Tomography

Vol. 3 No. 3 - Sep 2017

Tomography is a scientific journal for publication of articles in imaging research

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High-Resolution MR Imaging of Muscular Fat Fraction—Comparison of Three T 2 -Based Methods and Chemical Shift-Encoded Imaging Lena Trinh 1 , Emelie Lind 1,2 , Pernilla Peterson 1 , Jonas Svensson 1,3 , Lars E. Olsson 1 , and Sven Månsson 1 1 Medical Radiation Physics, Department of Translational Medicine, Lund University, Skåne University Hospital, Malmö, Sweden; 2 Department of Medical Radiation Physics, Lund University, Lund, Sweden; 3 Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden Corresponding Author: Lena Trinh, MSc Medical Radiation Physics, Inga Marie Nilssons gata 49, Skåne University Hospital, SE-205 02 Malmö, Sweden; E-mail: lena.trinh@med.lu.se Key Words: fat quantification, Bayesian probability theory, non-linear least squares, T 2 , high-resolution imaging Abbreviations: Chemical shift-encoded imaging (CSEI); fat fraction (FF); magnetic resonance imaging (MRI); non-linear least squares (NLLS); multi echo gradient echo (MGRE); repetition time (TR); echo time (TE); bandwidth (BW); multi echo spin echo (MESE); T 2 -relaxation time of fat (T 2,F ); T 2 -relaxation time of water (T 2,W ); region-of-interest (ROI); signal-to-noise ratio (SNR) Chemical shift-encoded imaging (CSEI) is the most common magnetic resonance imaging fat–water separa- tion method. However, when high spatial resolution fat fraction (FF) images are desired, CSEI might be chal- lenging owing to the increased interecho spacing. Here, 3 T 2 -based methods have been assessed as alterna- tive methods for obtaining high-resolution FF images. Images from the calf of 10 healthy volunteers were ac- quired; FF maps were then estimated using 3 T 2 -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 T 2 -based methods resulted in qualitatively im- proved high-resolution FF images compared with high-resolution CSEI. The 2-parameter fit showed best quan- titative agreement to low-resolution CSEI, even at low FF. The estimated T 2 -values of fat and water, and the estimated muscle FF of the calf, agreed well with previously published data. In conclusion, T 2 -based methods can provide improved high-resolution FF images of the calf compared with the CSEI method. INTRODUCTION Chemical shift-encoded imaging (CSEI) is a common quantita- tive 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 (1–5). In skeletal muscles, fatty infiltration has been related to, for example, insulin resistance and various neuromuscular diseases (6–11). The location of fat accumulation within the muscle has also been shown to be important (6), as some muscle groups are more likely to accumulate fat (12). Depending on the muscle group involvement, the outcome of some neuromuscular diseases can show a large variability (11, 13). In addition, different neuro- muscular 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 quanti- fication purposes (4, 15), and it has previously been used for skeletal muscle applications (1, 2, 5). Previously, fat quantification methods based on differences in fat and water T 2 (16) rather than chemical shifts have been suggested for applications in skeletal muscles (17, 18). With T 2 -based methods, there is a possibility of obtaining information on FF and T 2 relaxation times simultaneously (18). This would offer more information about the status of the disease, as a change in muscle T 2 -relaxation time has been shown to reflect the activity and progress of neuromuscular diseases (13, 19), complementing the information about the fat infiltration degree that primarily serves as a severity indicator (14). Moreover, there are several challenges associated with the CSEI technique, par- ticularly when high resolution is required, which may be ad- dressed by using T 2 -based methods. For example, increasing the resolution increases the minimal achievable interecho time which may have a negative impact on the CSEI fat quantifica- tion accuracy (20). In addition, it is common that fat/water swaps are present in FF images when using CSEI. To obtain both the amplitudes and the T 2 -relaxation times of the fat, as well as the water component of the signal, a nonlinear least squares (NLLS) fitting method is commonly used (21, 22). However, NLLS has known problems with estimating the parameters correctly when 1 component is considerably larger than the other (23, 24). As a consequence, it may be difficult to measure low FFs using NLLS. In such cases, a fitting method based on Bayesian probability theory could be an alter- native, as it has also been shown to be more robust against noise RESEARCH ARTICLE ABSTRACT © 2017 The Authors. Published by Grapho Publications, LLC This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). ISSN 2379-1381 http://dx.doi.org/10.18383/j.tom.2017.00011 TOMOGRAPHY.ORG | VOLUME 3 NUMBER 3 | SEPTEMBER 2017 153

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