High-Resolution MR Imaging of Muscular Fat Fraction—Comparison of Three T2-Based Methods and Chemical Shift-Encoded Imaging

Figure 1.. Schematic view over the used methods (chemical shift-encoded imaging [CSEI], 2-parameter fit, 3-parameter fit, and Bayesian fit) and the corresponding outputs.

Figure 2.. The regions of interest (ROIs) used for calculating T2,W and T2,F (dashed line), and the fat fraction (FF) in 3 calf muscles (solid line): gastrocnemius, soleus, and tibialis anterior.

Figure 3.. The mean and standard deviation of T2,W (A) within an ROI placed in tibialis anterior and T2,F (B) within an ROI placed in the subcutaneous fat, of all volunteers (except one in the monoexponential fit) at high- and low-resolution imaging.

Figure 4.. Fat fraction maps of a calf calculated at low and high resolution, using four methods: CSEI, 2-parameter fit, 3-parameter fit, and Bayesian fit.

Figure 5.. To the left: Scatter plots showing the estimated FF of high-resolution CSEI (A), 2-parameter fit (B), 3-parameter fit (C), and Bayesian fit (D). Each plot shows data points that represent the mean FF within an ROI (3 muscles measured for each volunteer), the linear regression fit (dashed), and the identity line (solid). To the right: Bland–Altman plots of high-resolution CSEI (E), 2-parameter fit (F), 3-parameter fit (G), and Bayesian fit (H), showing the mean difference (solid) and 1.96 standard deviations (dashed).

Figure 6.. The acquired and fitted signal decay of 3 voxels with different FFs are shown for the low-resolution (A–C) and high-resolution (D–F) MESE images.

Figure 7.. The difference between the true and estimated FFs when using incorrect T2,W (A) and incorrect T2,F (B) in the 2-parameter fit and when using incorrect T2,F (C) in the 3-parameter fit. The true T2,W and T2,F are 40 milliseconds and 160 milliseconds, respectively.

Figure 8.. The simulated effect of using an incorrect S0 value in the Bayesian fitting method showing the difference between the estimated and true FF (left), and the standard deviation of 1000 estimations (right).

Figure 9.. The difference between estimated FF and true FF equal to 2%, 5%, 10%, 30%, and 95% at different signal-to-noise ratios (SNRs) (20, 50, 150, 300, and 600) using the 2-parameter fit (A), the 3-parameter fit (B), and the Bayesian fit (C). The corresponding standard deviations of 1000 estimations using the 2-parameter fit (D), the 3-parameter fit (E), and the Bayesian fit (F) are also shown. The mean SNR of the collected MESE images (512 × 512) in muscle and fat is shown in the first plot (A). At low FF, all 3 methods overestimate the FF in the presence of a high noise level. The difference between estimated and true FF, of the 3-parameter fit outside the shown interval in (B) are: −40.9% (SNR = 20) and −27.8% (SNR = 50). The corresponding standard deviation not shown in (E) is ±41.4% and ±39.0%, respectively.