Sensitivity of chemical shift-encoded fat quantification to calibration of fat MR spectrum

• Published in: Magnetic resonance in medicine Vol. 75; no. 2; pp. 845 - 851
• Main Authors: Wang, Xiaoke, Hernando, Diego, Reeder, Scott B.
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.02.2016; Wiley Subscription Services, Inc
• Subjects: Calibration; Chemical equilibrium; Computer Simulation; fat quantification; fat spectrum; Fatty Liver - pathology; Humans; Image Processing, Computer-Assisted; In vivo methods and tests; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Magnetic Resonance Spectroscopy; nonalcoholic fatty liver disease; Proton density (concentration); proton density fat fraction; Protons; Sensitivity and Specificity; Spectra; spectral model of fat; fat spectrum; fat quantification; magnetic resonance imaging; nonalcoholic fatty liver disease; proton density fat fraction; spectral model of fat
• ISSN: 0740-3194; 1522-2594
• DOI: 10.1002/mrm.25681

Purpose To evaluate the impact of different fat spectral models on proton density fat fraction quantification using chemical shift‐encoded MRI (CSE‐MRI). Methods In a simulation study, spectral models of fat were compared pairwise. Comparison of magnitude fitting and mixed fitting was performed over a range of echo times and fat fractions. In vivo acquisitions from 41 patients were reconstructed using seven published spectral models of fat. T2‐corrected stimulated echo acquisition mode MR spectroscopy was used as a reference. Results The simulations demonstrated that imperfectly calibrated spectral models of fat result in biases that depend on echo times and fat fraction. Mixed fitting was more robust against this bias than magnitude fitting. Multipeak spectral models showed much smaller differences among themselves than from the single‐peak spectral model. In vivo studies showed that all multipeak models agreed better (for mixed fitting, the slope ranged from 0.967 to 1.045 using linear regression) with the reference standard than the single‐peak model (for mixed fitting, slope = 0.76). Conclusion It is essential to use a multipeak fat model for accurate quantification of fat with CSE‐MRI. Furthermore, fat quantification techniques using multipeak fat models are comparable, and no specific choice of spectral model has been shown to be superior to the rest. Magn Reson Med 75:845–851, 2016. © 2015 Wiley Periodicals, Inc.