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Putting it all together: established and emerging MRI techniques for detecting and measuring liver fibrosis

  • Pediatric Body MRI
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Abstract

Chronic injury to the liver leads to inflammation and hepatocyte necrosis, which when untreated can lead to myofibroblast activation and fibrogenesis with deposition of fibrous tissue. Over time, liver fibrosis can accumulate and lead to cirrhosis and end-stage liver disease with associated portal hypertension and liver failure. Detection and accurate measurement of the severity of liver fibrosis are important for assessing disease severity and progression, directing patient management, and establishing prognosis. Liver biopsy, generally considered the clinical standard of reference for detecting and measuring liver fibrosis, is invasive and has limitations, including sampling error, relatively high cost, and possible complications. For these reasons, liver biopsy is suboptimal for fibrosis screening, longitudinal monitoring, and assessing therapeutic efficacy. A variety of established and emerging qualitative and quantitative noninvasive MRI methods for detecting and staging liver fibrosis might ultimately serve these purposes. In this article, we review multiple MRI methods for detecting and measuring liver fibrosis and discuss the diagnostic performance and specific strengths and limitations of the various techniques.

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References

  1. Cordova J, Jericho H, Azzam RK (2016) An overview of cirrhosis in children. Pediatr Ann 45:e427–e432

    Article  PubMed  Google Scholar 

  2. Pinto RB, Schneider AC, da Silveira TR (2015) Cirrhosis in children and adolescents: an overview. World J Hepatol 7:392–405

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lee UE, Friedman SL (2011) Mechanisms of hepatic fibrogenesis. Best Pract Res Clin Gastroenterol 25:195–206

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Arthur MJ (2002) Reversibility of liver fibrosis and cirrhosis following treatment for hepatitis C. Gastroenterology 122:1525–1528

    Article  PubMed  Google Scholar 

  5. Wang P, Koyama Y, Liu X et al (2016) Promising therapy candidates for liver fibrosis. Front Physiol 7:47

    PubMed  PubMed Central  Google Scholar 

  6. Regev A, Berho M, Jeffers LJ et al (2002) Sampling error and intraobserver variation in liver biopsy in patients with chronic HCV infection. Am J Gastroenterol 97:2614–2618

    Article  PubMed  Google Scholar 

  7. 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 

  8. Serai SD, Towbin AJ, Podberesky DJ (2012) Pediatric liver MR elastography. Dig Dis Sci 57:2713–2719

    Article  PubMed  Google Scholar 

  9. Yin M, Talwalkar JA, Glaser KJ et al (2007) Assessment of hepatic fibrosis with magnetic resonance elastography. Clin Gastroenterol Hepatol 5:1207–1213 e1202

    Article  PubMed  PubMed Central  Google Scholar 

  10. Hu G, Zhang X, Liang W et al (2016) Assessment of liver fibrosis in rats by MRI with apparent diffusion coefficient and T1 relaxation time in the rotating frame. J Magn Reson Imaging 43:1082–1089

    Article  PubMed  Google Scholar 

  11. Rauscher I, Eiber M, Ganter C et al (2014) Evaluation of T1rho as a potential MR biomarker for liver cirrhosis: comparison of healthy control subjects and patients with liver cirrhosis. Eur J Radiol 83:900–904

    Article  PubMed  Google Scholar 

  12. Singh A, Reddy D, Haris M et al (2015) T1rho MRI of healthy and fibrotic human livers at 1.5 T. J Transl Med 13:292

    Article  PubMed  PubMed Central  Google Scholar 

  13. Zhang H, Yang Q, Yu T et al (2016) Comparison of T2, T1rho, and diffusion metrics in assessment of liver fibrosis in rats. J Magn Reson Imaging 45:741–750

    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  PubMed Central  Google Scholar 

  15. Guimaraes AR, Siqueira L, Uppal R et al (2016) T2 relaxation time is related to liver fibrosis severity. Quant Imaging Med Surg 6:103–114

    Article  PubMed  PubMed Central  Google Scholar 

  16. Serai SD, Trout AT, Sirlin CB (2017) Elastography to assess the stage of liver fibrosis in children: concepts, opportunities, and challenges. Clin Liver Dis 9:5–10

    Article  Google Scholar 

  17. Serai SD, Dillman JR, Trout AT (2017) Spin-echo echo-planar imaging MR elastography versus gradient-echo MR elastography for assessment of liver stiffness in children and young adults suspected of having liver disease. Radiology 282:761–770

    Article  PubMed  Google Scholar 

  18. Dodd GD 3rd, Baron RL, Oliver JH 3rd et al (1999) Spectrum of imaging findings of the liver in end-stage cirrhosis: part I, gross morphology and diffuse abnormalities. AJR Am J Roentgenol 173:1031–1036

    Article  PubMed  Google Scholar 

  19. Brancatelli G, Federle MP, Ambrosini R et al (2007) Cirrhosis: CT and MR imaging evaluation. Eur J Radiol 61:57–69

    Article  PubMed  Google Scholar 

  20. Ito K, Mitchell DG, Kim MJ et al (2003) Right posterior hepatic notch sign: a simple diagnostic MR finding of cirrhosis. J Magn Reson Imaging 18:561–566

    Article  PubMed  Google Scholar 

  21. Marti-Bonmati L, Delgado F (2010) MR imaging in liver cirrhosis: classical and new approaches. Insights Imaging 1:233–244

    Article  PubMed  PubMed Central  Google Scholar 

  22. Ito K, Mitchell DG, Gabata T et al (1999) Expanded gallbladder fossa: simple MR imaging sign of cirrhosis. Radiology 211:723–726

    Article  PubMed  CAS  Google Scholar 

  23. Smith AD, Branch CR, Zand K et al (2016) Liver surface nodularity quantification from routine CT images as a biomarker for detection and evaluation of cirrhosis. Radiology 280:771–781

    Article  PubMed  Google Scholar 

  24. Alhammad A, Kamath BM, Chami R et al (2016) Solitary hepatic nodule adjacent to the right portal vein: a common finding of Alagille syndrome? J Pediatr Gastroenterol Nutr 62:226–232

    Article  PubMed  Google Scholar 

  25. Venkatesh SK, Ehman RL (2014) Magnetic resonance elastography of liver. Magn Reson Imaging Clin N Am 22:433–446

    Article  PubMed  Google Scholar 

  26. Xanthakos SA, Podberesky DJ, Serai SD et al (2014) Use of magnetic resonance elastography to assess hepatic fibrosis in children with chronic liver disease. J Pediatr 164:186–188

    Article  PubMed  Google Scholar 

  27. Wagner M, Besa C, Bou Ayache J et al (2016) Magnetic resonance elastography of the liver: qualitative and quantitative comparison of gradient echo and spin echo echoplanar imaging sequences. Investig Radiol 51:575–581

    Article  Google Scholar 

  28. Loomba R, Cui J, Wolfson T et al (2016) Novel 3D magnetic resonance elastography for the noninvasive diagnosis of advanced fibrosis in NAFLD: a prospective study. Am J Gastroenterol 111:986–994

    Article  PubMed  PubMed Central  Google Scholar 

  29. Joshi M, Dillman JR, Singh K et al (2017) Quantitative MRI of fatty liver disease in a large pediatric cohort: correlation between liver fat fraction, stiffness, volume, and patient-specific factors. Abdom Radiol. https://doi.org/10.1007/s00261-017-1289-y

  30. Joshi M, Dillman JR, Towbin AJ et al (2017) MR elastography: high rate of technical success in pediatric and young adult patients. Pediatr Radiol 47:838–843

    Article  PubMed  Google Scholar 

  31. Venkatesh SK, Yin M, Ehman RL (2013) Magnetic resonance elastography of liver: technique, analysis, and clinical applications. J Magn Reson Imaging 37:544–555

    Article  PubMed  PubMed Central  Google Scholar 

  32. Trout AT, Dillman JR, Xanthakos S et al (2016) Prospective assessment of correlation between US acoustic radiation force impulse and MR elastography in a pediatric population: dispersion of US shear-wave speed measurement matters. Radiology 281:544–552

    Article  PubMed  Google Scholar 

  33. Singh S, Venkatesh SK, Wang Z et al (2015) Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clin Gastroenterol Hepatol 13:440–451 e446

    Article  PubMed  Google Scholar 

  34. Serai SD, Obuchowski NA, Venkatesh SK et al (2017) Repeatability of MR elastography of liver: a meta-analysis. Radiology 285:92–100

    Article  PubMed  Google Scholar 

  35. Cui J, Ang B, Haufe W et al (2015) Comparative diagnostic accuracy of magnetic resonance elastography vs. eight clinical prediction rules for non-invasive diagnosis of advanced fibrosis in biopsy-proven non-alcoholic fatty liver disease: a prospective study. Aliment Pharmacol Ther 41:1271–1280

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Shinagawa Y, Mitsufuji T, Morimoto S et al (2014) Optimization of scanning parameters for MR elastography at 3.0 T clinical unit: volunteer study. Jpn J Radiol 32:441–446

    Article  PubMed  Google Scholar 

  37. Trout AT, Serai S, Mahley AD et al (2016) Liver stiffness measurements with MR elastography: agreement and repeatability across imaging systems, field strengths, and pulse sequences. Radiology 281:793–804

    Article  PubMed  Google Scholar 

  38. Huwart L, Sempoux C, Salameh N et al (2007) Liver fibrosis: noninvasive assessment with MR elastography versus aspartate aminotransferase-to-platelet ratio index. Radiology 245:458–466

    Article  PubMed  Google Scholar 

  39. Cui J, Heba E, Hernandez C et al (2016) Magnetic resonance elastography is superior to acoustic radiation force impulse for the diagnosis of fibrosis in patients with biopsy-proven nonalcoholic fatty liver disease: a prospective study. Hepatology 63:453–461

    Article  PubMed  Google Scholar 

  40. Bonekamp S, Kamel I, Solga S et al (2009) Can imaging modalities diagnose and stage hepatic fibrosis and cirrhosis accurately? J Hepatol 50:17–35

    Article  PubMed  Google Scholar 

  41. Venkatesh SK, Yin M, Takahashi N et al (2015) Non-invasive detection of liver fibrosis: MR imaging features vs. MR elastography. Abdom Imaging 40:766–775

    Article  PubMed  PubMed Central  Google Scholar 

  42. Yin M, Glaser KJ, Talwalkar JA et al (2016) Hepatic MR elastography: clinical performance in a series of 1,377 consecutive examinations. Radiology 278:114–124

    Article  PubMed  Google Scholar 

  43. Shire NJ, Yin M, Chen J et al (2011) Test-retest repeatability of MR elastography for noninvasive liver fibrosis assessment in hepatitis C. J Magn Reson Imaging 34:947–955

    Article  PubMed  PubMed Central  Google Scholar 

  44. Dulai PS, Sirlin CB, Loomba R (2016) MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: clinical trials to clinical practice. J Hepatol 65:1006–1016

    Article  PubMed  PubMed Central  Google Scholar 

  45. Deng M, Zhao F, Yuan J et al (2012) Liver T1rho MRI measurement in healthy human subjects at 3 T: a preliminary study with a two-dimensional fast-field echo sequence. Br J Radiol 85:e590–e595

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  46. Serai SD, Wallihan DB, Venkatesh SK et al (2014) Magnetic resonance elastography of the liver in patients status-post fontan procedure: feasibility and preliminary results. Congenit Heart Dis 9:7–14

    Article  PubMed  Google Scholar 

  47. Wallihan DB, Podberesky DJ, Marino BS et al (2014) Relationship of MR elastography determined liver stiffness with cardiac function after Fontan palliation. J Magn Reson Imaging 40:1328–1335

    Article  PubMed  Google Scholar 

  48. Dillman JR, Trout AT, Costello EN et al (2017) Quantitative liver MRI-biopsy correlation in pediatric and young adult patients with nonalcoholic fatty liver disease: can one be used to predict the other? AJR Am J Roentgenol 18:1–9

    Google Scholar 

  49. Yin M, Talwalkar JA, Glaser KJ et al (2011) Dynamic postprandial hepatic stiffness augmentation assessed with MR elastography in patients with chronic liver disease. AJR Am J Roentgenol 197:64–70

    Article  PubMed  PubMed Central  Google Scholar 

  50. Mariappan YK, Dzyubak B, Glaser KJ et al (2017) Application of modified spin-echo-based sequences for hepatic MR elastography: evaluation, comparison with the conventional gradient-echo sequence, and preliminary clinical experience. Radiology 282:390–398

    Article  PubMed  Google Scholar 

  51. Hazlewood CF, Yamanashi WS, Rangel RA et al (1982) In vivo NMR imaging and T1 measurements of water protons in the human brain. Magn Reson Imaging 1:3–10

    Article  PubMed  CAS  Google Scholar 

  52. Look DC, Locker DR (1970) Time saving in measurement of NMR and EPR relaxation times. Rev Sci Instrum 41:250–251

    Article  CAS  Google Scholar 

  53. Messroghli DR, Radjenovic A, Kozerke S et al (2004) Modified look-locker inversion recovery (MOLLI) for high-resolution T1 mapping of the heart. Magn Reson Med 52:141–146

    Article  PubMed  Google Scholar 

  54. Serai SD, Fleck RJ, Quinn CT et al (2015) Retrospective comparison of gradient recalled echo R2* and spin-echo R2 magnetic resonance analysis methods for estimating liver iron content in children and adolescents. Pediatr Radiol 45:1629–1634

    Article  PubMed  Google Scholar 

  55. Towbin AJ, Serai SD, Podberesky DJ (2013) Magnetic resonance imaging of the pediatric liver. imaging of steatosis, iron deposition, and fibrosis Magn Reson Imaging Clin N Am 21:669–680

    Article  PubMed  Google Scholar 

  56. Tunnicliffe EM, Banerjee R, Pavlides M et al (2017) A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified look-locker inversion recovery T1 (shMOLLI-T1 ) in the liver. J Magn Reson Imaging 45:450–462

    Article  PubMed  Google Scholar 

  57. Pavlides M, Banerjee R, Sellwood J et al (2016) Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease. J Hepatol 64:308–315

    Article  PubMed  PubMed Central  Google Scholar 

  58. Pavlides M, Banerjee R, Tunnicliffe EM et al (2017) Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int 37:1065–1073

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Zhou ZP, Long LL, Qiu WJ et al (2017) Evaluating segmental liver function using T1 mapping on Gd-EOB-DTPA-enhanced MRI with a 3.0 tesla. BMC Med Imaging 17:20

    Article  PubMed  PubMed Central  Google Scholar 

  60. Haimerl M, Verloh N, Fellner C et al (2014) MRI-based estimation of liver function: Gd-EOB-DTPA-enhanced T1 relaxometry of 3T vs. the MELD score. Sci Rep 4:5621

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  61. Kawel N, Nacif M, Zavodni A et al (2012) T1 mapping of the myocardium: intra-individual assessment of the effect of field strength, cardiac cycle and variation by myocardial region. J Cardiovasc Magn Reson 14:27

    Article  PubMed  PubMed Central  Google Scholar 

  62. Neumann D, Blaimer M, Jakob PM et al (2014) Simple recipe for accurate T(2) quantification with multi spin-echo acquisitions. MAGMA 27:567–577

    Article  PubMed  Google Scholar 

  63. Schneiders NJ, Post H, Brunner P et al (1983) Accurate T2 NMR images. Med Phys 10:642–645

    Article  PubMed  CAS  Google Scholar 

  64. Filho HML, Chua-anusorn W, Oliveira CP et al (2017) Novel mapping of fibrosis and hepatic inflammation in NASH patients with dual R2 MRI relaxometry. J Hepatol 66:S243–S244

    Article  Google Scholar 

  65. Sepponen RE, Pohjonen JA, Sipponen JT et al (1985) A method for T1 rho imaging. J Comput Assist Tomogr 9:1007–1011

    Article  PubMed  CAS  Google Scholar 

  66. Takayama Y, Nishie A, Asayama Y et al (2015) T1 rho relaxation of the liver: a potential biomarker of liver function. J Magn Reson Imaging 42:188–195

    Article  PubMed  Google Scholar 

  67. Wang YX, Yuan J (2014) Evaluation of liver fibrosis with T1rho MR imaging. Quant Imaging Med Surg 4:152–155

    PubMed  PubMed Central  Google Scholar 

  68. Wang YX, Yuan J, Chu ES et al (2011) T1rho MR imaging is sensitive to evaluate liver fibrosis: an experimental study in a rat biliary duct ligation model. Radiology 259:712–719

    Article  PubMed  Google Scholar 

  69. Witschey WR 2nd, Borthakur A, Elliott MA et al (2007) Artifacts in T1 rho-weighted imaging: compensation for B(1) and B(0) field imperfections. J Magn Reson 186:75–85

  70. Chavhan GB, Alsabban Z, Babyn PS (2014) Diffusion-weighted imaging in pediatric body MR imaging: principles, technique, and emerging applications. Radiographics 34:E73–E88

    Article  PubMed  Google Scholar 

  71. Le Bihan D, Breton E, Lallemand D et al (1988) Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 168:497–505

    Article  PubMed  Google Scholar 

  72. Taouli B, Tolia AJ, Losada M et al (2007) Diffusion-weighted MRI for quantification of liver fibrosis: preliminary experience. AJR Am J Roentgenol 189:799–806

    Article  PubMed  Google Scholar 

  73. Palmucci S, Cappello G, Attina G et al (2015) Diffusion-weighted MRI for the assessment of liver fibrosis: principles and applications. Biomed Res Int 2015:874201

    Article  PubMed  PubMed Central  Google Scholar 

  74. Papalavrentios L, Sinakos E, Chourmouzi D et al (2015) Value of 3 tesla diffusion-weighted magnetic resonance imaging for assessing liver fibrosis. Ann Gastroenterol 28:118–123

    PubMed  PubMed Central  Google Scholar 

  75. Zhang B, Liang L, Dong Y et al (2016) Intravoxel incoherent motion MR imaging for staging of hepatic fibrosis. PLoS One 11:e0147789

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  76. Wang QB, Zhu H, Liu HL et al (2012) Performance of magnetic resonance elastography and diffusion-weighted imaging for the staging of hepatic fibrosis: a meta-analysis. Hepatology 56:239–247

    Article  PubMed  Google Scholar 

  77. Bakan AA, Inci E, Bakan S et al (2012) Utility of diffusion-weighted imaging in the evaluation of liver fibrosis. Eur Radiol 22:682–687

    Article  PubMed  Google Scholar 

  78. 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 46:658–665

    Article  PubMed  CAS  Google Scholar 

  79. Sandrasegaran K, Akisik FM, Lin C et al (2009) Value of diffusion-weighted MRI for assessing liver fibrosis and cirrhosis. AJR Am J Roentgenol 193:1556–1560

    Article  PubMed  Google Scholar 

  80. Soylu A, Kilickesmez O, Poturoglu S et al (2010) Utility of diffusion-weighted MRI for assessing liver fibrosis in patients with chronic active hepatitis. Diagn Interv Radiol 16:204–208

    PubMed  Google Scholar 

  81. Yang Y, Song B, Wu B et al (2009) Assessment of disease activity and liver fibrosis in chronic viral hepatitis by magnetic resonance diffusion-weighted imaging. Zhongguo Yi Xue Ke Xue Yuan Xue Bao 31:155–159

    PubMed  Google Scholar 

  82. 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 

  83. 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 

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Acknowledgements

The authors would like to acknowledge Dr. Eric Diaz for his consultation and assistance with generating the T1rho maps.

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Authors and Affiliations

  1. Department of Radiology, MLC 5031, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave., Cincinnati, OH, 45229, USA

    Suraj D. Serai, Andrew T. Trout, Eric Diaz & Jonathan R. Dillman

  2. Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, PA, USA

    Suraj D. Serai

  3. Department of Pediatrics, Division of Gastroenterology, Hepatology and Nutrition, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA

    Alexander Miethke & Stavra A. Xanthakos

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  1. Suraj D. Serai
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  2. Andrew T. Trout
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  3. Alexander Miethke
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  4. Eric Diaz
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  5. Stavra A. Xanthakos
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  6. Jonathan R. Dillman
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Correspondence to Suraj D. Serai.

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Conflicts of interest

The authors have active research collaborations, without associated financial support, with Perspectum Diagnostics (related to cT1) and The Mayo Clinic (related to MR elastography).

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Serai, S.D., Trout, A.T., Miethke, A. et al. Putting it all together: established and emerging MRI techniques for detecting and measuring liver fibrosis. Pediatr Radiol 48, 1256–1272 (2018). https://doi.org/10.1007/s00247-018-4083-2

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  • DOI: https://doi.org/10.1007/s00247-018-4083-2

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