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Hepatic Fat Fraction: MR Imaging for Quantitative Measurement and Display—Early Experience¹

¹ From the Departments of Radiology/MRI (H.K.H., T.L.C., F.J.L., V.G., S.D.S., S.A.), Pathology (B.J.M., H.D.A., J.K.G.), and Internal Medicine (H.S.C.), University of Michigan Health System, 1500 E Medical Center Dr, MRI UHB2A209, Ann Arbor, MI 48109-0030. From the 2004 RSNA Annual Meeting. Received September 23, 2004; revision requested November 29; revision received December 27; accepted January 21, 2005. Address correspondence to T.L.C. (e-mail: tlchenev{at}umich.edu).

View larger version (35K): [in a new window]   Figure 1. Graph shows the estimated percentage of fat, as given with Equation (E4) (radiology.rsnajnls.org/cgi/content/full/2373041639/DC1), as a function of true fat fraction at low T1 weighting (intermediate weighting) (flip angle, 20°) and high T1 weighting (flip angle, 70°). As expected, the lower flip angle data more faithfully match the true fat fraction because of reduced T1 relaxation contamination. Note ambiguity in fat fraction that originates from the magnitude format of IP and OP data. For example, both 30% and 70% true fat content yield apparent fat content around 30%. T2* correction has been applied to this simulation, which also demonstrates the performance of the algorithm for combined intermediate and T1 weighting. The technique yields quantitative fat estimates over a substantially greater dynamic range (ie, 0%–100%) without the need for phase-correction reconstruction algorithms or T1 measurement. Parameters used for this computer simulation were as follows: 150/2.3, 4.6; flip angle 1, 70°; flip angle 2, 20°; T1 of fat, 600 msec; T1 of water, 300 msec; and T2* of water and fat, 20 msec.

View larger version (33K): [in a new window]   Figure 2. Graph shows estimated percentage of fat, as given with Equation (E4) (radiology.rsnajnls.org/cgi/content/full/2373041639/DC1), as a function of true fat fraction at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). The T2* (assumed to be 4 msec) effect leads to substantial underestimation of percentage of fat at a level of true fat content of less than 50%. Parameters used for this computer simulation were as follows: 150/2.3, 4.6; flip angle 1, 70°; flip angle 2, 20°; T1 of fat, 600 msec; T1 of water, 300 msec; and T2* of water and fat, 4 msec.

View larger version (126K): [in a new window]   Figure 3a. (a) Image shows phantom model that consisted of a bottle (approximately 700 mL) filled with equal volumes of water and light mineral oil (to simulate fat). A single oblique section was acquired to intersect the oil-water interface such that there was a continuous transition from pure water to pure oil. (b) Images of the phantom obtained by using a dual-echo gradient-recalled echo sequence at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°) to test the proposed algorithm. The signal cancellation effect in voxels that have comparable mix of fat and oil is clearly apparent on the OP image (*). (c) Image shows color maps of the estimated percentage of oil. The color scale represents the estimated percentage of oil. Note ambiguity in the estimated percentage of oil at a level of true oil concentration of greater than 50% with low and high T1-weighted dual-echo spoiled gradient-recalled acquisition in the steady state sequences. The combined algorithm clearly addresses this issue and yields quantitative oil estimates over a substantially greater dynamic range (ie, 0%–100%). (d) Graph of percentage of oil along a line though the center of the phantom that shows transition from pure water (on left side of image) to pure oil (on right side of image).

View larger version (106K): [in a new window]   Figure 3b. (a) Image shows phantom model that consisted of a bottle (approximately 700 mL) filled with equal volumes of water and light mineral oil (to simulate fat). A single oblique section was acquired to intersect the oil-water interface such that there was a continuous transition from pure water to pure oil. (b) Images of the phantom obtained by using a dual-echo gradient-recalled echo sequence at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°) to test the proposed algorithm. The signal cancellation effect in voxels that have comparable mix of fat and oil is clearly apparent on the OP image (*). (c) Image shows color maps of the estimated percentage of oil. The color scale represents the estimated percentage of oil. Note ambiguity in the estimated percentage of oil at a level of true oil concentration of greater than 50% with low and high T1-weighted dual-echo spoiled gradient-recalled acquisition in the steady state sequences. The combined algorithm clearly addresses this issue and yields quantitative oil estimates over a substantially greater dynamic range (ie, 0%–100%). (d) Graph of percentage of oil along a line though the center of the phantom that shows transition from pure water (on left side of image) to pure oil (on right side of image).

View larger version (53K): [in a new window]   Figure 3c. (a) Image shows phantom model that consisted of a bottle (approximately 700 mL) filled with equal volumes of water and light mineral oil (to simulate fat). A single oblique section was acquired to intersect the oil-water interface such that there was a continuous transition from pure water to pure oil. (b) Images of the phantom obtained by using a dual-echo gradient-recalled echo sequence at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°) to test the proposed algorithm. The signal cancellation effect in voxels that have comparable mix of fat and oil is clearly apparent on the OP image (*). (c) Image shows color maps of the estimated percentage of oil. The color scale represents the estimated percentage of oil. Note ambiguity in the estimated percentage of oil at a level of true oil concentration of greater than 50% with low and high T1-weighted dual-echo spoiled gradient-recalled acquisition in the steady state sequences. The combined algorithm clearly addresses this issue and yields quantitative oil estimates over a substantially greater dynamic range (ie, 0%–100%). (d) Graph of percentage of oil along a line though the center of the phantom that shows transition from pure water (on left side of image) to pure oil (on right side of image).

View larger version (33K): [in a new window]   Figure 3d. (a) Image shows phantom model that consisted of a bottle (approximately 700 mL) filled with equal volumes of water and light mineral oil (to simulate fat). A single oblique section was acquired to intersect the oil-water interface such that there was a continuous transition from pure water to pure oil. (b) Images of the phantom obtained by using a dual-echo gradient-recalled echo sequence at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°) to test the proposed algorithm. The signal cancellation effect in voxels that have comparable mix of fat and oil is clearly apparent on the OP image (*). (c) Image shows color maps of the estimated percentage of oil. The color scale represents the estimated percentage of oil. Note ambiguity in the estimated percentage of oil at a level of true oil concentration of greater than 50% with low and high T1-weighted dual-echo spoiled gradient-recalled acquisition in the steady state sequences. The combined algorithm clearly addresses this issue and yields quantitative oil estimates over a substantially greater dynamic range (ie, 0%–100%). (d) Graph of percentage of oil along a line though the center of the phantom that shows transition from pure water (on left side of image) to pure oil (on right side of image).

View larger version (32K): [in a new window]   Figure 4. Graph of percentage of oil in the quantitative stepwise water-oil phantom. The oil content of the 3-mm slab is graduated in increments of 10% as it demonstrates transition from pure water to pure oil. Note that the estimated percentage of oil, measured in the center of the phantom with the combined algorithm, tracks well with the line of unity.

View larger version (153K): [in a new window]   Figure 5a. (a) Transverse IP and OP images (155/2.3 [OP], 4.6 [IP]) of the liver in a patient suspected of having nonalcoholic steatohepatitis, obtained at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). (b, c) Estimated percentage of fat maps obtained with the combined algorithm displayed on a (b) 100% scale and (c) 50% scale. The mean T2* value of the liver is 11 msec. The mean percentage of fat in the right lobe is 28.6% ± 2.4 (obtained with 5.5-cm2 region of interest). (d) Hematoxylin-eosin–stained slide of the biopsy specimen from the right lobe on medium power. (e) Graph shows results at quantitative histopathologic analysis with pixel intensity values, which yielded an estimate of 28.5% of fat.

View larger version (118K): [in a new window]   Figure 5b. (a) Transverse IP and OP images (155/2.3 [OP], 4.6 [IP]) of the liver in a patient suspected of having nonalcoholic steatohepatitis, obtained at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). (b, c) Estimated percentage of fat maps obtained with the combined algorithm displayed on a (b) 100% scale and (c) 50% scale. The mean T2* value of the liver is 11 msec. The mean percentage of fat in the right lobe is 28.6% ± 2.4 (obtained with 5.5-cm2 region of interest). (d) Hematoxylin-eosin–stained slide of the biopsy specimen from the right lobe on medium power. (e) Graph shows results at quantitative histopathologic analysis with pixel intensity values, which yielded an estimate of 28.5% of fat.

View larger version (115K): [in a new window]   Figure 5c. (a) Transverse IP and OP images (155/2.3 [OP], 4.6 [IP]) of the liver in a patient suspected of having nonalcoholic steatohepatitis, obtained at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). (b, c) Estimated percentage of fat maps obtained with the combined algorithm displayed on a (b) 100% scale and (c) 50% scale. The mean T2* value of the liver is 11 msec. The mean percentage of fat in the right lobe is 28.6% ± 2.4 (obtained with 5.5-cm2 region of interest). (d) Hematoxylin-eosin–stained slide of the biopsy specimen from the right lobe on medium power. (e) Graph shows results at quantitative histopathologic analysis with pixel intensity values, which yielded an estimate of 28.5% of fat.

View larger version (168K): [in a new window]   Figure 5d. (a) Transverse IP and OP images (155/2.3 [OP], 4.6 [IP]) of the liver in a patient suspected of having nonalcoholic steatohepatitis, obtained at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). (b, c) Estimated percentage of fat maps obtained with the combined algorithm displayed on a (b) 100% scale and (c) 50% scale. The mean T2* value of the liver is 11 msec. The mean percentage of fat in the right lobe is 28.6% ± 2.4 (obtained with 5.5-cm2 region of interest). (d) Hematoxylin-eosin–stained slide of the biopsy specimen from the right lobe on medium power. (e) Graph shows results at quantitative histopathologic analysis with pixel intensity values, which yielded an estimate of 28.5% of fat.

View larger version (24K): [in a new window]   Figure 5e. (a) Transverse IP and OP images (155/2.3 [OP], 4.6 [IP]) of the liver in a patient suspected of having nonalcoholic steatohepatitis, obtained at low T1 weighting (flip angle, 20°) and high T1 weighting (flip angle, 70°). (b, c) Estimated percentage of fat maps obtained with the combined algorithm displayed on a (b) 100% scale and (c) 50% scale. The mean T2* value of the liver is 11 msec. The mean percentage of fat in the right lobe is 28.6% ± 2.4 (obtained with 5.5-cm2 region of interest). (d) Hematoxylin-eosin–stained slide of the biopsy specimen from the right lobe on medium power. (e) Graph shows results at quantitative histopathologic analysis with pixel intensity values, which yielded an estimate of 28.5% of fat.