Influence of Gd-EOB-DTPA on T1 dependence of the proton density fat fraction using magnetic resonance spectroscopy.

This phantom study assessed the effect of Gd-EOB-DTPA on T1 bias (difference in T1 between water and fat) of the proton density fat fraction when using magnetic resonance spectroscopy. Phantoms containing varying fat percentages, without and with Gd-EOB-DTPA (precontrast and postcontrast, respectively), were scanned with repetition times ranging from 1000 to 5000 ms. The relationship between the proton density fat fraction at a reference repetition time of 5000 ms and that using different repetition times, was evaluated in the precontrast and postcontrast phantoms using linear regression and Bland-Altman analyses. In the precontrast phantom, as the repetition time increased, the slope tended to approach one. In the postcontrast phantom, the slope and intercept were near one and zero, respectively. The mean difference was smaller in the postcontrast phantom (range - 0.24 to - 0.01%) than in the precontrast phantom (range 0.12 to 3.52%). We conclude that I1 bias is minimized by Gd-EOB-DTPA.

Correction to: Influence of Gd-EOB-DTPA on proton density fat fraction using the six-echo Dixon method in 3 Tesla magnetic resonance imaging.

A diameter of glass bottles in phantoms in the above article (2 cm) was incorrect. The correct diameter is 4.5 cm.

Influence of Gd-EOB-DTPA on proton density fat fraction using the six-echo Dixon method in 3 Tesla magnetic resonance imaging.

The purpose of this study was to evaluate whether disodium gadoxetate (Gd-EOB-DTPA) affects proton density fat fractions (PDFFs) during use of the multiecho Dixon (meDixon) method in phantom and simulation magnetic resonance imaging (MRI) studies at 3 T. Fat-water phantoms comprising vegetable fat-water emulsions with varying fat volume percentages (0, 5, 10, 15, 20, 30, 40, and 50) and Gd-EOB-DTPA concentrations (0 and 0.4 mM) were prepared. Phantoms without Gd-EOB-DTPA were defined as precontrast, and those with Gd-EOB-DTPA were defined as postcontrast. All phantoms were scanned with a 3 T MRI system using the meDixon method, and precontrast and postcontrast PDFFs were calculated. Simulated pre and postcontrast PDFFs in the liver were calculated using a theoretical formula. The relationship between PDFFs measured in the pre and postcontrast phantoms was evaluated using linear regression and Bland-Altman analysis. The regression analysis comparing the pre and postcontrast PDFFs yielded a slope of 0.77 (P < 0.001). The PDFFs on the postcontrast phantom were smaller than those on the precontrast phantom. The mean difference between the PDFFs on the pre and postcontrast phantoms was 6.12% (95% confidence interval 3.13 to 9.10%; limits of agreement -0.88 to 13.11%). The simulated PDFF on the postcontrast phantom was smaller than that on the precontrast phantom. We demonstrated that the PDFF measured using the meDixon was smaller on postcontrast than on precontrast at 3 T, if a low flip angle was used. This tendency was also seen in the simulation study results.