Abstract
Chemical shift-encoded imaging (CSEI) is the most common magnetic resonance imaging fat–water separation method. However, when high spatial resolution fat fraction (FF) images are desired, CSEI might be challenging owing to the increased interecho spacing. Here, 3 T2-based methods have been assessed as alternative methods for obtaining high-resolution FF images. Images from the calf of 10 healthy volunteers were acquired; FF maps were then estimated using 3 T2-based methods (2- and 3-parameter nonlinear least squares fit and a Bayesian probability method) and CSEI for reference. In addition, simulations were conducted to characterize the performance of various methods. Here, all T2-based methods resulted in qualitatively improved high-resolution FF images compared with high-resolution CSEI. The 2-parameter fit showed best quantitative agreement to low-resolution CSEI, even at low FF. The estimated T2-values of fat and water, and the estimated muscle FF of the calf, agreed well with previously published data. In conclusion, T2-based methods can provide improved high-resolution FF images of the calf compared with the CSEI method.
Highlights
Chemical shift-encoded imaging (CSEI) is a common quantitative magnetic resonance imaging (MRI) method for fat–water separation and measurement of fat content in numerous body parts, such as the liver and skeletal muscles [1,2,3,4,5]
The 3-parameter fit estimated a lower value of T2,W compared with the monoexponential fit and the Bayesian fit
In contrast to the T2-based methods, the high-resolution CSEI produced an fat fraction (FF) image with a noise level that concealed the anatomy of the calf
Summary
Chemical shift-encoded imaging (CSEI) is a common quantitative magnetic resonance imaging (MRI) method for fat–water separation and measurement of fat content in numerous body parts, such as the liver and skeletal muscles [1,2,3,4,5]. Fatty infiltration has been related to, for example, insulin resistance and various neuromuscular diseases [6,7,8,9,10,11]. Depending on the muscle group involvement, the outcome of some neuromuscular diseases can show a large variability [11, 13]. Different neuromuscular diseases show different fat infiltration patterns of the muscle groups. By detecting these patterns, it might be easier to identify a specific disease [11, 14]. To enable and simplify the distinction between the different muscle groups, and between inter- and intramuscular fat, high-resolution fat fraction (FF) images are desirable. CSEI is a validated method for fat quantification purposes [4, 15], and it has previously been used for skeletal muscle applications [1, 2, 5]
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