic and fat-grading accuracy of low-flip-angle multiecho gradient-recalled-echo MR imaging at 1.5 T. Radiology. 2009;251:67–76.

    Article  Google Scholar 

  17. Szczepaniak LS, Babcock EE, Schick F, et al. Measurement of intracellular triglyceride stores by H spectroscopy: validation in vivo. Am J Physiol. 1999;276:E977–89.

    CAS  PubMed  Google Scholar 

  18. Thomsen C, Becker U, Winkler K, et al. Quantification of liver fat using magnetic resonance spectroscopy. Magn Reson Imaging. 1994;12:487–95.

    Article  CAS  Google Scholar 

  19. Meisamy S, Hines CD, Hamilton G, et al. Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy. Radiology. 2011;258:767–75.

    Article  Google Scholar 

  20. Zhong X, Nickel MD, Kannengiesser SA, et al. Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med. 2014;72:1353–65.

    Article  Google Scholar 

  21. Yokoo T, Shiehmorteza M, Hamilton G, et al. Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T. Radiology. 2011;258:749–59.

    Article  Google Scholar 

  22. Noworolski SM, Lam MM, Merriman RB, et al. Liver steatosis: concordance of MR imaging and MR spectroscopic data with histologic grade. Radiology. 2012;264:88–96.

    Article  Google Scholar 

  23. Hwang I, Lee JM, Lee KB, et al. Hepatic steatosis in living liver donor candidates: preoperative assessment by using breath-hold triple-echo MR imaging and 1H MR spectroscopy. Radiology. 2014;271:730–8.

    Article  Google Scholar 

  24. Kühn JP, Hernando D, Muñoz del Rio A, et al. Effect of multipeak spectral modeling of fat for liver iron and fat quantification: correlation of biopsy with MR imaging results. Radiology. 2012;265:133–42.

    Article  Google Scholar 

  25. Noureddin M, Lam J, Peterson MR, et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology. 2013;58:1930–40.

    Article  CAS  Google Scholar 

  26. Yu H, Shimakawa A, McKenzie CA, et al. Multiecho water-fat separation and simultaneous R2* estimation with multifrequency fat spectrum modeling. Magn Reson Med. 2008;60:1122–34.

    Article  Google Scholar 

  27. Rostoker G, Loridon C, Griuncelli M, et al. Liver iron load influences hepatic fat fraction in end-stage renal disease patients on dialysis: a proof of concept study. EBioMedicine. 2019;39:461–71.

    Article  Google Scholar 

  28. Bashir MR, Wolfson T, Gamst AC, et al. Hepatic R2* is more strongly associated with proton density fat fraction than histologic liver iron scores in patients with nonalcoholic fatty liver disease. J Magn Reson Imaging. 2019;49:1456–66.

    Article  Google Scholar 

  29. Bannas P, Kramer H, Hernando D, et al. Quantitative magnetic resonance imaging of hepatic steatosis: validation in ex vivo human livers. Hepatology. 2015;62:1444–55.

    Article  CAS  Google Scholar 

  30. Yokoo T, Serai SD, Pirasteh A, et al. Linearity, bias, and precision of hepatic proton density fat fraction measurements by using MR imaging: a meta-analysis. Radiology. 2018;286:486–98.

    Article  Google Scholar 

  31. van Werven JR, Marsman HA, Nederveen AJ, et al. Assessment of hepatic steatosis in patients undergoing liver resection: comparison of US, CT, T1-weighted dual-echo MR imaging, and point-resolved 1H MR spectroscopy. Radiology. 2010;256:159–68.

    Article  Google Scholar 

  32. Xu X, Zhu H, Li R, et al. Whole-liver histogram and texture analysis on T1 maps improves the risk stratification of advanced fibrosis in NAFLD. Eur Radiol. 2021;31:1748–59.

    Article  CAS  Google Scholar 

  33. Shahryari M, Meyer T, Warmuth C, et al. Reduction of breathing artifacts in multifrequency magnetic resonance elastography of the abdomen. Magn Reson Med. 2021;85:1962–73.

    Article  Google Scholar 

  34. Idilman IS, Aniktar H, Idilman R, et al. Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology. 2013;267:767–75.

    Article  Google Scholar 

  35. Angulo P, Kleiner DE, Dam-Larsen S, et al. Liver fibrosis, but no other histologic features, is associated with long-term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology. 2015;149:389-97.e10.

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Radiology, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-2621, Japan

    Eriko Yoshizawa & Akira Yamada

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  1. Eriko Yoshizawa
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  2. Akira Yamada
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Correspondence to Akira Yamada.

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Akira Yamada declares that he has no conflicts of interest. Eriko Yoshizawa declares that she has no conflicts of interest.

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Yoshizawa, E., Yamada, A. MRI-derived proton density fat fraction. J Med Ultrasonics 48, 497–506 (2021). https://doi.org/10.1007/s10396-021-01135-w

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  • DOI: https://doi.org/10.1007/s10396-021-01135-w

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