Literature DB >> 21248233

Quantification of hepatic steatosis with T1-independent, T2-corrected MR imaging with spectral modeling of fat: blinded comparison with MR spectroscopy.

Sina Meisamy1, Catherine D G Hines, Gavin Hamilton, Claude B Sirlin, Charles A McKenzie, Huanzhou Yu, Jean H Brittain, Scott B Reeder.   

Abstract

PURPOSE: To prospectively compare an investigational version of a complex-based chemical shift-based fat fraction magnetic resonance (MR) imaging method with MR spectroscopy for the quantification of hepatic steatosis.
MATERIALS AND METHODS: This study was approved by the institutional review board and was HIPAA compliant. Written informed consent was obtained before all studies. Fifty-five patients (31 women, 24 men; age range, 24-71 years) were prospectively imaged at 1.5 T with quantitative MR imaging and single-voxel MR spectroscopy, each within a single breath hold. The effects of T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction on fat quantification with MR imaging were investigated by reconstructing fat fraction images from the same source data with different combinations of error correction. Single-voxel T2-corrected MR spectroscopy was used to measure fat fraction and served as the reference standard. All MR spectroscopy data were postprocessed at a separate institution by an MR physicist who was blinded to MR imaging results. Fat fractions measured with MR imaging and MR spectroscopy were compared statistically to determine the correlation (r(2)), and the slope and intercept as measures of agreement between MR imaging and MR spectroscopy fat fraction measurements, to determine whether MR imaging can help quantify fat, and examine the importance of T2 correction, spectral modeling of fat, and eddy current correction. Two-sided t tests (significance level, P = .05) were used to determine whether estimated slopes and intercepts were significantly different from 1.0 and 0.0, respectively. Sensitivity and specificity for the classification of clinically significant steatosis were evaluated.
RESULTS: Overall, there was excellent correlation between MR imaging and MR spectroscopy for all reconstruction combinations. However, agreement was only achieved when T2 correction, spectral modeling of fat, and magnitude fitting for eddy current correction were used (r(2) = 0.99; slope ± standard deviation = 1.00 ± 0.01, P = .77; intercept ± standard deviation = 0.2% ± 0.1, P = .19).
CONCLUSION: T1-independent chemical shift-based water-fat separation MR imaging methods can accurately quantify fat over the entire liver, by using MR spectroscopy as the reference standard, when T2 correction, spectral modeling of fat, and eddy current correction methods are used. © RSNA, 2011.

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Year:  2011        PMID: 21248233      PMCID: PMC3042638          DOI: 10.1148/radiol.10100708

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  45 in total

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2.  Fat quantification with IDEAL gradient echo imaging: correction of bias from T(1) and noise.

Authors:  Chia-Ying Liu; Charles A McKenzie; Huanzhou Yu; Jean H Brittain; Scott B Reeder
Journal:  Magn Reson Med       Date:  2007-08       Impact factor: 4.668

3.  Optimal phased-array combination for spectroscopy.

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4.  Nonalcoholic fatty liver disease and risk of future cardiovascular events among type 2 diabetic patients.

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Journal:  Diabetes       Date:  2005-12       Impact factor: 9.461

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6.  Prevalence of overweight and obesity in the United States, 1999-2004.

Authors:  Cynthia L Ogden; Margaret D Carroll; Lester R Curtin; Margaret A McDowell; Carolyn J Tabak; Katherine M Flegal
Journal:  JAMA       Date:  2006-04-05       Impact factor: 56.272

7.  Water-fat separation with IDEAL gradient-echo imaging.

Authors:  Scott B Reeder; Charles A McKenzie; Angel R Pineda; Huanzhou Yu; Ann Shimakawa; Anja C Brau; Brian A Hargreaves; Garry E Gold; Jean H Brittain
Journal:  J Magn Reson Imaging       Date:  2007-03       Impact factor: 4.813

8.  T1 independent, T2* corrected MRI with accurate spectral modeling for quantification of fat: validation in a fat-water-SPIO phantom.

Authors:  Catherine D G Hines; Huanzhou Yu; Ann Shimakawa; Charles A McKenzie; Jean H Brittain; Scott B Reeder
Journal:  J Magn Reson Imaging       Date:  2009-11       Impact factor: 4.813

9.  Measurement of hepatic lipid: high-speed T2-corrected multiecho acquisition at 1H MR spectroscopy--a rapid and accurate technique.

Authors:  Nashiely Pineda; Puneet Sharma; Qin Xu; Xiaoping Hu; Miriam Vos; Diego R Martin
Journal:  Radiology       Date:  2009-06-22       Impact factor: 11.105

10.  T2* relaxometry in liver, pancreas, and spleen in a healthy cohort of one hundred twenty-nine subjects-correlation with age, gender, and serum ferritin.

Authors:  Nina F Schwenzer; Jürgen Machann; Michael M Haap; Petros Martirosian; Christina Schraml; Gerd Liebig; Norbert Stefan; Hans-Ulrich Häring; Claus D Claussen; Andreas Fritsche; Fritz Schick
Journal:  Invest Radiol       Date:  2008-12       Impact factor: 6.016

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  184 in total

1.  R*(2) mapping in the presence of macroscopic B₀ field variations.

Authors:  Diego Hernando; Karl K Vigen; Ann Shimakawa; Scott B Reeder
Journal:  Magn Reson Med       Date:  2011-12-09       Impact factor: 4.668

Review 2.  Quantitative Assessment of Liver Fat with Magnetic Resonance Imaging and Spectroscopy.

Authors:  Scott B Reeder; Irene Cruite; Gavin Hamilton; Claude B Sirlin
Journal:  J Magn Reson Imaging       Date:  2011-09-16       Impact factor: 4.813

3.  Liver steatosis: concordance of MR imaging and MR spectroscopic data with histologic grade.

Authors:  Susan M Noworolski; Maggie M Lam; Raphael B Merriman; Linda Ferrell; Aliya Qayyum
Journal:  Radiology       Date:  2012-07       Impact factor: 11.105

4.  Free-breathing liver fat and R 2 quantification using motion-corrected averaging based on a nonlocal means algorithm.

Authors:  Huiwen Luo; Ante Zhu; Curtis N Wiens; Jitka Starekova; Ann Shimakawa; Scott B Reeder; Kevin M Johnson; Diego Hernando
Journal:  Magn Reson Med       Date:  2020-08-01       Impact factor: 4.668

5.  Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis.

Authors:  An Tang; Justin Tan; Mark Sun; Gavin Hamilton; Mark Bydder; Tanya Wolfson; Anthony C Gamst; Michael Middleton; Elizabeth M Brunt; Rohit Loomba; Joel E Lavine; Jeffrey B Schwimmer; Claude B Sirlin
Journal:  Radiology       Date:  2013-02-04       Impact factor: 11.105

6.  Association between novel MRI-estimated pancreatic fat and liver histology-determined steatosis and fibrosis in non-alcoholic fatty liver disease.

Authors:  N S Patel; M R Peterson; D A Brenner; E Heba; C Sirlin; R Loomba
Journal:  Aliment Pharmacol Ther       Date:  2013-02-05       Impact factor: 8.171

7.  In vivo triglyceride composition of abdominal adipose tissue measured by 1 H MRS at 3T.

Authors:  Gavin Hamilton; Alexandra N Schlein; Michael S Middleton; Catherine A Hooker; Tanya Wolfson; Anthony C Gamst; Rohit Loomba; Claude B Sirlin
Journal:  J Magn Reson Imaging       Date:  2016-08-29       Impact factor: 4.813

Review 8.  Liver fat imaging-a clinical overview of ultrasound, CT, and MR imaging.

Authors:  Yingzhen N Zhang; Kathryn J Fowler; Gavin Hamilton; Jennifer Y Cui; Ethan Z Sy; Michelle Balanay; Jonathan C Hooker; Nikolaus Szeverenyi; Claude B Sirlin
Journal:  Br J Radiol       Date:  2018-06-06       Impact factor: 3.039

9.  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.

Authors:  Tess Armstrong; Karrie V Ly; Smruthi Murthy; Shahnaz Ghahremani; Grace Hyun J Kim; Kara L Calkins; Holden H Wu
Journal:  Pediatr Radiol       Date:  2018-05-04

Review 10.  Measurement of liver fat fraction and iron with MRI and MR spectroscopy techniques.

Authors:  Puneet Sharma; Maria Altbach; Jean-Philippe Galons; Bobby Kalb; Diego R Martin
Journal:  Diagn Interv Radiol       Date:  2014 Jan-Feb       Impact factor: 2.630

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