Sources of systematic error in proton density fat fraction (PDFF) quantification in the liver evaluated from magnitude images with different numbers of echoes

• Published in: NMR in biomedicine Vol. 31; no. 1
• Main Authors: Bydder, Mark, Hamilton, Gavin, Rochefort, Ludovic, Desai, Ajinkya, Heba, Elhamy R., Loomba, Rohit, Schwimmer, Jeffrey B., Szeverenyi, Nikolaus M., Sirlin, Claude B.
• Format: Journal Article
• Language: English
• Published: England Wiley Subscription Services, Inc 01.01.2018; Wiley
• Subjects: Adiposity; Adolescent; Adult; Aged; Bias; Biological products; Child; Decay; Engineering Sciences; Errors; fat quantification; Female; Frequency shift; Humans; Life Sciences; Liver; Liver - metabolism; Magnetic Resonance Imaging; Male; Middle Aged; NAFLD; NMR; Nuclear magnetic resonance; PDFF; Physics; Proton density (concentration); Protons; Regression Analysis; Spectroscopy; Spectrum analysis; Young Adult; PDFF; fat quantification; NAFLD; liver; bias
• ISSN: 0952-3480; 1099-1492; 1099-1492
• DOI: 10.1002/nbm.3843

The purpose of this work was to investigate sources of bias in magnetic resonance imaging (MRI) liver fat quantification that lead to a dependence of the proton density fat fraction (PDFF) on the number of echoes. This was a retrospective analysis of liver MRI data from 463 subjects. The magnitude signal variation with TE from spoiled gradient echo images was curve fitted to estimate the PDFF using a model that included monoexponential R2* decay and a multi‐peak fat spectrum. Additional corrections for non‐exponential decay (Gaussian), bi‐exponential decay, degree of fat saturation, water frequency shift and noise bias were introduced. The fitting error was minimized with respect to 463 × 3 = 1389 subject‐specific parameters and seven additional parameters associated with these corrections. The effect on PDFF was analyzed, notably the dependence on the number of echoes. The effects on R2* were also analyzed. The results showed that the inclusion of bias corrections resulted in an increase in the quality of fit (r2) in 427 of 463 subjects (i.e. 92.2%) and a reduction in the total fitting error (residual norm) of 43.6%. This was largely a result of the Gaussian decay (57.8% of the reduction), fat spectrum (31.0%) and biexponential decay (8.8%) terms. The inclusion of corrections was also accompanied by a decrease in the dependence of PDFF on the number of echoes. Similar analysis of R2* showed a decrease in the dependence on the number of echoes. Comparison of PDFF with spectroscopy indicated excellent agreement before and after correction, but the latter exhibited lower bias on a Bland–Altman plot (1.35% versus 0.41%). In conclusion, correction for known and expected biases in PDFF quantification in liver reduces the fitting error, decreases the dependence on the number of echoes and increases the accuracy. This retrospective analysis of liver MRI data from 463 subjects fitted the magnitude signal versus echo time from spoiled gradient echo imaging to estimate PDFF with different numbers of echoes (from 3 to 16). Monoexponential R2* decay and a multi‐peak fat spectrum were used, as well as additional corrections for non‐exponential decay (Gaussian), number of double bonds, R2* difference between water and fat, water frequency shift and noise bias. These corrections reduced the fitting error by 43.6 % and removed the dependence of PDFF and R2* on number of echoes.