ISSN: 1899-0967
Polish Journal of Radiology
Established by prof. Zygmunt Grudziński in 1926 Sun
Current issue Archive About the journal Editorial board Abstracting and indexing Contact Instructions for authors
SCImago Journal & Country Rank



2018
vol. 83
 
Share:
Share:
more
 
 
Original paper

The influence of leg positioning on the appearance and quantification of 1H magnetic resonance muscle spectra obtained from calf muscle

Duanghathai Pasanta, Montree Tungjai, Suchart Kothan

© Pol J Radiol 2018; 83: e530-e536
Online publish date: 2018/12/10
Article file
Get citation
ENW
EndNote
BIB
JabRef, Mendeley
RIS
Papers, Reference Manager, RefWorks, Zotero
AMA
APA
Chicago
Harvard
MLA
Vancouver
 
 

Introduction

One of the important components of normal skeletal muscle is fat. This fat located inside muscle cells occurs as droplets composed of intramyocellular lipids (IMCL) and as adipocytes spread between muscle cells.
These are called extramyocellular lipids (EMCL) [1]. Recently, evidence has suggested that IMCL are positively correlated with insulin resistance in type 2 diabetes [2-4], and they are also an important energy supply [5,6]. The IMCL has traditionally been measured by muscle biopsy. Furthermore, non-invasive proton magnetic resonance spectroscopy (1H-MRS) has been developed for measuring the IMCL. Compared with a muscle biopsy, 1H-MRS presents several advantages for measuring IMCL. The advantages are that the in vivo measurement can be done, the variation coefficient is low, and the short-term changes can be determined [7]. Although the measurement of IMCL with 1H-MRS has been used in many previous studies, some influences of 1H-MRS spectral still remain.
1H-MRS spectra of muscle are influenced by two effects: bulk magnetic susceptibility and residual dipolar coupling [8,9]. These effects depend on the angle between the muscle fibres with respect to the main magnetic field [10]. Such effects do not only affect 1H-MRS spectra, but also the IMCL and EMCL quantification [11]. The 1H-MRS has previously been measured by IMCL in calf muscles [12,13]. However, a correlation between the angle of calf muscle fibres and IMCL and EMCL quantification has yet to be determined. In this study, we aim to evaluate three leg positions (neutral [0°], internal rotation [–45° from neutral position], and external rotation [+45° from neutral position]) based on IMCL and EMCL quantification in the calf muscles using 1H-MRS.

Material and methods

Subjects and equipment

The subjects included 39 healthy male volunteers (mean age, 21 years) who were studied after written informed consent was obtained. All procedures were approved by the Ethics Committee of the Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand. 1H-MRS measurements were performed on a 1.5-Tesla Magnetic Resonance Imaging (MRI) scanner equipped with a knee coil (Philips Achieva Release 2.5 series, Philips Healthcare, Netherlands).

Data acquisition and analysis

1H-MRS spectra were measured in the calf muscle of a non-dominant leg in these subjects. The leg was placed in three positions: neutral [0°], internal rotation [–45° from neutral position], and external rotation [+45° from neutral position]. Angles were obtained by semicircle angle using the anterior crest of the tibia as a surface point of reference, with the long axis of each leg placed parallel to the main magnetic field. Gel bags and foam were used to support the leg and fix position throughout the scan as shown in Figure 1A.
The T1-weighted axial and sagittal image MRI scans had the following parameters: repetition time (TR) = 700 ms, echo time (TE) = 20 ms, slice thickness = 5 mm, and field of view (FOV) = 20 × 20 cm2. The single-voxel MRS had the following parameters: PRESS pulse sequence with TR = 2000 ms, TE = 30 ms, NSA = 128 with automatic shimming protocol, and voxel = 8 × 8 × 20 mm3. We placed the voxel on the tibialis anterior (TA), gastrocnemius (medial head) (GAS), and soleus (SOL), as shown in Figure 1B.
Post-processing spectra were analysed by Java-based MRUI software (jMRUI version 5.2) [10,14]. The residual tail of water peak spectrum at 4.7 ppm was removed by applying the HLSVD water filtering algorithm. The spectrum was fitted by AMARES algorithm [15] for IMCL, EMCL, and creatine [16]. The zero-order phases were estimated by AMARES, and the first-order phase was fixed at 0 ms with the first two points of data being truncated for baseline correction. The spectrum line shape was estimated by Lorentzian function. The fitted spectrum showed metabolite spectrum peaks at different chemical shifts: IMCL (CH3) at 0.9 ppm, IMCL (CH2) at 1.3 ppm, EMCL (CH3) at 1.1 ppm, EMCL (CH2) at 1.5 ppm, and creatine at around 3.02 ppm.
To reduce biological factors that may affect the IMCL level in each individual, such as gender, training, and diet, each IMCL (CH2) and EMCL (CH2) amplitude was calculated as the ratio to the amount of methylene IMCL and EMCL signal intensity (IMCL [CH2] + EMCL [CH2]). Each IMCL (CH3) and EMCL (CH3) was calculated as the ratio based on the amount of methyl IMCL and EMCL signal intensity (IMCL [CH3] + EMCL [CH3]). Creatine was calculated as a percentage differently than the creatine signal intensity in the neutral position.

Statistical analysis

Statistical analysis was done using Origin version 8 with Friedman test for three pairwise analyses, with statistical significance being less than 0.05 between neutral, internal rotation, and external rotation on each metabolite (IMCL [CH2], EMCL [CH2] and IMCL [CH3], EMCL [CH3]) ratio and the percentage difference of Cr. The Wilcoxon Signed Rank Test was used when the three pairwise comparisons were shown to be significantly different, having a statistical significance of less than 0.05. Any metabolite that jMRUI software is unable to detect from fitted algorithm or that yielded unreliable results was excluded from the data analysis.

Results

The 1HMRS measurements were obtained using spectrums from 39 volunteers. All spectrums were fitted to the jMRUI AMARES algorithm. The spectrum was scaled to water peak at 4.7 ppm.
For TA muscle, the change in spectral appearance of TA is observed by metabolite intensity. Despite the change, the spectrum has still shown good separation of metabolite peaks in both the methyl group and the methylene group of IMCL and EMCL, as indicated in Figure 2.The mean line width of EMCL CH2 changed from 7.51 ± 2.8 (NEU) to 13.7 ± 7.1 (INT) and 17.4 ± 2.8 Hz (EXT), and the mean line width of EMCL CH3 changed from 9.54 ± 6.4 (NEU) to 10.8 ± 5.4 (INT) and 15.2 ± 4.1 Hz (EXT).
For SOL muscle, the spectra appearance did not change for difference leg positions. Additionally, there was well-defined splitting of the spectrum peak occurring between both the methyl and methylene group of IMCL and EMCL in all positions, as indicated in Figure 3. The mean line width of EMCL CH2 changed from 12.8 ± 4.4 (NEU) to 16.0 ± 4.9 (INT) and 10.5 ± 4.8 Hz (EXT), and the mean line width of EMCL CH3 changed from 1.17 ± 3.8 (NEU) to 12.1 ± 3.5 (INT) and 8.72 ± 3.9 Hz (EXT).
For GAS muscle, the fitted spectrum obtained also showed no difference between the various leg positions. However, it was shown that leg position affects IMCL (CH2) and EMCL (CH2) splitting because the spectrum peaks tend to overlap, making it difficult to distinguish between each one, as indicated in Figure 4. The mean line width of EMCL CH2 changed from 9.46 ± 6.7 (NEU) to 9.51 ± 3.1 (INT) and 7.92 ± 4.0 Hz (EXT), and the mean line width of EMCL CH3 changed from 7.24 ± 2.6 (NEU) to 9.05 ± 2.3 (INT) and 8.24 ± 2.9 Hz (EXT).
The spectra have shown that variation of leg position affects spectral intensity, spitting, and line width. Some spectral changes in appearance are barely visible; the AMARES quantification algorithm showed that the change in EMCL CH2, EMCL CH3 line width varies with leg position. In addition, the mean line width of EMCL CH2 and CH3 in SOL muscle is more than TA and GAS muscle in the same position.
The quantification of each metabolite in TA, SOL, and GAS muscles are expressed in the concentration ratio, as indicated in Table 1. It was found that the concentration ratio of IMCL and EMCL changed significantly in SOL muscle.
Table 1 shows the quantification results of IMCL and EMCL, which was calculated using ratios of methylene (CH2) and methyl (CH3) lipid to water in TA, SOL, and GAS. There was a significant change in the ratios of the methyl group of IMCL and EMCL in SOL. The Wilcoxon Signed Rank test was used to determine significant differences among the groups. The significantly different ratios of IMCL (CH3) and EMCL (CH3) were found when compared with NEU-EXT and INT-EXT positions.
When comparing Cr percentage differences between NEU position with INT and EXT positions (Table 2), it was seen that the EXT position of the leg effects the quantification of Cr more than INT in terms of percentage change. However, statistical analysis determined that no significant changes can be seen.

Discussion

1HMRS spectroscopy is a non-destructive and non-invasive method used to separate and measure IMCL from EMCL. It has been used in various clinical applications and in research such as lipid metabolism studies and sport medicine. Recent studies have shown that the various foot orientations could affect the separation of IMCL and EMCL peak from MRS leg muscle spectra [12,17,18].
This study demonstrates how various legs positions affect the appearance of spectra and quantification of 1.5 T 1H MRS measured in the leg muscles of 39 healthy subjects. The obtained spectra showed clear separation between the methylene group of IMCL and EMCL in TA, with less clear separation taking place in SOL and GAS. The different leg positioning was shown to affect the appearance of the metabolite profile obtained from TA, SOL, and GAS with the variation of EMCL CH2 and CH3 resonance line width occurring at different positions in each muscle. Because the IMCL is considered to be composed of spherical lipid droplets distributed homogenously in
muscle cells, magnetic susceptibility of IMCL is independent of the orientation. While the EMCL occurs as fasciae between the muscle bundles, which is orientation dependent with the different types of muscle fibre arrangement or the orientation of the limbs relative to the main magnetic field, there is bulk magnetic susceptibility and induced ECML resonance to allow extra resonance frequency shifts, resulting in the discrimination between EMCL and IMCL being maximised at around 0.2 ppm, when the muscle is relatively parallel to the main magnetic field [9].
The muscle pennation or the angle of muscle fibre relative to the main axis of the muscle is related to the type of muscle and its function. There can be a difference in pennation angles among subjects [18] due to various factors such as sex [19], prior muscle training [20], and muscle atrophy [21]. The muscle fibre orientation is determined by mapping 1H MRS if it is assumed that the long axis of the leg is the same axis as the main magnetic field, and TA muscle fibre is mostly parallel to the main magnetic field; the larger angles being with GAS and SOL [18].
Position alters the muscle angle relative to the main magnetic field, EMCL chemical shift and peak changes due bulk magnetic susceptibility, while the IMCL remains at the same resonance and causes the variation in spectrum appearance. In this study, spectra from GAS muscle was found to have less fitting quality, because the AMARES algorithm is unable to detect and quantify some individual metabolites. When the same muscles are compared in the same subjects, EXT was found to be the position with the lowest fitting quality, despite the good signal-to-noise ratio (SNR) of the obtained signal.
This study found that lipid quantification of EMCL (CH3) and IMCL (CH3) in SOL is statistically significant between the positions at NEU-EXT and INT-EXT, in agreement with the change of spectrum appearance showing that EXT is the position that yields the lowest spectrum fitting quality.
The significant changes in EMCL and IMCL methyl resonance occur despite the lack of SOL spectral appearance, and this is thought to be caused by the overlapping of IMCL and EMCL spectra, as well as bleeding signals from the EMCL CH3 concentration. This causes estimation errors of the spectrum fitting algorithm because methyl EMCL and IMCL resonance has low signal intensity when compared to the intensity of the other metabolites in the same voxel. Therefore, it can be overestimated or underestimated quite easily. Whenever the largest angle of SOL is compared to GAS and TA, it is also suggested that the orientation of the leg is the effect that most alters the soleus and the angle between the muscle and the main magnetic field. Other studies have revealed that the geometry of the leg muscle affects the spectrum appearance [10] and quantification of metabolite [22]. However, the exact angle of the muscle relative to the main magnetic field is beyond the scope of this work.
This study showed the limitations of quantifying metabolite when Cr is used as the reference metabolite or when used as the reference concentration. Whenever the leg is not positioned parallel to the main magnetic field the spectrum fitting quality is affected, and this may result in difficulty in Cr resonance quantification.
Lower spectrum fitting quality occurs in GAS and SOL when compared to TA. This tendency suggests that there are limitations of 1HMRS metabolite quantification from the non-parallel position to main magnetic field in SOL and GAS when using the same algorithm. The fitting algorithm has been used mostly to study TA muscle, which is orientated almost parallel to main magnetic field, but it may be not suitable for other muscles that have different muscle orientations relative to the main magnetic field.
Most published studies have reported IMCL and EMCL concentrations from the methylene (CH2) resonance because this is the most dominate signal and has clear separation of peaks between IMCL and EMCL. However, to study the relationship between various factors that can alter the methylene signal per mole of triglycerides in human fat [23], the methylene resonance of IMCL and EMCL concentration should not be overlooked.

Conclusions

In this study, leg orientation affects the appearance of 1HMRS spectra obtained from TA muscle and quantification in SOL muscle. The change of spectral appearance also impedes the quantification of various metabolites, and this may result in misinterpreting spectrum results used to predict or study diseases. It is also suggested that the magnetic resonance spectroscopy measured from calf muscle can minimise the effect of leg positioning. In order to reduce the possible errors in quantification, close attention to leg positioning is required when measuring 1HMRS in leg muscle.

Acknowledgments

Funds for this research were granted by the Department of Radiologic Technology, Faculty of Associated Medical Sciences, Chiang Mai University, Chiang Mai, Thailand.

Conflict of interest

The authors report no conflict of interest.

References

1. Schrauwen-Hinderling VB, Hesselink MK, Schrauwen P, et al. Intramyocellular lipid content in human skeletal muscle. Obesity (Silver Spring) 2006; 14: 357-367.
2. Kitessa SM, Abeywardena MY. Lipid-induced insulin resistance in skeletal muscle: the chase for the culprit goes from total intramuscular fat to lipid intermediates, and finally to species of lipid intermediates. Nutrients 2016; 8: 466.
3. Krssak M, Falk Petersen K, Dresner A, et al. Intramyocellular lipid concentrations are correlated with insulin sensitivity in humans: a 1H NMR spectroscopy study. Diabetologia 1999; 42: 113-116.
4. Li Y, Xu S, Zhang X, et al. Skeletal intramyocellular lipid metabolism and insulin resistance. Biophysics Reports 2015; 1: 90-98.
5. Consitt LA, Bell JA, Houmard JA. Intramuscular lipid metabolism, insulin action and obesity. IUBMB Life 2009; 61: 47-55.
6. Coen PM, Goodpaster BH. Role of intramyocelluar lipids in human health. Trends Endocrinol Metab 2012; 23: 391-398.
7. Machann J, Stefan N, Schick F. 1H MR spectroscopy of skeletal muscle, liver and bone marrow. Eur J Radiol 2008; 67: 275-284.
8. Pola A, Sadananthan SA, Yaligar J, et al. Skeletal muscle lipid metabolism studied by advanced magnetic resonance spectroscopy. Prog Nucl Magn Reson Spectrosc 2012; 65: 66-76.
9. Szczepaniak LS, Dobbins RL, Stein DT, et al. Bulk magnetic susceptibility effects on the assessment of intra- and extramyocellular lipids in vivo. Magn Reson Med 2002; 47: 607-610.
10. Boesch C, Machann J, Vermathen P, et al. Role of proton MR for the study of muscle lipid metabolism. NMR Biomed 2006; 19: 968-988.
11. Steidle G, Machann J, Claussen CD, et al. Separation of intra- and extramyocellular lipid signals in proton MR spectra by determination of their magnetic field distribution. J Magn Reson 2002; 154: 228-235.
12. Marjanska M, Eberly LE, Adriany G, et al. Influence of foot orientation on the appearance and quantification of 1H magnetic resonance muscle spectra obtained from the soleus and the vastus lateralis. Magn Reson Med 2012; 68: 1731-1737.
13. Vermathen P, Kreis R, Boesch C. Distribution of intramyocellular lipids in human calf muscles as determined by MR spectroscopic imaging. Magn Reson Med 2004; 51: 253-262.
14. Stefan D, Cesare FD, Andrasescu A, et al. Quantitation of magnetic resonance spectroscopy signals: the jMRUI software package. Measurement Science and Technology 2009; 20: 104035.
15. Vanhamme L, van den Boogaart A, Van Huffel S. Improved method for accurate and efficient quantification of MRS data with use of prior knowledge. J Magn Reson 1997; 129: 35-43.
16. Weis J, Johansson L, Ortiz-Nieto F, et al. Assessment of lipids in skeletal muscle by LCModel and AMARES. J Magn Reson Imaging 2009; 30: 1124-1129.
17. Takashima H, Shishido H, Imamura R, et al. Effect of ankle flexion on the quantification of MRS for intramyocellular lipids of the tibialis anterior and the medial gastrocnemius. Radiol Phys Technol 2015; 8: 209-214.
18. Vermathen P, Boesch C, Kreis R. Mapping fiber orientation in human muscle by proton MR spectroscopic imaging. Magn Reson Med 2003; 49: 424-432.
19. Chow RS, Medri MK, Martin DC, et al. Sonographic studies of human soleus and gastrocnemius muscle architecture: gender variability. Eur J Appl Physiol 2000; 82: 236-244.
20. Aagaard P, Andersen JL, Dyhre-Poulsen P, et al. A mechanism for increased contractile strength of human pennate muscle in response to strength training: changes in muscle architecture. J Physiol 2001; 534: 613-623.
21. Narici M, Cerretelli P. Changes in human muscle architecture in disuse-atrophy evaluated by ultrasound imaging. J Gravit Physiol 1998; 5: P73-74.
22. Khuu A, Ren J, Dimitrov I, et al. Orientation of lipid strands in the extracellular compartment of muscle: effect on quantitation of intramyocellular lipids. Magn Reson Med 2009; 61: 16-21.
23. Ren J, Sherry AD, Malloy CR. 1H MRS of intramyocellular lipids in soleus muscle at 7 T: spectral simplification by using long echo times without water suppression. Magn Reson Med 2010; 64: 662-671.
Copyright: © Polish Medical Society of Radiology This is an Open Access article distributed under the terms of the Creative Commons Attribution-Noncommercial-No Derivatives 4.0 International (CC BY-NC-ND 4.0). License allowing third parties to download articles and share them with others as long as they credit the authors and the publisher, but without permission to change them in any way or use them commercially.
 
Quick links
© 2019 Termedia Sp. z o.o. All rights reserved.
Developed by Bentus.
PayU - płatności internetowe