Skeletal muscle lipid metabolism studied by advanced magnetic resonance spectroscopy

Progress in Nuclear Magnetic Resonance Spectroscopy 65 (2012) 66–76

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Progress in Nuclear Magnetic Resonance Spectroscopy journal homepage: www.elsevier.com/locate/pnmrs

Skeletal muscle lipid metabolism studied by advanced magnetic resonance spectroscopy Arunima Pola a,b, Suresh Anand Sadananthan a,b, Jadegoud Yaligar a, Vijayasarathi Nagarajan a, Weiping Han a, Philip W. Kuchel a, S. Sendhil Velan a,b,c,⇑ a

Laboratory of Molecular Imaging, Singapore Bioimaging Consortium, ASTAR, Singapore Singapore Institute for Clinical Sciences, ASTAR, Singapore c Clinical Imaging Research Centre, NUS-ASTAR, Singapore b

a r t i c l e

i n f o

a b s t r a c t

Article history: Received 17 January 2012 Accepted 8 February 2012 Available online 23 February 2012

Ó 2012 Elsevier B.V. All rights reserved.

Keywords: Skeletal muscle IMCL 2D MRS 2D JPRESS 2D LCOSY

Contents 1.

2.

3.

4.

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1. MRS of skeletal muscle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1. Changes in intra-myocellular lipid levels due to age, gender and activity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Factors influencing the 1H NMR spectrum of skeletal muscle: bulk susceptibility and residual dipolar couplings. . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Bulk magnetic susceptibility. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Residual dipolar couplings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Localized magnetic resonance spectroscopy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Single voxel spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Multi-voxel chemical shift imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Comparison of single voxel spectroscopy versus chemical shift imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Two-dimensional localized magnetic resonance spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1. Building block of localized 2D MRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.2. Localized 2D J-resolved spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3. Localized 2D correlation spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

67 68 68 69 69 70 70 70 71 71 72 72 73 74

Abbreviations: ATP, adenosine tri-phosphate; BMI, body mass index; BMS, bulk magnetic susceptibility; CABINET, coherence transfer spin-echo spectroscopy; CHESS, chemical shift selective; CSI, chemical shift imaging; DM, diabetes mellitus; DTI, diffusion tensor imaging; ED, extensor digitorum; EMCL, extra-myocellular lipids; EPI, echo planar imaging; EPSI, echo-planar spectroscopic imaging; EXSY, exchange spectroscopy; fMRI, functional magnetic resonance imaging; FOV, field of view; GL, gastrocnemius lateralis; GM, gastrocnemius medialis; IMCL, intra-myocellular lipids; JPRESS, J-resolved spectroscopy; L-COSY, localized correlation spectroscopy; LCT-COSY, localized constant time correlation spectroscopy; MRI, magnetic resonance imaging; MRS, magnetic resonance spectroscopy; MRSI, magnetic resonance spectroscopic imaging; NA, number of averages; NMR, nuclear magnetic resonance; OVS, outer volume suppression; PB, peroneus brevis; PRESS, point resolved spectroscopy; PUFA, poly-unsaturated fatty acids; RDC, residual dipolar coupling; RF, radio frequency; SAR, specific absorption rate; SD, sprague dawley; SENSE, sensitivity encoding; SM, soleus medial; SL, soleus lateral; STEAM, stimulated echo mode; SVS, single voxel spectroscopy; TA, tibialis anterior; TP, tibialis posterior; TR, repetition time; VAPOR, variable power radio frequency pulses with optimized relaxation delays; WET, water suppression enhanced through t1 effects; ZDF, Zucker diabetic fatty rats. ⇑ Corresponding author at: Laboratory of Molecular Imaging, Singapore Bioimaging Consortium, 11 Biopolis Way, #02-02, Singapore 138667, Singapore. Tel.: +65 64788757; fax: +65 64788732. E-mail address: [email protected] (S.S. Velan). 0079-6565/$ - see front matter Ó 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.pnmrs.2012.02.002

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5.

6.

4.3.1. Measurement of unsaturation within intra- and extra-myocellular lipid pools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3.2. Localized constant-time correlated spectroscopy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4. Multi-voxel 2D MRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Future directions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.1. Ultrafast 2D MRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 C MRS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5.2. Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Magnetic resonance imaging (MRI) is closely related to magnetic resonance spectroscopy (MRS) and yet it only yields maps of tissue water spin density and mobility and remains a nonspecific assessor of tissue function. In contrast, MRS generates specific chemical signatures of metabolites within the body since each metabolite exhibits a unique set of resonances (peaks) with distinct chemical shifts and intensities, peak multiplicities (J-couplings) and dipolar splittings (residual D values), allowing for its identification and quantification. One-dimensional (1D) 1H NMR spectroscopy remains a leading analytical technology for in vivo MRS. Advantages of this approach relative to using other nuclides include more rapid signal acquisition that provides direct information for each resonance enabling the study of metabolic changes on the 1-min timescale. However, severe spectral congestion can significantly hinder the identification and quantification of 1H MR spectra. Two-dimensional (2D) 1H NMR spectroscopy retains many of the benefits of 1D NMR but gains greatly by dispersing the overlapping resonances into a second dimension at the expense of

Fig. 1. Schematic representation of the development of Type 2 diabetes.

much longer signal-acquisition times [1]. The usefulness of this approach in vivo was first realized in the early 1990s, and since then it has been used in biological and medical studies of humans and small animals [2–6]. Although, this technique is going through a development phase for in vivo applications, it can be added to any MRI protocol. This review summarizes the key features of skeletal muscle spectra and describes localized 2D MRS techniques that are suitable for investigating skeletal muscle lipids. In vivo MRS has been used extensively for investigating metabolic pathways, where concentrations of intermediates and their fluxes are controlled by enzymes, whose levels of expression are controlled by genes. In particular, the pathophysiology of diabetes involves decreased insulin secretion and defects in the sensitivity of muscles to insulin. Insulin plays a central role in metabolic homeostasis by enhancing glucose uptake from the blood into metabolically active organs, particularly skeletal muscle. In the skeletal muscle, glucose is used either for ongoing energy requirements or stored as glycogen. Insulin resistance, a state in which excessive amounts of insulin are required for regulating glucose homeostasis, is a co-morbidity state of obesity and is a risk factor for the development of diabetes mellitus (DM) and cardiovascular disease (Fig. 1). Skeletal muscle plays a prominent role in regulating glucose homeostasis as a major site of glucose disposition. Indeed, an association between the accumulation of lipids within muscle and insulin resistance is well established [7,8]. Even though there is a positive correlation between skeletal muscle lipids and insulin resistance, a clear understanding of the lipids in muscle is still lacking, and in fact, lipids in muscle may be more complex than those in other body parts as they depend on the fiber type and/or specific muscle groups in both rodents and humans. Skeletal muscle is structurally organized as different compartments and each of them is unique in terms of their metabolic properties. Different fiber types are known to contain various concentrations of triglycerides. Muscle fibers are classified into several types based on their biochemical, morphological and physiological properties. In addition, they are classified into Type I (slow) and Type II (fast) on the basis of histochemical analysis. Additional classifications can be performed by histochemical staining for myosin ATPase, myosin heavy chain isoforms, and metabolic enzymes. Table 1 summarizes the categories of skeletal muscle fibers based on these different characteristics. The skeletal muscle can be segmented into various compartments on the basis of muscle fiber orientation. Examples of individual muscle compartments are tibialis anterior (TA), tibialis posterior (TP), soleus that has two sub-compartments (medial (SM) and a lateral (SL)), gastrocnemius lateralis (GL) and medialis

Table 1 Categories of skeletal muscle fiber types. Methods of fiber type classification

mATPase Myosin heavy chain Biochemical

74 74 75 75 75 75 75 75 75

Muscle fiber types Category I

Category II

Category III

I, IC, IIC, IIAC MHCI SO

IIA, IIAB MHCIIa FOG

IIB MHCIIx/d(IIb) FG

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Fig. 2. T2-weighted spin-echo images of the human (A–C) and rat (D–F) skeletal muscle measured at 3T and 7T, respectively, in axial (AX), saggital (SAG) and coronal (COR) planes showing tibialis anterior (TA), tibialis posterior (TP), soleus (SL), gastrocnemius medialis (GM), gastrocnemius lateralis (GL), peroneus longus et brevis (PLB) and extensor digitorum longus (EDL) regions. PLB and EDL fibers could not be clearly distinguished in the rat skeletal muscle.

(GM), extensor digitorum (ED), and peroneus brevis (PB). Fig. 2 shows the MR images of human and rodent skeletal muscles with their annotated compartments. TA, located in the lower leg consists of fast twitch glycolytic (Type IIB) muscle fibers that are spindle (fusiform) in shape. SL is predominantly characterized by slow oxidative fibers (Type I) called feathered muscle. The distribution of lipid content among the different types of muscle fibers is very heterogeneous; Type I fibers (slow, oxidative) have a higher proportion of triglycerides than Type II fibers that are fast-twitch and glycolytic [9–11].

and rat muscle, along with creatine (Cr) and phosphocreatine (PCr) [12], choline-containing compounds [13], taurine [2,14] and carnosine [15]. The two sets of lipid resonances with a chemical shift difference of 0.2 ppm in the initial observation [16] are attributed to the intra- and extra-myocellular lipids (IMCL and EMCL). The chemical shift separation of the two lipid pools is due to the fact that they originate from two compartments of different geometrical shape. The maximal separation of the two [CH2]n signals from IMCL and EMCL is observed when the TA muscle is parallel to the static magnetic field, B0, of the MR scanner.

1.1. MRS of skeletal muscle

1.1.1. Changes in intra-myocellular lipid levels due to age, gender and activity Studies on rodents by Neumann-Haefelin et al. [17] showed that the amount of IMCL is influenced by the strain of the rat, and a number of other factors, such as age, gender, and muscle

Fig. 3A and B shows localized 1D 1H MR spectra obtained from the skeletal muscle of human and rat, respectively. It is readily seen that there are two sets of lipid resonances in both human

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Fig. 3. In vivo localized 1D PRESS spectrum of human (A) and rat (B) skeletal muscle acquired at 3T and 7T, respectively. The insets show the location of the voxel from which the spectrum was acquired.

type. This study used different strains including Sprague Dawley (SD), Wistar and Zucker diabetic fatty (ZDF) rats, and showed that younger rats have increased IMCL levels that decrease with age. This observation was made independent of the rat strain, gender and type of muscle. The higher IMCL levels in younger rats are attributed to increased energy expenditure, growth rate and hence metabolic rate. IMCL levels in SM and SL are significantly different in male Wistar and female SD rats that are 10–14 weeks old, but not affected in the TA region. This might be due to variation in oxidative capacity of the TA compartment between animals. The IMCL content in TA and SL muscle of ZDF rats is significantly higher than in Wistar and SD rats. Age-related effects also influence the IMCL levels in ZDF rats and are independent of insulin resistance and diabetes. Further, De Feyter et al. [18] reported that the regional distribution of IMCL within TA of the rat muscle differed by up to 3-fold, depending on the position of the voxel from which the spectrum was obtained. The total creatine content of the TA region did not change as a function of voxel position. Recently, it has been shown that depending on the state of nutrition and body activity, IMCL levels change during the day. It is also observed that starvation and/or strong physical activity during the day lead to a decrease in IMCL [19]. Since IMCL in the various muscle compartments is always metabolically active, it is necessary to maintain standardized conditions of nutrition, physi-

cal activity and time of measurement during the day for metabolic studies. A standardized protocol for depletion of IMCL has been evaluated to obtain reproducible IMCL levels in subjects with a broad range of insulin resistance, exercise capacity and BMI [20]. 2. Factors influencing the 1H NMR spectrum of skeletal muscle: bulk susceptibility and residual dipolar couplings 2.1. Bulk magnetic susceptibility Depending on the geometry and type of tissue, the magnetic field strength that is experienced by nuclei in a compartment changes due to bulk magnetic susceptibility (BMS) differences between the inside and outside of the compartment. The differences in magnetic susceptibility in heterogeneous samples can introduce unanticipated complications to the NMR spectrum. In order to achieve quantitative interpretations of spectra carried out on heterogeneous samples, it is important to estimate the BMS. The estimation of BMS is described in detail by Boesch et al. [21], based on the original formalism of Chu et al. [22]. Several groups have contributed to the understanding of magnetic susceptibility differences in tissues [23]. The bulk magnetic susceptibility of any material is represented by the symbol v, which is defined by the relation

70

M ¼ vH

A. Pola et al. / Progress in Nuclear Magnetic Resonance Spectroscopy 65 (2012) 66–76

ð1Þ

where M is the magnetization vector of the material (the magnetic dipole moment per unit volume) and H is the magnetic field strength. The presence of any nucleus in a magnetic field of strength H creates a magnetic flux density B in its vicinity. The intensity of B depends on the polarizability of the medium. Hence, B = lH where l is the magnetic permeability. In vacuum, B = l0H, where l0 is the permeability of free space. The interaction of moving charges in atoms and molecules within a magnetic field leads to the induction of a bulk magnetization M. Therefore,

orrhages. Using an approach with a phantom as an external reference, low noise measurement of the phase component was performed from which tissue or compartment susceptibility was determined [36]. Recently a method for accurate measurement of magnetic susceptibility and determination of the shape factor in a NMR tube was proposed; it proved to be useful for comparing samples in different solvents and conditions such as temperature and pH [37]. Apart from these studies, predicting the magnitude of shifts in variously shaped compartments of cells and tissues remains a challenging task.

B ¼ l0 ðH þ MÞ

ð2Þ

2.2. Residual dipolar couplings

B ¼ l0 ð1 þ vÞH

ð3Þ

B ¼ lH

ð4Þ

Dipolar couplings occur between pairs of magnetic nuclei and like the scalar coupling, the interactions produce fine structure or splitting of individual resonances in the NMR spectrum. Usually these splittings average to zero in liquids as a result of rapid, isotropic molecular tumbling. However, the establishment of even a small extent of molecular alignment can introduce residual effects of these interactions into the spectrum, resulting in residual dipolar couplings (RDCs). The values of RDCs follow the well-known orientation dependence of the magnetic dipole–dipole interaction with a splitting Dmax. The value of this RDC depends on the alignment angle h with respect to B0 according to the expression

where l is the permeability of the medium. As the values of l0 and H are constants, Eq. (4) shows that the magnetic field around any object changes with the change in its bulk susceptibility leading to a change in Larmor frequency [24]:

x ¼ cBnuc

ð5Þ

which specifies that the resonance frequency of a nucleus is directly proportional to the value of magnetic field Bnuc in its immediate neighborhood. Thus we can say that Bnuc is a function of the magnetic susceptibility of the medium and a change in its value can change the resonance frequency of the nucleus. It is known that the nucleus is surrounded by polarizable material, hence the field in its vicinity also depends on the shape of the macroscopic body. In other words, we can say that Bnuc is also a function of the shape of the body in which the nucleus resides. The calculation of the value of the field in and around the bodies requires solving the Laplace equation for the magnetic potential [25]. The mathematical method of separation of variables can be used for different boundary conditions specified for different shapes [26,27]. Earlier work showed that the value of Bnuc inside a homogeneous spherical body is uniform in a uniform magnetic field, even if the magnetic susceptibility of the material is different from that outside [28,29]. This is also true for the central compartment of concentric spheres and ellipsoids [30,31]. Thus the value of Bnuc inside a spherical body is the same as that of the uniform field outside (B0). This is also the outcome for oblate and prolate spheroids and general ellipsoids; in other words all degree-2 surfaces. However, for a homogeneous cylinder in a uniform imposed field, the field inside is uniform apart from inhomogeneities near the two ends [25]. Thus, the cylinder behaves like an elongated prolate spheroid and the internal field is only parallel to its long axis if the cylinder is parallel to B0. Based on these studies, we can predict the effect of BMS differences between the inside of a cylinder and outside it on the direction of shift in resonance frequency. Several studies show the correction and elimination of susceptibility artifacts in MRI [32–35]. These predict that the phase information available from a gradient-echo measurement can be used to assess clinically the blood clots in cranial hem-

DðhÞ ¼ Dmax

  3 cos2 h  1 2

ð6Þ

In solutions the RDC is generally averaged to zero because of the isotropic tumbling of the molecule and hence its isotropic distribution of orientations. However, in solids the tumbling is restricted and the RDC interaction can become prominent. In vivo MRS of skeletal muscle can show RDCs for some metabolites that are trapped within muscle fibers [38]. This orientation dependent dipolar interaction within molecules leads to split resonances in which the splitting depends strongly on the angle between muscle fibers and B0 [39]. Several studies have validated the finding that Cr and PCr exhibit RDCs [11,40]. Many models have been proposed to account for RDC of the protons of Cr and PCr in skeletal muscle [41]. These include the possibility of binding sites on creatine kinase that reside within ordered structures in the myocytes. Also, the elongated spaces between the actin and myosin chains hinder the t-Cr molecules and hence prevent them from isotropic tumbling. Other molecules including taurine, carnosine [42,43] and lactate [44] also exhibit RDCs. 3. Localized magnetic resonance spectroscopy 3.1. Single voxel spectroscopy Volume localized MRS permits non-invasive assessment of the structure, composition, and metabolism of living tissue. Its uniqueness in studies of skeletal muscle is the ability to distinguish

Fig. 4. Basic modules of the 1D localized MRS and CSI experiment.

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Fig. 5. (A) Variation in IMCL with respect to fiber type in the 1H MR spectra obtained at 7T from a 2 mm3 voxel in tibialis posterior (TP), soleus (SL) and gastrocnemius (GL) regions of the rat skeletal muscle using CSI experiment. (B) Chemical shift imaging grid overlaid on the T2-weighted spin-echo image of the rat skeletal muscle.

between IMCL and EMCL; this is due to the differential effects on the local magnetic field inside cylinders and degree-2 surfaces (and hence the Larmor frequency/chemical shift) arising from a difference in bulk magnetic susceptibility across the bodies. The pulse sequence of 1D MRS consists of four basic modules (see Fig. 4): water suppression, outer volume suppression, localization, and signal acquisition. The water suppression module consists of several chemical-shift selective (CHESS) pulses [45] for selectively exciting the water signal, followed by crusher gradients to dephase the magnetization in the x–y plane and hence suppress the signal. Other water suppression schemes include water suppression enhanced through T1 effects (WET) [46] and variable power radio frequency (RF) pulses with optimized relaxation delays (VAPOR) [47]. Outer volume suppression (OVS) schemes employ a train of RF pulses and gradients prior to the localization for saturating nuclear magnetization that otherwise gives rise to unwanted 1H signals from outside the volume of interest [48]. The single voxel based volume localization module typically involves three RF pulses in conjunction with three slice selective orthogonal gradients. The commonly used single voxel spectroscopic protocols are point resolved spectroscopy (PRESS) [49] and stimulated echo acquisition mode (STEAM) [50]. Both these sequences achieve localization in a single transient. PRESS employs dual spin-echoes with three RF pulses ðp2  p  pÞ in conjunction with three slice-selective gradients for volume localization and achieves a high signal-to-noise ratio (SNR). The STEAM sequence uses three p2 RF pulses with a stimulated echo for volume localization. The STEAM sequence delivers 50% lower SNR compared to the PRESS sequence but permits shorter echo times, thus making it suitable for detecting metabolites with short T2 values. The total time of acquisition for these experiments is the repetition time (TR)  number of averaged transients (NA).

the volume of interest requires more optimization using advanced shimming programs compared with single voxel MRS. In addition, the multi-voxel approaches require efficient water suppression schemes compared with the single voxel methods. CSI experiments can be performed in 2D with slice selection or in 3D covering the whole volume [51,52]. The block diagram for 2D CSI is shown in Fig. 4. It is based on either STEAM or PRESS sequences within which spatial phase encoding gradients are incorporated. The number and direction of phase encoding pulses depend on the number of dimensions explored (1D, 2D or 3D) thus adding to the total acquisition time. The duration of the pulse sequence is equal to TR  N1  N2  N3  NA where Nx is the number of phase encoding steps in each direction and NA is the number of averaged transients. The 1D 1H spectrum obtained from the TP, SL and GL regions of rat skeletal muscle using this technique as shown in Fig. 5 clearly displays the variation of IMCL and EMCL in different regions of the skeletal muscle. 3.3. Comparison of single voxel spectroscopy versus chemical shift imaging The signal-to-noise ratio (S/N) of a resonance in the spectrum from a single voxel experiment is given by

ðS=NÞSV ¼ cV SV

pffiffiffiffiffiffiffiffiffiffiffi NA;SV ;

ð7Þ

where the constant c depends on parameters such as relaxation time, spectral bandwidth, RF-induced nutation angle, and Q-characteristic of the coil: VSV and NA,SV are localized volume and number of averaged transients, respectively. In the case of multi-voxel CSI, S/N is given by [53]:

ðS=NÞSI ¼ cV SI

pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi N1 N2 N3 N A;SI

3.2. Multi-voxel chemical shift imaging

VSI is given by

Single voxel spectroscopy (SVS) methods have a limitation on spatial coverage and are inefficient in applications for which information is required on metabolite levels from different locations in a tissue. The spectroscopic imaging approaches such as chemical shift imaging (CSI) achieve localization with the use of phaseencoding pulse sequences. The magnetic field homogeneity over

V SI ¼

FOV 1 FOV 2 FOV 3 N1 N2 N3

ð8Þ

ð9Þ

Using Eq. (9) in Eq. (8),

ðS=NÞSI ¼

cFOV 1 FOV 2 FOV 3 pffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi NA;SI N1 N2 N3

ð10Þ

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Fig. 6. Basic scheme of a 2D MRS experiment including components of a basic 2D NMR pulse sequence (above) and an in vivo 2D localized MR pulse sequence (below).

Fig. 7. MR pulse sequence of localized 2D J-resolved spectroscopy. The CHESS sequence is used as global water suppression module and the PRESS sequence is used for localization. The time intervals before and after the last p-pulse are incremented in order to achieve the second-dimension [61].

where FOV1, FOV2 and FOV3 are the field of view in each phase encoding direction. When VSV = VSI, single voxel MRS and CSI are equally efficient in terms of S/N per unit time. However, for a single scan the duration of CSI is much longer than SVS, so it becomes a more favorable technique in terms of acquired information per unit time. Several variants of the basic sequence have been designed to reduce the acquisition time of multi-voxel CSI, such as multiple slice CSI [54], turbo CSI [55], fast CSI [56], and CSI with parallel acquisition (SENSE CSI) [57]. In all these experiments, the final results appear in the form of parametric images (metabolic maps) or a matrix of the spectra of the regions to be studied. 4. Two-dimensional localized magnetic resonance spectroscopy Conventional localized 1D MRS including PRESS [49] and STEAM [50] involves recording the signal as a function of a single time variable, and the signal is Fourier transformed with respect to this variable to give a spectrum. The 1D spectrum contains chemical shift information (arising from chemically distinct 1H nuclei present in each metabolite) and J-splitting (spin–spin interactions mediated by electron-nuclear and electron–electron interactions). In 1D localized MRS, what may appear to be a single resonance can in fact be an unresolved multiplet that may contain contributions from resonances of several different compounds. Because the overall 1H spectrum is confined to a narrow frequency range at the field strengths of clinical MR scanners, complicated and poorly resolved spectra are obtained. Over the past decade major efforts have been made by several groups to implement localized 2D MRS on pre-clinical and clinical scanners [2,4,58–60].

Fig. 8. Various J-couplings and the residual dipolar coupling (D1) at 3.9 ppm (indicated by arrow) on a 2D JPRESS spectrum at 3T acquired from a 3 cm3 voxel in the human soleus muscle compartment in dorsiflexion (neutral – 20°) angle [69].

4.1. Building block of localized 2D MRS A simple 2D MRS experiment consists of four major time periods that comprise preparation, evolution, mixing and detection (see Fig. 6). During the preparation period the spin system is manipulated into a coherent non-equilibrium state. For in vivo experiments it is preferable to set the time interval to be

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Fig. 9. MR pulse sequence of 2D shift correlated spectroscopy. CHESS sequence is used for water suppression. The RF pulse scheme consists of three orthogonal slice selective   pulses p2  p  p2 . Spoiler gradients placed symmetrically about the transfer pulse select the coherence pathway [4].

zation is redistributed through chemical exchange or dipolar interactions between nuclear populations that resonate at different frequencies. In addition, the design of the localization module can include coherence transfer where a single-quantum coherence is converted into one or more coherences of higher order, or the spatial localization can occur without coherence transfer. All experiments based on coherence or polarization transfer include a mixing time that transforms coherences into observable magnetization. The magnetization is observed during the detection period and it constitutes the second frequency domain in the 2D spectrum. To improve the signal-to-noise ratio the whole process can be repeated over a number of transients. Thus the acquired signal is a function of two time variables t1 and t2 and the two-dimensional Fourier transformation results in a two-dimensional data matrix with F1 and F2 frequency axes. 4.2. Localized 2D J-resolved spectroscopy

Fig. 10. 2D L-COSY 1H spectrum acquired at 3T from a 3 cm3 voxel in the human soleus muscle compartment in dorsiflexion (neutral – 20°) angle showing the diagonal and cross-peaks generated from saturated and unsaturated groups of IMCL, EMCL lipid pools and other metabolites [73]. Full assignments are given in Table 2.

sufficiently long to allow full thermal equilibrium to be attained by the spin system. During the evolution period the magnetization precesses in an environment that might include refocusing pulses to decouple spin–spin interactions (J) and/or refocus chemical shifts. The evolution period contains a variable delay t1 that is increased during the course of a 2D MRS measurement, from an initial value to a final one using equal time increments (Dt1). At the end of the evolution time, magnetization can either be detected or can be allowed to evolve further. This additional period is called the ‘‘mixing time’’; it is introduced in some 2D experiments such as exchange spectroscopy (EXSY) in which the longitudinal magneti-

Localized 2D J-resolved PRESS (2D JPRESS) is one of the most commonly used techniques for metabolic studies in vivo [61–63]. Fig. 7 shows the pulse sequence for 2D JPRESS. This sequence uses similar RF pulses as those in the PRESS module (see Section 3.1) for volume localization, where a series of FIDs are acquired with different echo times encoding the indirect evolution period (t1). The evolution period is placed before and after the last p-pulse (see Fig. 7). This permits encoding of the J-coupling along the t1 dimension thus improving specificity for detection of particular metabolites. During the evolution period, magnetization evolves under the chemical shift and J-coupling Hamiltonians. After the first half of the evolution period, the p-pulse is applied which results in refocusing the chemical shift during the second half of the evolution period, whereas the evolution of J-coupling is unchanged. During the acquisition period (t2), both chemical shifts and J-couplings evolve in the usual way. Fourier transformation of the data results in a 2D matrix that reveals J-couplings along the F1 dimension and chemical shifts along the F2 dimension. As the coupled spins are dispersed in both the dimensions, this technique resolves overlapping metabolite resonances. The 2D J-resolved methods have been used for several in vivo studies at 1.5T, 3T, 4.7T and 7T [63–67]. At higher fields, the SNR and spectral resolution improve significantly and therefore they can be used for reducing the acquisition time and also to improve spectral resolution. Most of the studies using this approach have been on the brain [60,68]. Very few studies have been on skeletal muscle [2]. Recently we demonstrated the feasibility of investigating J-couplings and RDCs between the various resonances of IMCL and EMCL lipid pools [69]. Fig. 8 shows the

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Table 2 In vivo assignment of the diagonal and cross-peaks in 2D L-COSY spectrum of human soleus muscle [59]. Resonance Diagonal peaks ACH3 (IMCL) ACH3 (EMCL) A(CH2)n (IMCL) A(CH2)n (EMCL) ACH2ACH@CHA(IMCL) ACH2ACH@CHA(EMCL) ACH@CHACH2ACH@CHA (IMCL) ACH@CHACH2ACH@CHA (EMCL) ACH3 (creatine) ACH2 (creatine) ACH@CHA (IMCL) ACH@CHA (EMCL) Cross-peaks A (CH2)n (IMCL), ACH3 (IMCL) A (CH2)n (EMCL), ACH3 (EMCL) ACH@CHACH2A (IMCL), A(CH2)n (IMCL) ACH@CHACH2A (EMCL), A(CH2)n (EMCL) ACH2ACH@CHA (IMCL), ACH2ACH@CHA (IMCL) ACH2ACH@CHA (EMCL), ACH2ACH@CHA (IMCL) ACH@CHACH2 ACH@CHA (IMCL), ACH@CHACH2 ACH@CHA (IMCL) ACH@CHACH2 ACH@CHA (EMCL), ACH@CHACH2 ACH@CHA (EMCL) ACH3 (creatine), ACH2 (creatine)

Chemical shift (ppm) F2, F1 0.90, 1.12, 1.30, 1.52, 2.03, 2.23, 2.77, 2.93, 3.02, 3.92, 5.30, 5.54,

0.89 1.12 1.31 1.52 2.03 2.23 2.77 2.93 3.02 3.93 5.30 5.54

1.29, 1.52, 1.32, 1.55, 5.30, 5.54, 5.30,

0.88 1.12 2.02 2.22 2.02 2.27 2.75

5.50, 2.93 3.02, 3.92

Fig. 11. LCT-COSY 1H spectrum recorded at 3T from the soleus muscle of a healthy subject with TR = 2 s, minimum TE = 30 ms, TCT = 56 ms and voxel size of 27 mL in dorsiflexion (neutral – 20°) angle [80]. Full assignments are given in Table 2.

2D JPRESS spectrum acquired from a soleus muscle compartment with a voxel size of 3 cm3. The spectrum highlights diagonal and cross-peaks generated from saturated and unsaturated moieties of IMCL, EMCL lipid pools and other metabolites.

4.3. Localized 2D correlation spectroscopy The pulse sequence for localized 2D correlation spectroscopy (LCOSY) uses a combination of three slice selective RF pulses as shown in Fig. 9. This sequence has a localization module that is based on coherence transfer spin-echo spectroscopy (CABINET) for volume localization [4]. The localization is achieved by combining a spin-echo and a coherence transfer echo. The last p2 pulse serves as a coherence transfer pulse along with spatial slice selection. The incremental evolution period for the second dimension is inserted immediately after the formation of the spin-echo; this allows determination of the connectivity of the metabolite peaks in the second-dimension of the 2D spectrum. The advantage of this pulse sequence is that the volume selection and coherence transfer are achieved simultaneously without adding more RF and gradient pulses. Several groups have implemented the L-COSY technique for various applications in both 3T and 7T MR scanners [2,4,59,60,70– 73]. Fig. 10 shows the 2D L-COSY spectrum from a soleus muscle with a voxel size of 3  3  3 cm3 (27 mL) volume. The assignments of various resonances are given in Table 2. In addition to the methyl (CH3) and n-methylene (CH2) groups of IMCL and EMCL, the L-COSY spectrum provides information on cross-peaks that arise from scalar couplings within various resonances of IMCL, EMCL and glycerol backbone protons. Cross-peaks C1, C3, and C8 arise from spin–spin coupling between olefinic (ACH@CHA) and allylic methylene protons (ACH2 CH@CHA) of IMCL and EMCL, respectively. The cross-peaks C2, C4, and C7 arise from the indirect spin–spin coupling between olefinic (ACH@CHA) and diallylic methylene protons (ACH@CHACH2ACH@CHA) of IMCL and EMCL, respectively. The C5 cross-peaks result from the correlation between (CH2) and (CH) groups of glycerol backbone protons. The L-COSY spectrum also exhibits orientation-dependent RDCs of creatine and carnosine (C6 cross-peaks) [74,75]. 4.3.1. Measurement of unsaturation within intra- and extramyocellular lipid pools The degree of lipid unsaturation within the IMCL and EMCL is of clinical importance. The effects of fatty acids on energy metabolism and metabolic signaling are modulated by the degree of unsaturation [76–78]. The cross-peaks C1, C2 and C3, C4 can be used to estimate the degree of unsaturation within IMCL and EMCL, respectively. The volumes of the cross-peaks C1, C3 between olefinic (ACH@CHA) protons and allylic methylene (CH2CH@CH) protons represent the monounsaturated fatty acid component of the two lipid pools. Similarly the cross-peak volumes C2, C4 between olefinic and diallylic methylene (ACH@CHACH2ACH@CHA) protons represent polyunsaturated fatty acids (PUFA). The ratios of these cross-peak volumes define the degree of unsaturation [73]. Further study conducted to evaluate the degree of unsaturation in normal, overweight and obese subjects by the L-COSY approach indicated that the polyunsaturated fatty acids (PUFAs) are reduced in obese and overweight subjects compared to normal-weight subjects, reflecting a lower degree of unsaturation [74]. This approach was further used in establishing the gender differences in lipid metabolism, and identifying distinct patterns of fat metabolism in skeletal muscle [75]. It was also shown that female subjects have a reduced degree of unsaturation in comparison with males. Recently the L-COSY approach has been implemented on a 7T whole body scanner to evaluate the lipids in skeletal muscle [59]. This study also highlights the advantages of increased field strength for studies on in vivo lipid metabolism. 4.3.2. Localized constant-time correlated spectroscopy The advantages of 2D MRS over one-dimensional approaches are that connectivity between distinct individual spins in

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molecules is delineated and J-coupled multiplet resonances are spread over two spectral dimensions. However, in the L-COSY experiment the resonances along the diagonal exhibit the same overlap as in 1D MR spectra resulting in the same spectral resolution for resonances without J-coupling. Girvin et al. demonstrated that the constant-time approach can be utilized to increase the spectral resolution along the diagonal [79]. Recently, localized constant-time correlated spectroscopy (LCT-COSY) sequence that combines the constant-time approach with localized MRS has been proposed [80]. The LCT-COSY experiment was implemented for skeletal muscle applications to improve the spectral resolution of the diagonal peaks. Fig. 11 shows the 2D spectrum from LCT-COSY experiment on skeletal muscle. We can readily notice the clear separation of cross-peaks C1, C3, C8, and C2, C4, C7 between olefinic and allylic and diallylic methylene groups of IMCL and EMCL.

4.4. Multi-voxel 2D MRS Most of the 2D MRS experiments used for in vivo applications have been implemented in the single voxel mode that has limitations of both long acquisition time and limited spatial coverage. Recently a novel 4D MR spectroscopic imaging (MRSI) technique has been developed, combining two spectral dimensions with two space-encoding dimensions, on a 3T MR scanner [81]. This 4D MRSI pulse sequence combines the high acquisition speed of echo planar spectroscopic imaging (EPSI) [82–84] and the increased spectral information of L-COSY. The approach has been used in vivo to evaluate the feasibility of detecting IMCL, EMCL and other metabolites in healthy human calf muscle.

5. Future directions 5.1. Ultrafast 2D MRS The major limitation of 2D MRS approaches is that they require longer acquisition times than the 1D methods. Hence reduction of time is an important objective, since reduced scan-time improves patient comfort and reduces motion artifacts. Spatially encoded single-scan ‘‘ultra-fast’’ experiments [85,86] permit acquisition of an entire 2D spectrum in a single transient. Single-shot imaging approaches have earlier been implemented for functional MRI (fMRI) [87], diffusion tensor imaging (DTI) [88] and echo planar imaging (EPI) [89]. Single-scan MRI approaches have been well established for both clinical and research applications [90,91]. In 2002, Frydman et al. [85] demonstrated ultrafast acquisition of 2D NMR spectra based on the concept of parallelizing all steps (see Fig. 6) involved in a 2D experiment. This was accomplished by partitioning the sample into a series of independent sub-ensembles and characterizing each of them by an individual evolution process. Such partitioning can be achieved by applying a time incremented series of spatially selective excitation RF-pulses throughout the sample followed by a common mixing period. Independent signal recording from each component of this ensemble leads to the simultaneous acquisition of a complete 2D NMR data set. The basic principles and features of the new ultrafast 2D NMR spectroscopy have been reported in detail [92]. Since the first study, several alternative approaches have been proposed for achieving heterogeneous evolution of spin systems [93–99]. The translation of this approach to clinical systems requires sophisticated hardware in terms of gradient capabilities. The first in vivo implementation of this technique was performed on a 7T whole body scanner [100]. The approach will significantly reduce the acquisition time and improve the utilization of this technique for investigating the kinetics of metabolism in vivo.

5.2.

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13

C MRS

13

C MRS is a useful approach to the study of metabolism and metabolic fluxes in vivo. In vitro high resolution 13C NMR studies of cells have used the 200 ppm dispersion domain of the 13C spectrum for exploring metabolism [101]. The large chemical shift dispersion permits detection of a wide range of metabolite signals which are otherwise difficult to resolve in 1H MR spectra. The 13C MR approach is still under-developed for in vivo applications due to low natural abundance of 13C (1.1%), complexity in the design of dual tuned RF coils for different body applications, RF power deposition (specific absorption ratio (SAR)) limitations, and poor signal-to-noise ratio. Research is being performed in several laboratories using polarization transfer and decoupling techniques to improve the spectral sensitivity [102,103]. Nevertheless, 13C can be used to study glycogen and triglyceride metabolism, since these molecules typically exist at concentrations over 50 mM. In most of the applications of 13C MRS to human skeletal muscle, glycogen has been observed and this represents (together with IMCL) the main energy storage within muscle [104]. In particular, glycogen levels in skeletal muscle of exercising subjects [105–109] and in patients with different pathological conditions have been investigated [110–115]. Due to the technical challenges, only a few in vivo studies have been performed on skeletal muscle. 6. Conclusions Worldwide, the number of people with diabetes and other metabolic diseases has risen at an alarming rate over the last several decades, and these diseases have become a pandemic. The major mechanism contributing to the pathogenesis of diabetes, and other metabolic diseases related to obesity, is lipotoxicity, which results from the excessive deposition and accumulation of lipids in peripheral tissues beyond their oxidative or storage capacities. As skeletal muscle is the major site for glucose clearance, and lipid accumulation in skeletal muscle is a major risk factor for diabetes, it is of particular significance to understand the progression of lipid accumulation and the kinetics of lipid turnover. The advanced MRS techniques described above will permit deeper understanding of lipid metabolism in skeletal muscle including the metabolic and clinical consequences of defects of the lipid-desaturase enzymes. Acknowledgements We are thankful for intramural research funding from Singapore Bioimaging Consortium (SBIC) and Singapore Institute for Clinical Sciences (SICS), Agency for Science Technology and Research (ASTAR), Singapore. References [1] R.R. Ernst, G. Bodenhausen, A. Wokaun, Principles of nuclear magnetic resonance in one and two dimensions, Clarendon, Oxford, 1987. [2] R. Kreis, C. Boesch, J. Magn. Reson. B 113 (1996) 103–118. [3] B. Sebrie, J.P. Gillet, A. Lefaucheur, J.C. Sebille, Beloeil, FEBS Lett. 423 (1998) 71–74. [4] M.A. Thomas, K. Yue, N. Binesh, P. Davanzo, A. Kumar, B. Siegel, M. Frye, J. Curran, R. Lufkin, P. Martin, B. Guze, Magn. Reson. Med. 46 (2001) 58–67. [5] W. Shen, X. Mao, Z. Wang, M. Punyanitya, S.B. Heymsfield, D.C. Shungu, Acta Diabetol 40 (Suppl 1) (2003) S51–S54. [6] C. Boesch, J Magn. Reson. Imaging 25 (2007) 321–328. [7] M. Krssak, K. Falk Petersen, A. Dresner, L. DiPietro, S.M. Vogel, D.L. Rothman, M. Roden, G.I. Shulman, Diabetologia 42 (1999) 113–116. [8] C. Boesch, J. Machann, P. Vermathen, F. Schick, NMR Biomed. 19 (2006) 968– 988. [9] R.S. Staron, Can. J. Appl. Physiol. 22 (1997) 307–327. [10] D. Pette, R.S. Staron, Int. Rev. Cytol. 170 (1997) 143–223. [11] D. Pette, R.S. Staron, Rev. Physiol. Biochem. Pharmacol. 116 (1990) 1–76. [12] R. Kreis, M. Koster, M. Kamber, H. Hoppeler, C. Boesch, Magn. Reson. Med. 37 (1997) 159–163.

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