Advertisement

Pediatric Radiology

, Volume 48, Issue 7, pp 941–953 | Cite as

Free-breathing quantification of hepatic fat in healthy children and children with nonalcoholic fatty liver disease using a multi-echo 3-D stack-of-radial MRI technique

  • Tess Armstrong
  • Karrie V. Ly
  • Smruthi Murthy
  • Shahnaz Ghahremani
  • Grace Hyun J. Kim
  • Kara L. Calkins
  • Holden H. Wu
Original Article

Abstract

Background

In adults, noninvasive chemical shift encoded Cartesian magnetic resonance imaging (MRI) and single-voxel magnetic resonance (MR) spectroscopy (SVS) accurately quantify hepatic steatosis but require breath-holding. In children, especially young and sick children, breath-holding is often limited or not feasible. Sedation can facilitate breath-holding but is highly undesirable. For these reasons, there is a need to develop free-breathing MRI technology that accurately quantifies steatosis in all children.

Objective

This study aimed to compare non-sedated free-breathing multi-echo 3-D stack-of-radial (radial) MRI versus standard breath-holding MRI and SVS techniques in a group of children for fat quantification with respect to image quality, accuracy and repeatability.

Materials and methods

Healthy children (n=10, median age [±interquartile range]: 10.9 [±3.3] years) and overweight children with nonalcoholic fatty liver disease (NAFLD) (n=9, median age: 15.2 [±3.2] years) were imaged at 3 Tesla using free-breathing radial MRI, breath-holding Cartesian MRI and breath-holding SVS. Acquisitions were performed twice to assess repeatability (within-subject mean difference, MDwithin). Images and hepatic proton-density fat fraction (PDFF) maps were scored for image quality. Free-breathing and breath-holding PDFF were compared using linear regression (correlation coefficient, r and concordance correlation coefficient, ρc) and Bland-Altman analysis (mean difference). P<0.05 was considered significant.

Results

In patients with NAFLD, free-breathing radial MRI demonstrated significantly less motion artifacts compared to breath-holding Cartesian (P<0.05). Free-breathing radial PDFF demonstrated a linear relationship (P<0.001) versus breath-holding SVS PDFF and breath-holding Cartesian PDFF with r=0.996 and ρc=0.994, and r=0.997 and ρc=0.995, respectively. The mean difference in PDFF between free-breathing radial MRI, breath-holding Cartesian MRI and breath-holding SVS was <0.7%. Repeated free-breathing radial MRI had MDwithin=0.25% for PDFF.

Conclusion

In this pediatric study, non-sedated free-breathing radial MRI provided accurate and repeatable hepatic PDFF measurements and improved image quality, compared to standard breath-holding MR techniques.

Keywords

Children Fat Liver Magnetic resonance imaging Nonalcoholic fatty liver disease Quantification Radial multi-echo sequence 

Notes

Acknowledgments

The authors thank Aaron Scheffler, Dr. Joanna Yeh, Barbara Lee, Tammy Floore, Glen Nyborg and Sergio Godinez at University of California Los Angeles (UCLA) for their help with this project. This work acknowledges the use of the International Society of Magnetic Resonance in Medicine Fat-Water Toolbox (http://ismrm.org/workshops/FatWater12/data.htm).

Research reported in this publication was supported in part by a UCLA Radiology Department Exploratory Research Grant.

Compliance with ethical standards

Conflicts of interest

T. Armstrong and H. H. Wu receive institutional research support from Siemens Healthineers.

References

  1. 1.
    Centers for Disease Control and Prevention. Overweight and Obesity. https://www.cdc.gov/obesity/data/childhood.html. Accessed 20 Nov 2017
  2. 2.
    Schwimmer JB, Deutsch R, Kahen T et al (2006) Prevalence of fatty liver in children and adolescents. Pediatrics 118:1388–1393CrossRefGoogle Scholar
  3. 3.
    Feldstein AE, Charatcharoenwitthaya P, Treeprasertsuk S et al (2009) The natural history of non-alcoholic fatty liver disease in children: a follow-up study for up to 20 years. Gut 58:1538–1544CrossRefPubMedCentralGoogle Scholar
  4. 4.
    Pardee PE, Lavine JE, Schwimmer JB (2009) Diagnosis and treatment of pediatric nonalcoholic steatohepatitis and the implications for bariatric surgery. Semin Pediatr Surg 18:144–151CrossRefPubMedCentralGoogle Scholar
  5. 5.
    Younossi ZM (2008) Review article: current management of non-alcoholic fatty liver disease and non-alcoholic steatohepatitis. Aliment Pharmacol Ther 28:2–12CrossRefGoogle Scholar
  6. 6.
    Uppal V, Mansoor S, Furuya KN (2016) Pediatric non-alcoholic fatty liver disease. Curr Gastroenterol Rep 18:24CrossRefGoogle Scholar
  7. 7.
    Della Corte C, Vajro P, Socha P et al (2014) Pediatric non-alcoholic fatty liver disease: recent advances. Clin Res Hepatol Gastroenterol 38:419–422CrossRefGoogle Scholar
  8. 8.
    Tapper EB, Lok AS-F (2017) Use of liver imaging and biopsy in clinical practice. N Engl J Med 377:756–768CrossRefGoogle Scholar
  9. 9.
    Sumida Y, Nakajima A, Itoh Y (2014) Limitations of liver biopsy and non-invasive diagnostic tests for the diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis. World J Gastroenterol 20:475–485CrossRefPubMedCentralGoogle Scholar
  10. 10.
    Ovchinsky N, Moreira RK, Lefkowitch JH et al (2012) Liver biopsy in modern clinical practice: a pediatric point-of-view. Adv Anat Pathol 19:250–262CrossRefPubMedCentralGoogle Scholar
  11. 11.
    Manning DS, Afdhal NH (2008) Diagnosis and quantitation of fibrosis. Gastroenterology 134:1670–1681CrossRefGoogle Scholar
  12. 12.
    Loomba R, Sirlin CB, Schwimmer JB et al (2009) Advances in pediatric nonalcoholic fatty liver disease. Hepatology 50:1282–1293CrossRefPubMedCentralGoogle Scholar
  13. 13.
    Lee SS, Park SH (2014) Radiologic evaluation of nonalcoholic fatty liver disease. World J Gastroenterol 20:7392–7402CrossRefPubMedCentralGoogle Scholar
  14. 14.
    Szczepaniak LS, Nurenberg P, Leonard D et al (2005) Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab 288:E462–E468CrossRefGoogle Scholar
  15. 15.
    Bohte AE, van Werven JR, Bipat S et al (2011) The diagnostic accuracy of US, CT, MRI and H-1-MRS for the evaluation of hepatic steatosis compared with liver biopsy: a meta-analysis. Eur Radiol 21:87–97CrossRefGoogle Scholar
  16. 16.
    Georgoff P, Thomasson D, Louie A et al (2012) Hydrogen-1 MR spectroscopy for measurement and diagnosis of hepatic steatosis. AJR Am J Roentgenol 199:2–7CrossRefPubMedCentralGoogle Scholar
  17. 17.
    Meisamy S, Hines CDG, Hamilton G et al (2011) Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy. Radiology 258:767–775CrossRefPubMedCentralGoogle Scholar
  18. 18.
    Hines CDG, Yu H, Shimakawa A et al (2009) T1 independent, T2* corrected MRI with accurate spectral modeling for quantification of fat: validation in a fat-water-SPIO phantom. J Magn Reson Imaging 30:1215–1222CrossRefPubMedCentralGoogle Scholar
  19. 19.
    Achmad E, Yokoo T, Hamilton G et al (2015) Feasibility of and agreement between MR imaging and spectroscopic estimation of hepatic proton density fat fraction in children with known or suspected nonalcoholic fatty liver disease. Abdom Imaging 40:3084–3090CrossRefPubMedCentralGoogle Scholar
  20. 20.
    Reeder SB, Cruite I, Hamilton G et al (2011) Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging 34:729–749CrossRefGoogle Scholar
  21. 21.
    Koh H, Kim S, Kim MJ et al (2015) Hepatic fat quantification magnetic resonance for monitoring treatment response in pediatric nonalcoholic steatohepatitis. World J Gastroenterol 21:9741–9748CrossRefPubMedCentralGoogle Scholar
  22. 22.
    Schwimmer JB, Middleton MS, Behling C et al (2015) Magnetic resonance imaging and liver histology as biomarkers of hepatic steatosis in children with nonalcoholic fatty liver disease. Hepatology 61:1887–1895CrossRefPubMedCentralGoogle Scholar
  23. 23.
    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
  24. 24.
    Bashir MR, Zhong X, Nickel MD et al (2015) Quantification of hepatic steatosis with a multistep adaptive fitting MRI approach: prospective validation against MR spectroscopy. AJR Am J Roentgenol 204:297–306CrossRefGoogle Scholar
  25. 25.
    Kühn J-P, Hernando D, Muñoz del Rio A et al (2012) Effect of multipeak spectral modeling of fat for liver iron and fat quantification: correlation of biopsy with MR imaging results. Radiology 265:133–142CrossRefPubMedCentralGoogle Scholar
  26. 26.
    Idilman IS, Aniktar H, Idilman R et al (2013) Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology 267:767–775CrossRefGoogle Scholar
  27. 27.
    Yokoo T, Shiehmorteza M, Hamilton G et al (2011) Estimation of hepatic proton-density fat fraction by using MR imaging at 3.0 T. Radiology 258:749–759CrossRefPubMedCentralGoogle Scholar
  28. 28.
    Zhong X, Nickel MD, Kannengiesser SAR et al (2014) Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med 72:1353–1365CrossRefGoogle Scholar
  29. 29.
    Chavhan GB, Babyn PS, Vasanawala SS (2013) Abdominal MR imaging in children: motion compensation, sequence optimization, and protocol organization. Radiographics 33:703–719CrossRefGoogle Scholar
  30. 30.
    Courtier J, Rao AG, Anupindi SA (2017) Advanced imaging techniques in pediatric body MRI. Pediatr Radiol 47:522–533CrossRefGoogle Scholar
  31. 31.
    Jaimes C, Gee MS (2016) Strategies to minimize sedation in pediatric body magnetic resonance imaging. Pediatr Radiol 46:916–927CrossRefGoogle Scholar
  32. 32.
    Arboleda C, Aguirre-Reyes D, García MP et al (2016) Total liver fat quantification using three-dimensional respiratory self-navigated MRI sequence. Magn Reson Med 76:1400–1409CrossRefGoogle Scholar
  33. 33.
    Motosugi U, Hernando D, Bannas P et al (2015) Quantification of liver fat with respiratory-gated quantitative chemical shift encoded MRI. J Magn Reson Imaging 42:1241–1248CrossRefPubMedCentralGoogle Scholar
  34. 34.
    Malamateniou C, Malik SJ, Counsell SJ et al (2013) Motion-compensation techniques in neonatal and fetal MR imaging. AJNR Am J Neuroradiol 34:1124–1136CrossRefGoogle Scholar
  35. 35.
    Fujinaga Y, Kitou Y, Ohya A et al (2016) Advantages of radial volumetric breath-hold examination (VIBE) with k-space weighted image contrast reconstruction (KWIC) over Cartesian VIBE in liver imaging of volunteers simulating inadequate or no breath-holding ability. Eur Radiol 26:2790–2797CrossRefGoogle Scholar
  36. 36.
    Armstrong T, Dregely I, Stemmer A et al (2018) Free-breathing liver fat quantification using a multiecho 3D stack-of-radial technique. Magn Reson Med 79:370–382CrossRefGoogle Scholar
  37. 37.
    Block KT, Chandarana H, Milla S et al (2014) Towards routine clinical use of radial stack-of-stars 3D gradient-echo sequences for reducing motion sensitivity. J Korean Soc Magn Reson Med 18:87–106CrossRefGoogle Scholar
  38. 38.
    Armstrong T, Martin T, Stemmer A, et al (2017) Free-breathing fat quantification in the liver using a multiecho 3D stack-of-radial technique: investigation of motion compensation and quantification accuracy. Proc. Int. Soc. Magn. Reson. Med. 25th. p 363Google Scholar
  39. 39.
    Breuer FA, Blaimer M, Heidemann RM et al (2005) Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging. Magn Reson Med 53:1–8CrossRefGoogle Scholar
  40. 40.
    Pineda N, Sharma P, Xu Q et al (2009) Measurement of hepatic lipid: high-speed T2-corrected multiecho acquisition at 1H MR spectroscopy--a rapid and accurate technique. Radiology 252:568–576CrossRefGoogle Scholar
  41. 41.
    Ren J, Dimitrov I, Sherry AD et al (2008) Composition of adipose tissue and marrow fat in humans by 1H NMR at 7 Tesla. J Lipid Res 49:2055–2062CrossRefPubMedCentralGoogle Scholar
  42. 42.
    Hernando D, Kellman P, Haldar JP et al (2010) Robust water/fat separation in the presence of large field inhomogeneities using a graph cut algorithm. Magn Reson Med 63:79–90PubMedCentralGoogle Scholar
  43. 43.
    International Society of Magnetic Resonance in Medicine (2012) ISMRM Fat Water Toolbox. https://www.ismrm.org/workshops/FatWater12/data.htm. Accessed 27 Feb 2012
  44. 44.
    Gleich DF (2009) Models and algorithms for pagerank sensitivity. Dissertation. Stanford UniversityGoogle Scholar
  45. 45.
    Liu CY, McKenzie CA, Yu H et al (2007) Fat quantification with IDEAL gradient echo imaging: correction of bias from T1 and noise. Magn Reson Med 58:354–364CrossRefGoogle Scholar
  46. 46.
    Mann HB, Whitney DR (1947) On a test of whether one of two random variables is stochastically larger than the other. Ann Math Stat 18:50–60CrossRefGoogle Scholar
  47. 47.
    Sawilowsky SS (2005) Misconceptions leading to choosing the t test over the Wilcoxon Mann-Whitney test for shift in location parameter. J Mod Appl Stat Methods 4:598–600CrossRefGoogle Scholar
  48. 48.
    Bowker AH (1948) A test for symmetry in contingency tables. J Am Stat Assoc 43:572–574CrossRefGoogle Scholar
  49. 49.
    Williams S (1996) Pearson’s correlation coefficient. N Z Med J 109:38Google Scholar
  50. 50.
    Lin LI (1989) A concordance correlation coefficient to evaluate reproducibility. Biometrics 45:255–268CrossRefGoogle Scholar
  51. 51.
    Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135–160CrossRefGoogle Scholar
  52. 52.
    Bartlett JW, Frost C (2008) Reliability, repeatability and reproducibility: analysis of measurement errors in continuous variables. Ultrasound Obstet Gynecol 31:466–475CrossRefGoogle Scholar
  53. 53.
    Obuchowski NA, Reeves AP, Huang EP et al (2014) Quantitative imaging biomarkers: a review of statistical methods for computer algorithm comparisons. Stat Methods Med Res 24:68–106CrossRefGoogle Scholar
  54. 54.
    Rinella ME (2015) Nonalcoholic fatty liver disease: a systematic review. JAMA 313:2263–2273CrossRefGoogle Scholar
  55. 55.
    Yu H, McKenzie CA, Shimakawa A et al (2007) Multiecho reconstruction for simultaneous water-fat decomposition and T2* estimation. J Magn Reson Imaging 26:1153–1161CrossRefGoogle Scholar
  56. 56.
    Venkatesh SK, Hennedige T, Johnson GB et al (2017) Imaging patterns and focal lesions in fatty liver: a pictorial review. Abdom Radiol 42:1374–1392CrossRefGoogle Scholar
  57. 57.
    Lee H, Jun DW, Kang BK et al (2017) Estimating of hepatic fat amount using MRI proton density fat fraction in a real practice setting. Medicine (Baltimore) 96:e7778CrossRefGoogle Scholar
  58. 58.
    Hamer OW, Aguirre DA, Casola G et al (2006) Fatty liver: imaging patterns and pitfalls. Radiographics 26:1637–1653CrossRefGoogle Scholar
  59. 59.
    Özcan HN, Oğuz B, Haliloğlu M et al (2015) Imaging patterns of fatty liver in pediatric patients. Diagn Interv Radiol 21:355–360CrossRefPubMedCentralGoogle Scholar
  60. 60.
    Fazeli Dehkordy S, Wolfson T, William Hong C et al (2017) Liver fat reduction following bariatric weight loss surgery is greater in the right lobe of the liver. Proc. Int. Soc. Magn. Reson. Med. 25th. p 123Google Scholar
  61. 61.
    Uecker M, Lai P, Murphy MJ et al (2014) ESPIRiT - an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med 71:990–1001CrossRefPubMedCentralGoogle Scholar
  62. 62.
    Feng L, Axel L, Chandarana H et al (2016) XD-GRASP: golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing. Magn Reson Med 75:775–788CrossRefGoogle Scholar
  63. 63.
    Horng DE, Hernando D, Reeder SB (2017) Quantification of liver fat in the presence of iron overload. J Magn Reson Imaging 45:428–439CrossRefGoogle Scholar
  64. 64.
    Hankins JS, McCarville MB, Loeffler RB et al (2009) R2* magnetic resonance imaging of the liver in patients with iron overload. Blood 113:4853–4855CrossRefPubMedCentralGoogle Scholar
  65. 65.
    Manco M, Alisi A, Real JMF et al (2011) Early interplay of intra-hepatic iron and insulin resistance in children with non-alcoholic fatty liver disease. J Hepatol 55:647–653CrossRefGoogle Scholar
  66. 66.
    St Pierre TG, Clark PR, Chua-anusorn W et al (2005) Noninvasive measurement and imaging of liver iron concentrations using proton magnetic resonance. Blood 105:855–861CrossRefGoogle Scholar
  67. 67.
    Doyle EK, Toy K, Valdez B et al (2018) Ultra-short echo time images quantify high liver iron. Magn Reson Med 79:1579–1585CrossRefGoogle Scholar
  68. 68.
    Krafft AJ, Loeffler RB, Song R et al (2017) Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 tesla. Magn Reson Med 78:1839–1851CrossRefGoogle Scholar
  69. 69.
    Tipirneni-Sajja A, Krafft AJ, McCarville MB et al (2017) Radial ultrashort TE imaging removes the need for breath-holding in hepatic iron overload quantification by R2* MRI. Am J Roentgenol 209:187–194CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Tess Armstrong
    • 1
    • 2
  • Karrie V. Ly
    • 3
  • Smruthi Murthy
    • 3
  • Shahnaz Ghahremani
    • 1
  • Grace Hyun J. Kim
    • 1
  • Kara L. Calkins
    • 3
  • Holden H. Wu
    • 1
    • 2
  1. 1.Department of Radiological Sciences, David Geffen School of MedicineUniversity of California Los AngelesLos AngelesUSA
  2. 2.Physics and Biology in MedicineUniversity of California Los AngelesLos AngelesUSA
  3. 3.Department of Pediatrics, Division of Neonatology, David Geffen School of MedicineUniversity of California Los Angeles, Mattel Children’s HospitalLos AngelesUSA

Personalised recommendations