Organ-Specific Fat Quantification: Skeletal Muscle
Young Cheol Yoon1
1Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea, Republic of

Synopsis

Keywords: Cross-organ: Tissue characterisation, Musculoskeletal: Muscular, Contrast mechanisms: Fat

The accumulation of lipids in skeletal muscle can lead to various health issues. Currently, semiquantitative methods like the Goutallier and Mercuri systems are used to evaluate fatty infiltration, but they have limitations. MRS is more reliable for measuring lipid content, but several factors must be considered during data acquisition. PDFF is an emerging technique that generates fat fraction maps, allowing for direct quantitative measurement of fat proportion. T2*-corrected six-echo Dixon sequences are recommended. PDFF is the most commonly used metric for estimating skeletal muscle quality, and studies have shown its usefulness in various clinical conditions, including sarcopenia and neuromuscular diseases.

1. Fat in skeletal muscle

Various myokines released from active muscles act as signaling mediators between skeletal muscle and other vital organs, such as the liver, fat, and brain. This signaling influences the progression of chronic disease such as diabetes, cardiovascular disease, osteoporosis, osteoarthritis, cancer, and many other ageing-related diseases(1). Lipid entry and subsequent metabolism in skeletal muscle fibers is an important energy production process, with about two-thirds of resting skeletal muscle energy production coming from lipid oxidation. The accumulation of lipids inside muscle cells can be a useful way of storing a quickly accessible energy source, much like glycogen does for glucose. However, while this may be beneficial for athletes, excess lipid accumulation, particularly in diseases such as diabetes and sarcopenia with aging, can lead to lipotoxicity.(2-4) Excess lipids and their derivatives accumulate both within and between muscle cells, myosteatosis, inducing mitochondrial dysfunction, disturbing β-oxidation of fatty acids, and enhancing reactive oxygen species production, leading to lipotoxicity and insulin resistance, as well as enhanced secretion of some pro-inflammatory cytokines. In turn, these muscle-secreted cytokines may exacerbate adipose tissue atrophy, support chronic low-grade inflammation, and establish a vicious cycle of local hyperlipidemia, insulin resistance, and inflammation.(1) As for mechanical dysfunction, myosteatosis leads to conversion of type II muscle fibers into type I fibers, which may impair the force and speed of muscle contraction. Deterioration in mobility and physical function can increase the risk of fall and fracture, decrease cardiovascular function, and eventually lead to frailty and mortality(5). The term myosteatosis, a possible concomitant component of sarcopenia, refers to fatty infiltration of the skeletal muscle, which is caused by several factors including aging, disuse, muscle injury, and hormonal dysfunction.(6) Myosteatosis is associated with loss of muscle mass and strength and increased mortality among the elderly.(6)

2. Semi-quantitative methods

The Goutallier classification has been the most popular method to evaluate the quality of rotator cuff muscles before surgery. The Goutallier method was originally designed as a semi-quantitative grading system of degenerative rotator cuff muscles with five different grades from grade 0 (no fat inside the muscle) to grade 4 (more than 50% fat inside the muscle) in CT images. Currently, a similar grading system is widely applied in MR images. The Goutallier grading method is fast and convenient because the grades of muscle degenerations are visually evaluated on standard T1-weighted MR images. Although the Goutallier grades have been reported to correlate with the severity of fatty infiltration in the rotator cuff muscles, their inconsistent intra-observer and inter-observer agreements need to be improved for use in accurate clinical diagnostic applications.(7) The Mercuri grading system of muscle MRI was developed to determine the ratio of muscle impairment in patients with muscular dystrophy(8). Each muscle group can be staged as follows: Normal appearance; Mild involvement, An early moth-eaten appearance, with scattered small areas of increased signal or with numerous discrete areas of increased signal with beginning confluence, comprising less than 30% of the volume of the individual muscle.; Moderate involvement, A late moth-eaten appearance, with numerous discrete areas of increased signal with beginning confluence, comprising 30% to 60% of the volume of the individual muscle.; Severe involvement, A washed-out appearance, a fuzzy appearance due to confluent areas of increased signal, or an end-stage appearance, with muscle replaced by increased density connective tissue and fat, and only a rim of fascia and neurovascular structures distinguishable. This scoring system has proved to be useful, but it should be kept in mind that the comparison among muscles and the overall gestalt of the pattern of involvement is more important than the severity of involvement of individual muscles.(9) These semiquantitative grading systems using a conventional T1WI are widely used for various muscular abnormalities, but has a significant shortcoming of being highly observer dependent(10). Furthermore, because they rely on macroscopic fat signal and only has four or five grades, it is not optimized for assessment of early fat infiltration or interval progression that is not severe enough to result in change of grades.(11)

3. MR spectroscopy

Skeletal musculature shows variable amounts and distribution of adipose tissue, which are mainly arranged in macroscopically visible septa along the muscle fiber bundles. This muscular adipose tissue consists of adipocytes and is often termed extramyocellular lipids (EMCL), in contrast to clearly smaller lipid droplets inside myocytes, which are termed intramyocellular lipids (IMCL).(12) These represent two different forms of lipid storage with distinctly different physiological functions and 1H-MRS features. While the discrete localization and high concentration of EMCL makes MR imaging methods most appropriate, IMCL which are stored in droplets adjacent to mitochondria, and associated with insulin resistance, type 2 diabetes, and metabolic dysfunction, can be directly measured by 1H-MRS.(13, 14) The interest in studying skeletal muscle lipid content via 1H-MRS in vivo was sparked by the demonstration that the proximity of IMCL is a highly active energy storage form that can be used and replenished within short time periods in healthy subjects(15), while insulin-resistant patients have constantly increased IMCL levels.(16) To accurately measure the small amount of included IMCL, there are several factors to consider during data acquisition. Due to the orientation dependence of the EMCL/IMCL separation, the best separation of signals will be achieved in fusiform muscles with a uniform fiber orientation along the axis of the muscle (e.g., tibialis anterior or vastus intermedius). Exact repositioning in the transversal image plane is usually easier than along the muscle, high resolution orthogonal, contiguous axial or 3D images are mandatory. In general, the voxel size for IMCL acquisition should be as small as SNR allows, ~ 10 mm x 10 mm in the transversal image plane. For consistent quantitative results, the voxel size should be the same for all study subjects at all study time points, allowing only small adaptions for exclusion of obvious EMCL contributions and deviating muscle size.(13)

4. Proton density fat fraction (PDFF)

Dixon MRI is an emerging imaging technique for fat fraction measurement that exploits the capability to differentiate the individual contributions of water and fat in each voxel of tissue using the chemical shift difference between the two. Recent Dixon-based MRI techniques generate fat fraction maps that allows direct quantitative measurement of the fat proportion within the designated region of interest (ROI). Studies have reported encouraging results with using Dixon-based techniques for fat quantification in skeletal muscle.(11, 17) A study using MR spectroscopy as a reference standard reported that intramuscular fat quantification using T2*-corrected six-echo Dixon sequences showed a significantly better concordance with the spectroscopic data compared with those of T2*-corrected three-echo Dixon or non-T2*-corrected two-echo Dixon technique.(18) The importance of T2*-correction has been proposed considering the presence of iron that causes local magnetic inhomogeneity and has been emphasized in liver fat quantification. Skeletal muscles are also reported to contain non-negligible amounts of iron.(19) Also, it has been suggested that it is necessary to acquire at least six echoes for the optimal separation of water and fat signals with T2*-correction. Dixon imaging techniques, which enables the reproducible and efficient quantification of fat content, strengthened the MRI role for the quantitative assessment of body composition.(20) Indeed, the Dixon method overcomes the limited applicability of MRS, due to inhomogeneity of fat muscle infiltration, and might be used for the prediction of adverse outcome related to low muscle quality and quantity.(21) Moreover, as pointed out by the recent studies published by Grimm et al,(21) the Dixon method represents a highly repeatable MRI protocol for muscle volume and PDFF estimation compared with MRS. Indeed, the use large field of view may cause technical difficulties related to magnetic field inhomogeneity and increased distances between analyzed body region and RF coils.(20) The estimation of PDFF from Dixon images (both T1- and T2-weighted) represents the most frequently used metric of skeletal muscle quality.(22) PDFF has been applied to various clinical condition such as osteoarthritis(23), rotator cuff tear(24) or sarcopenia(25). Multiple studies revealed that muscular function is related to muscle fat distribution(26), and PDFF is negatively correlated with relative muscle strength(27) but positively correlated with age.(28) Sarcopenia is a condition characterized by loss of skeletal muscle mass and function. The European Working Group on Sarcopenia in Older People (EWGSOP) recently updated this definition as follows: "a muscle disease rooted in adverse muscle changes that accrue across a lifetime."(22) MRI is the only technique that allows combining body mass composition and muscle quality assessment. For this reason, it may represent one of the most promising imaging modalities for the assessment of skeletal muscle quality and quantity, which is fundamental for sarcopenia confirmation.(28) There are studies evaluated the role of PDFF in the assessment of fatty replacement in muscles in neuromuscular diseases.(11, 26, 29, 30) PDFF allows demonstration and quantification of fatty replacement in muscles in neuromuscular diseases as well as diabetic polyneuropathy(31) which may be helpful in both diagnosis and evaluation of treatment response(26).

5. Conclusion

MRI is useful tool for measuring the quantity of fat in skeletal muscle. MRS can evaluate the intramyocellular lipid and can be applied to clinical studies regarding physiology and endocrinology. PDFF can be easily adopted daily practices and useful to evaluate the patients with various conditions such as sarcopenia, osteoarthritis, and neuromuscular disorders.

Acknowledgements

No acknowledgement found.

References

1. Li CW, Yu K, Shyh-Chang N, Jiang Z, Liu T, Ma S, et al. Pathogenesis of sarcopenia and the relationship with fat mass: descriptive review. J Cachexia Sarcopenia Muscle. 2022;13(2):781-94. 2. Al Saedi A, Debruin DA, Hayes A, Hamrick M. Lipid metabolism in sarcopenia. Bone. 2022;164:116539. 3. Biltz NK, Collins KH, Shen KC, Schwartz K, Harris CA, Meyer GA. Infiltration of intramuscular adipose tissue impairs skeletal muscle contraction. J Physiol. 2020;598(13):2669-83. 4. Bakke SS, Feng YZ, Nikolic N, Kase ET, Moro C, Stensrud C, et al. Myotubes from severely obese type 2 diabetic subjects accumulate less lipids and show higher lipolytic rate than myotubes from severely obese non-diabetic subjects. PLoS One. 2015;10(3):e0119556. 5. Ahn H, Kim DW, Ko Y, Ha J, Shin YB, Lee J, et al. Updated systematic review and meta-analysis on diagnostic issues and the prognostic impact of myosteatosis: A new paradigm beyond sarcopenia. Ageing Res Rev. 2021;70:101398. 6. Hamrick MW, McGee-Lawrence ME, Frechette DM. Fatty Infiltration of Skeletal Muscle: Mechanisms and Comparisons with Bone Marrow Adiposity. Front Endocrinol (Lausanne). 2016;7:69. 7. Lee D, Hong KT, Lee W, Khil EK, Lee GY, Choi JA, et al. Threshold-based quantification of fatty degeneration in the supraspinatus muscle on MRI as an alternative method to Goutallier classification and single-voxel MR spectroscopy. BMC Musculoskelet Disord. 2020;21(1):362. 8. Nakayama T, Ishiyama A, Murakami T, Kimura E, Kuru S. Automatic calculation of Mercuri grades from CT and MR muscle images. Brain Dev. 2019;41(10):870-7. 9. Mercuri E, Pichiecchio A, Allsop J, Messina S, Pane M, Muntoni F. Muscle MRI in inherited neuromuscular disorders: past, present, and future. J Magn Reson Imaging. 2007;25(2):433-40. 10. Shahabpour M, Kichouh M, Laridon E, Gielen JL, De Mey J. The effectiveness of diagnostic imaging methods for the assessment of soft tissue and articular disorders of the shoulder and elbow. Eur J Radiol. 2008;65(2):194-200. 11. Kim HS, Yoon YC, Choi BO, Jin W, Cha JG. Muscle fat quantification using magnetic resonance imaging: case-control study of Charcot-Marie-Tooth disease patients and volunteers. J Cachexia Sarcopenia Muscle. 2019;10(3):574-85. 12. Schick F, Eismann B, Jung WI, Bongers H, Bunse M, Lutz O. Comparison of localized proton NMR signals of skeletal muscle and fat tissue in vivo: two lipid compartments in muscle tissue. Magn Reson Med. 1993;29(2):158-67. 13. Krssak M, Lindeboom L, Schrauwen-Hinderling V, Szczepaniak LS, Derave W, Lundbom J, et al. Proton magnetic resonance spectroscopy in skeletal muscle: Experts' consensus recommendations. NMR Biomed. 2021;34(5):e4266. 14. Kakehi S, Tamura Y, Takeno K, Sakurai Y, Kawaguchi M, Watanabe T, et al. Increased intramyocellular lipid/impaired insulin sensitivity is associated with altered lipid metabolic genes in muscle of high responders to a high-fat diet. Am J Physiol Endocrinol Metab. 2016;310(1):E32-40. 15. Boesch C, Slotboom J, Hoppeler H, Kreis R. In vivo determination of intra-myocellular lipids in human muscle by means of localized 1H-MR-spectroscopy. Magn Reson Med. 1997;37(4):484-93. 16. Krssak M, Falk Petersen K, Dresner A, DiPietro L, Vogel SM, Rothman DL, et al. Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study. Diabetologia. 1999;42(1):113-6. 17. Kreis R, Jung B, Slotboom J, Felblinger J, Boesch C. Effect of exercise on the creatine resonances in 1H MR spectra of human skeletal muscle. J Magn Reson. 1999;137(2):350-7. 18. Yoo YH, Kim HS, Lee YH, Yoon CS, Paek MY, Yoo H, et al. Comparison of Multi-Echo Dixon Methods with Volume Interpolated Breath-Hold Gradient Echo Magnetic Resonance Imaging in Fat-Signal Fraction Quantification of Paravertebral Muscle. Korean J Radiol. 2015;16(5):1086-95. 19. Beard JL. Iron biology in immune function, muscle metabolism and neuronal functioning. J Nutr. 2001;131(2S-2):568S-79S; discussion 80S. 20. Berglund J, Johansson L, Ahlstrom H, Kullberg J. Three-point Dixon method enables whole-body water and fat imaging of obese subjects. Magn Reson Med. 2010;63(6):1659-68. 21. Grimm A, Meyer H, Nickel MD, Nittka M, Raithel E, Chaudry O, et al. Repeatability of Dixon magnetic resonance imaging and magnetic resonance spectroscopy for quantitative muscle fat assessments in the thigh. J Cachexia Sarcopenia Muscle. 2018;9(6):1093-100. 22. Codari M, Zanardo M, di Sabato ME, Nocerino E, Messina C, Sconfienza LM, et al. MRI-Derived Biomarkers Related to Sarcopenia: A Systematic Review. J Magn Reson Imaging. 2020;51(4):1117-27. 23. Kumar D, Karampinos DC, MacLeod TD, Lin W, Nardo L, Li X, et al. Quadriceps intramuscular fat fraction rather than muscle size is associated with knee osteoarthritis. Osteoarthritis Cartilage. 2014;22(2):226-34. 24. Nozaki T, Tasaki A, Horiuchi S, Ochi J, Starkey J, Hara T, et al. Predicting Retear after Repair of Full-Thickness Rotator Cuff Tear: Two-Point Dixon MR Imaging Quantification of Fatty Muscle Degeneration-Initial Experience with 1-year Follow-up. Radiology. 2016;280(2):500-9. 25. Grimm A, Meyer H, Nickel MD, Nittka M, Raithel E, Chaudry O, et al. A Comparison between 6-point Dixon MRI and MR Spectroscopy to Quantify Muscle Fat in the Thigh of Subjects with Sarcopenia. J Frailty Aging. 2019;8(1):21-6. 26. Idilman IS, Yildiz AE, Karaosmanoglu AD, Ozmen MN, Akata D, Karcaaltincaba M. Proton density fat fraction: magnetic resonance imaging applications beyond the liver. Diagn Interv Radiol. 2022;28(1):83-91. 27. Inhuber S, Sollmann N, Schlaeger S, Dieckmeyer M, Burian E, Kohlmeyer C, et al. Associations of thigh muscle fat infiltration with isometric strength measurements based on chemical shift encoding-based water-fat magnetic resonance imaging. Eur Radiol Exp. 2019;3(1):45. 28. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48(1):16-31. 29. Leporq B, Le Troter A, Le Fur Y, Salort-Campana E, Guye M, Beuf O, et al. Combined quantification of fatty infiltration, T (1)-relaxation times and T (2)*-relaxation times in normal-appearing skeletal muscle of controls and dystrophic patients. MAGMA. 2017;30(4):407-15. 30. Khan AA, Boggs T, Bowling M, Austin S, Stefanescu M, Case L, et al. Whole-body magnetic resonance imaging in late-onset Pompe disease: Clinical utility and correlation with functional measures. J Inherit Metab Dis. 2020;43(3):549-57. 31. Stouge A, Khan KS, Kristensen AG, Tankisi H, Schlaffke L, Froeling M, et al. MRI of Skeletal Muscles in Participants with Type 2 Diabetes with or without Diabetic Polyneuropathy. Radiology. 2020;297(3):608-19.
Proc. Intl. Soc. Mag. Reson. Med. 31 (2023)