Fat Quantification in the Abdomen

Topics in Magnetic Resonance Imaging

Volumn 26, Issue 6, 2017, Pages 221-227

  Hong, Cheng William ^a   Fazeli Dehkordy, Soudabeh ^a   Hooker, Jonathan C ^a   Hamilton, Gavin ^a   Sirlin, Claude B ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

fat fraction; fat quantification; hepatic steatosis; proton density fat fraction

Indexed keywords

FAT;

ADIPOSE TISSUE; COMPUTER ASSISTED TOMOGRAPHY; ECHOGRAPHY; FATTY LIVER; HUMAN; INTERMETHOD COMPARISON; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PANCREAS; PRIORITY JOURNAL; PROTON NUCLEAR MAGNETIC RESONANCE; REVIEW; ABDOMEN; DIAGNOSTIC IMAGING; INTRA-ABDOMINAL FAT; METABOLISM; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROCEDURES; REPRODUCIBILITY; X-RAY COMPUTED TOMOGRAPHY;

ABDOMEN; FATTY LIVER; HUMANS; INTRA-ABDOMINAL FAT; MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY OF RESULTS; TOMOGRAPHY, X-RAY COMPUTED;

EID: 85036531469     PISSN: 08993459     EISSN: 15361004     Source Type: Journal    
DOI: 10.1097/RMR.0000000000000141     Document Type: Review

References (85)

1. Brateman L. Chemical shift imaging: a review. Am J Roentgenol. 1986;146: 971-980.
2. Heiken JP, Lee JK, Dixon WT. Fatty infiltration of the liver: evaluation by proton spectroscopic imaging. Radiology. 1985;157:707-710.
3. Reeder SB, Sirlin CB. Quantification of liver fat with magnetic resonance imaging. Magn Reson Imaging Clin N Am. 2010;18:337-357.
4. 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.
5. 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: 749-759.
6. Tang A, Desai A, Hamilton G, et al. Accuracy of MR imaging-estimated proton density fat fraction for classification of dichotomized histologic steatosis grades in nonalcoholic fatty liver disease. Radiology. 2015;274: 416-425.
7. Negrete LM, Middleton MS, Clark L, et al. Inter-examination precision of magnitude-based MRI for estimation of segmental hepatic proton density fat fraction in obese subjects. J Magn Reson Imaging. 2014;39:1265-1271.
8. Le T-A, Chen J, Changchien C, et al. Effect of colesevelam on liver fat quantified by magnetic resonance in nonalcoholic steatohepatitis: a randomized controlled trial. Hepatology. 2012;56:922-932.
9. Browning JD, Szczepaniak LS, Dobbins R, et al. Prevalence of hepatic steatosis in an urban population in the United States: impact of ethnicity. Hepatology. 2004;40:1387-1395.
10. Loomba R, Sirlin CB, Ang B, et al. Ezetimibe for the treatment of nonalcoholic steatohepatitis: assessment by novel magnetic resonance imaging and magnetic resonance elastography in a randomized trial (MOZART trial). Hepatology. 2015;61:1239-1250.
11. Idilman IS, Tuzun A, Savas B, et al. Quantification of liver, pancreas, kidney, and vertebral body MRI-PDFF in non-alcoholic fatty liver disease. Abdom Imaging. 2015;40:1512-1519.
12. Adam SZ, Nikolaidis P, Horowitz JM, et al. Chemical shift MR imaging of the adrenal gland: principles, pitfalls, and applications. Radio Graphics. 2016;36:414-432.
13. Inan N, Arslan A, Akansel G, et al. Dynamic contrast enhanced MRI in the differential diagnosis of adrenal adenomas and malignant adrenal masses. Eur J Radiol. 2008;65:154-162.
14. Slapa RZ, Jakubowski W, Januszewicz A, et al. Discriminatory power of MRI for differentiation of adrenal non-adenomas vs adenomas evaluated by means of ROC analysis: can biopsy be obviated? Eur Radiol. 2000;10:95-104.
15. Rodacki K, Ramalho M, Dale BM, et al. Combined chemical shift imaging with early dynamic serial gadolinium-enhanced MRI in the characterization of adrenal lesions. Am J Roentgenol. 2014;203:99-106.
16. Kullberg J, Karlsson A-K, Stokland E, et al. Adipose tissue distribution in children: automated quantification using water and fat MRI. J Magn Reson Imaging. 2010;32:204-210.
17. Poonawalla AH, Sjoberg BP, Rehm JL, et al. Adipose tissue MRI for quantitative measurement of central obesity. J Magn Reson Imaging. 2013;37:707-716.
18. Thörmer G, Bertram HH, Garnov N, et al. Software for automated MRI-based quantification of abdominal fat and preliminary evaluation in morbidly obese patients. J Magn Reson Imaging. 2013;37:1144-1150.
19. Wald D, Teucher B, Dinkel J, et al. Automatic quantification of subcutaneous and visceral adipose tissue from whole-body magnetic resonance images suitable for large cohort studies. J Magn Reson Imaging. 2012;36:1421-1434.
20. Müller H-P, Raudies F, Unrath A, et al. Quantificationof human body fat tissue percentage by MRI. NMR Biomed. 2011;24:17-24.
21. Addeman BT, Kutty S, Perkins TG, et al. Validation of volumetric and single-slice MRI adipose analysis using a novel fully automated segmentation method. J Magn Reson Imaging. 2015;41:233-241.
22. Würslin C, Machann J, Rempp H, et al. Topography mapping of whole body adipose tissue using a fully automated and standardized procedure. J Magn Reson Imaging. 2010;31:430-439.
23. Borga M, Thomas EL, Romu T, et al. Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies. NMR Biomed. 2015;28:1747-1753.
24. Brennan DD, Whelan PF, Robinson K, et al. Rapid automated measurement of body fat distribution from whole-body MRI. Am J Roentgenol. 2005;185:418-423.
25. Karlsson A, Rosander J, Romu T, et al. Automatic and quantitative assessment of regional muscle volume by multi-atlas segmentation using whole-body water-fat MRI. J Magn Reson Imaging. 2015;41:1558-1569.
26. Thomas MS, Newman D, Leinhard OD, et al. Test-retest reliability of automated whole body and compartmental muscle volume measurements on a wide bore 3T MR system. Eur Radiol. 2014;24:2279-2291.
27. West J, Dahlqvist Leinhard O, Romu T, et al. Feasibility of MR-based body composition analysis in large scale population studies. PLoS One. 2016;11:e0163332.
28. Mitchell DG, Kim I, Chang TS, et al. Fatty liver. Chemical shift phase-difference and suppression magnetic resonance imaging techniques in animals, phantoms, and humans. Invest Radiol. 1991;26:1041-1052.
29. Qayyum A, Goh JS, Kakar S, et al. Accuracy of liver fat quantification at MR imaging: comparison of out-of-phase gradient-echo and fat-saturated fast spin-echo techniques-initial experience. Radiology. 2005;237:507-511.
30. Dixon WT. Simple proton spectroscopic imaging. Radiology. 1984;153: 189-194.
31. Reeder SB, Cruite I, Hamilton G, et al. Quantitative assessment of liver fat with magnetic resonance imaging and spectroscopy. J Magn Reson Imaging. 2011;34:729-749.
32. Reeder SB, Pineda AR, Wen Z, et al. Iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL): application with fast spin-echo imaging. Magn Reson Med. 2005;54:636-644.
33. Bydder M, Yokoo T, Hamilton G, et al. Relaxation effects in the quantification of fat using gradient echo imaging. Magn Reson Imaging. 2008;26:347-359.
34. Yu H, Shimakawa A, McKenzie CA, et al. Multiecho water-fat separation and simultaneous R 2∗ estimation with multifrequency fat spectrum modeling. Magn Reson Med. 2008;60:1122-1134.
35. Yu H, McKenzie CA, Shimakawa A, et al. Multiecho reconstruction for simultaneous water-fat decomposition and T2∗ estimation. J Magn Reson Imaging. 2007;26:1153-1161.
36. Bashir MR, Zhong X, Nickel MD, et al. Quantification of hepatic steatosis with a multistep adaptive fitting MRI approach: prospective validation against MR spectroscopy. AJR Am J Roentgenol. 2015;204:297-306.
37. Hamilton G, Yokoo T, Bydder M, et al. In vivo characterization of the liver fat 1H MR spectrum. NMR Biomed. 2011;24:784-790.
38. Kühn J-P, Hernando D, Munoz 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;265:133-142.
39. Hines CDG, Frydrychowicz A, Hamilton G, et al. 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. 2011;33:873-881.
40. Meisamy S, Hines CDG, 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;258:767-775.
41. Wang X, Hernando D, Reeder SB. Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum. Magn Reson Med. 2016;75:845-851.
42. Liu C-Y, 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;58:354-364.
43. Levin YS, Yokoo T, Wolfson T, et al. Effect of echo-sampling strategy on the accuracy of out-of-phase and in-phase multiecho gradient-echo MRI hepatic fat fraction estimation. J Magn Reson Imaging. 2014;39:567-575.
44. Yokoo T, Browning JD. Fat and iron quantification in the liver. Top Magn Reson Imaging. 2014;23:129-150.
45. Hernando D, Sharma SD, Aliyari Ghasabeh M, et al. Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom. Magn Reson Med. 2017;77:1516-1524.
46. Johnson BL, Schroeder ME, Wolfson T, et al. Effect of flip angle on the accuracy and repeatability of hepatic proton density fat fraction estimation by complex data-based, T1-independent, T2∗-corrected, spectrum-modeled MRI. J Magn Reson Imaging. 2014;39:440-447.
47. Kühn J-P, Hernando D, Mensel B, et al. Quantitative chemical shift-encoded MRI is an accurate method to quantify hepatic steatosis. J Magn Reson Imaging. 2014;39:1494-1501.
48. Horng DE, Hernando D, Hines CDG, et al. Comparison of R2∗ correction methods for accurate fat quantification in fatty liver. J Magn Reson Imaging. 2013;37:414-422.
49. Hu HH, Kim H-W, Nayak KS, et al. Comparison of fat-water MRI and single-voxel MRS in the assessment of hepatic and pancreatic fat fractions in humans. Obesity (Silver Spring). 2010;18:841-847.
50. Zhong X, Nickel MD, Kannengiesser SAR, et al. Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging. Magn Reson Med. 2014;72:1353-1365.
51. Szczepaniak LS, Nurenberg P, Leonard D, et al. Magnetic resonance spectroscopy to measure hepatic triglyceride content: prevalence of hepatic steatosis in the general population. Am J Physiol Endocrinol Metab. 2005;288:E462-E468.
52. Tang A, Rabasa-Lhoret R, Castel H, et al. Effects of insulin glargine and liraglutide therapy on liver fat as measured by magnetic resonance in patients with type 2 diabetes: a randomized trial. Diabetes Care. 2015;38:1339-1346.
53. Van Werven JR, Hoogduin JM, Nederveen AJ, et al. Reproducibility of 3.0 Tesla magnetic resonance spectroscopy for measuring hepatic fat content. J Magn Reson Imaging. 2009;30:444-448.
54. Piekarski J, Goldberg HI, Royal SA, et al. Difference between liver and spleen CT numbers in the normal adult: its usefulness in predicting the presence of diffuse liver disease. Radiology. 1980;137:727-729.
55. Limanond P, Raman SS, Lassman C, et al. Macrovesicular hepatic steatosis in living related liver donors: correlation between CT and histologic findings. Radiology. 2004;230:276-280.
56. Hamer OW, Aguirre DA, Casola G, et al. Imaging features of perivascular fatty infiltration of the liver: initial observations. Radiology. 2005;237:159-169.
57. Yajima Y, Narui T, Ishii M, et al. Computed tomography in the diagnosis of fatty liver: total lipid content and computed tomography number. Tohoku J Exp Med. 1982;136:337-342.
58. Johnston RJ, Stamm ER, Lewin JM, et al. Diagnosis of fatty infiltration of the liver on contrast enhanced CT: limitations of liver-minus-spleen attenuation difference measurements. Abdom Imaging. 1998;23:409-415.
59. Jacobs JE, Birnbaum BA, Shapiro MA, et al. Diagnostic criteria for fatty infiltration of the liver on contrast-enhanced helical CT. Am J Roentgenol. 1998;171:659-664.
60. Lawrence DA, Oliva IB, Israel GM. Detection of hepatic steatosis on contrast-enhanced CT images: diagnostic accuracy of identification of areas of presumed focal fatty sparing. Am J Roentgenol. 2012;199:44-47.
61. Yajima Y, Ohta K, Narui T, et al. Ultrasonographical diagnosis of fatty liver: significance of the liver-kidney contrast. Tohoku J Exp Med. 1983;139:43-50.
62. Ballestri S, Lonardo A, Romagnoli D, et al. Ultrasonographic fatty liver indicator, a novel score which rules out NASH and is correlated with metabolic parameters in NAFLD. Liver Int. 2012;32:1242-1252.
63. Hamaguchi M, Kojima T, Itoh Y, et al. The severity of ultrasonographic findings in nonalcoholic fatty liver disease reflects the metabolic syndrome and visceral fat accumulation. Am J Gastroenterol. 2007;102:2708-2715.
64. Fishbein M, Castro F, Cheruku S, et al. Hepatic MRI for fat quantitation: its relationship to fat morphology, diagnosis, and ultrasound. J Clin Gastroenterol. 2005;39:619-625.
65. Dasarathy S, Dasarathy J, Khiyami A, et al. Validity of real time ultrasound in the diagnosis of hepatic steatosis: a prospective study. J Hepatol. 2009;51:1061-1067.
66. Saadeh S, Younossi ZM, Remer EM, et al. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology. 2002;123:745-750.
67. Strauss S, Gavish E, Gottlieb P, et al. Interobserver and intraobserver variability in the sonographic assessment of fatty liver. AJR Am J Roentgenol. 2007;189:W320-W323.
68. Bohte AE, Van Werven JR, Bipat S, et al. 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. 2011;21:87-97.
69. Lédinghen V, Vergniol J, Foucher J, et al. Non-invasive diagnosis of liver steatosis using controlled attenuation parameter (CAP) and transient elastography. Liver Int. 2012;32:911-918.
70. Myers RP, Pollett A, Kirsch R, et al. Controlled attenuation parameter (CAP): a noninvasive method for the detection of hepatic steatosis based on transient elastography. Liver Int. 2012;32:902-910.
71. Forestier N, Gaus A, Herrmann E, et al. Acoustic radiation force impulse imaging for evaluation of antiviral treatment response in chronic hepatitis C. J Gastrointestin Liver Dis. 2012;21:367-373.
72. Yao LX, Zagzebski JA, Madsen EL. Backscatter coefficient measurements using a reference phantom to extract depth-dependent instrumentation factors. Ultrason Imaging. 1990;12:58-70.
73. Han A, Erdman JW, Simpson DG, et al. Early detection offatty liver disease in mice via quantitative ultrasound. In: 2014 IEEE International Ultrasonics Symposium. IEEE; 2014:2363-2366. doi:10.1109/ULTSYM.2014.0589.
74. Ghoshal G, Lavarello RJ, Kemmerer JP, et al. Ex vivo study of quantitative ultrasound parameters in fatty rabbit livers. Ultrasound Med Biol. 2012;38:2238-2248.
75. Lin SC, Heba E, Wolfson T, et al. Noninvasive diagnosis of nonalcoholic fatty liver disease and quantification of liver fat using a new quantitative ultrasound technique. Clin Gastroenterol Hepatol. 2015;13:1337.e6-1345.e6.
76. Li J, Xie Y, Yuan F, et al. Noninvasive quantification of pancreatic fat in healthy male population using chemical shift magnetic resonance imaging. Pancreas. 2011;40:295-299.
77. Patel NS, Peterson MR, Brenner DA, et al. Association between novel MRI-estimated pancreatic fat and liver histology-determined steatosis and fibrosis in non-alcoholic fatty liver disease. Aliment Pharmacol Ther. 2013;37:630-639.
78. Livingstone RS, Begovatz P, Kahl S, et al. Initial clinical application of modified Dixon with flexible echo times: hepatic and pancreatic fat assessments in comparison with 1H MRS. Magn Reson Mater Physics Biol Med. 2014;27:397-405.
79. Kovanlikaya A, Mittelman SD, Ward A, et al. Obesity and fat quantification in lean tissues using three-point Dixon MR imaging. Pediatr Radiol. 2005;35:601-607.
80. Yoon JH, Lee JM, Lee KB, et al. Pancreatic steatosis and fibrosis: quantitative assessment with preoperative multiparametric MR imaging. Radiology. 2016;279:140-150.
81. Kim SY, Kim H, Cho JY, et al. Quantitative assessment of pancreatic fat by using unenhanced CT: pathologic correlation and clinical implications. Radiology. 2014;271:104-112.
82. Ju Y, Liu A, Dong Y, et al. The value of nonenhanced single-source dual-energy CT for differentiating metastases from adenoma in adrenal glands. Acad Radiol. 2015;22:834-839.
83. Namimoto T, Yamashita Y, Mitsuzaki K, et al. Adrenal masses: quantification of fat content with double-echo chemical shift in-phase and opposed-phase FLASH MR images for differentiation of adrenal adenomas. Radiology. 2001;218:642-646.
84. Peng Q, McColl RW, Ding Y, et al. Automated method for accurate abdominal fat quantification on water-saturated magnetic resonance images. J Magn Reson Imaging. 2007;26:738-746.
85. Ludwig UA, Klausmann F, Baumann S, et al. Whole-body MRI-based fat quantification: a comparison to air displacement plethysmography. J Magn Reson Imaging. 2014;40:1437-1444.