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Review
. 2015 Feb 6;47(2):e139.
doi: 10.1038/emm.2014.101.

Use of in vivo magnetic resonance spectroscopy for studying metabolic diseases

Jong-Hee Hwang  1 , Cheol Soo Choi  2
Affiliations
Review

Use of in vivo magnetic resonance spectroscopy for studying metabolic diseases

Jong-Hee Hwang et al. Exp Mol Med. .

Abstract

Owing to the worldwide obesity epidemic and the sedentary lifestyle in industrialized countries, the number of people with metabolic diseases is explosively increasing. Magnetic resonance spectroscopy (MRS), which is fundamentally similar to magnetic resonance imaging, can detect metabolic changes in vivo noninvasively. With its noninvasive nature, (1)H, (13)C and (31)P MRS are being actively utilized in clinical and biomedical metabolic studies to detect lipids and important metabolites without ionizing radiation. (1)H MRS can quantify lipid content in liver and muscle and can detect other metabolites, such as 2-hydroxyglutarate, in vivo. Of interest, many studies have indicated that hepatic and intramyocellular lipid content is inversely correlated with insulin sensitivity in humans. Thus, lipid content can be utilized as an in vivo biomarker for detecting early insulin resistance. Employing (13)C MRS, hepatic glycogen synthesis and breakdown can be directly detected, whereas (31)P MRS provides in vivo adenosine triphosphate (ATP) synthesis rates by saturation transfer methods in addition to ATP content. These in vivo data can be very difficult to assess by other methods and offer a critical piece of metabolic information. To aid the reader in understanding these new methods, fundamentals of MRS are described in this review in addition to promising future applications of MRS and its limitations.

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Figures

Figure 1
Figure 1
(a) Bruker 9.4T magnetic resonance spectrometer in Lee Gil Ya Cancer and Diabetes Institute, Gachon University. (b, c) Without a magnetic field (outside of the magnet), all of the spins are randomly oriented (b), but within a field (inside of the magnet), all of the spins are aligned with or against the field (quantized at different energy levels, c). When all of the spins are combined, a longitudinal magnetization is generated parallel to the magnetic field. (d) When a small amount of energy is applied to the magnetization by an radiofrequency (r.f.) coil, the magnetization is flipped to another orientation. However, the magnetization tries to return to its original position (the thermal equilibrium (c)) with precession. While in precession, the magnetization also emits energy (d). This energy is detected by a receiver, which generates nuclear magnetic resonance signals.
Figure 2
Figure 2
(a) A NMR spectrum of water (H2O). Water protons resonate at ~4.7 p.p.m. in living tissues. (b) Chemical structure of ethanol and its simplified NMR spectrum. Different types of protons (attached to C1 and C2 carbons) are resonated at two different chemical shifts. Therefore, each different proton can be distinguished in magnetic resonance spectroscopy. NMR, nuclear magnetic resonance.
Figure 3
Figure 3
Comparison between MRS and MRI. (a) For MRS, a schematic explanation on how to obtain an MR spectrum and its example in the human brain. Time domain data (free induction decay: FID) were acquired and they were converted to frequency domain data through fast Fourier transformation (FFT). The resulting spectrum demonstrated a peak/peaks as shown in the example of a tumor. Within the tumor, choline (Cho), creatine (Cre), NAA(N-acetyl aspartate) and lactate doublet peaks are clearly demonstrated. (b) For MRI, a schematic explanation for how to obtain an MRI is provided. 2D/3D time domain data were converted to 2D/3D spatial domain data via FFT. The resulting images can exhibit T1- or T2-weighted contrast depending on the sequence and the parameters employed. MRI, magnetic resonance imaging; MRS, magnetic resonance spectroscopy; 2D, two dimensional; 3D, three dimensional.
Figure 4
Figure 4
(a) Axial image of the liver and the voxel where spectroscopic measurements were obtained. (b) 1H-magnetic resonance (MR) spectrum from the liver clearly shows the methylene peak of triglycerides. (c) Sagittal image of an abdomen; the lumbar spine was set as a landmark to select the location for subcutaneous and visceral fat analysis in transverse images. Lumbar spine L3 and L4 are denoted. (d) Transverse image of an abdomen for fat analysis. Subcutaneous and visceral fat were separated (bottom) and the fat content was quantified after converting those images to black-and-white binary images.
Figure 5
Figure 5
(a) 1H-MR spectrum from soleus muscle. (b) 1H-spectrum from tibialis anterior muscle. Intramyocellular lipid (IMCL), total creatine (tCr) and extramyocellular lipid (EMCL) peaks are delineated.
Figure 6
Figure 6
(a) 31P MRS of human liver. Selected voxel in the transverse image around the liver is shown with the r.f. coil position and the reference phantom for absolute phosphorus metabolite quantification. (b) The human 31P MRS of the liver is shown in the right panel. Hepatic phosphorus metabolites are α-, β- and γ-adenosine triphosphate (ATP), uridine diphosphoglucose (UDPG), nicotinamide adenine dinucleotide (/phosphate) (NADP(/H)), phosphatidylcholine (PtdC), inorganic phosphate (Pi), phosphocholine (PC), phosphoethanol (PE), glycerophosphoethanolamine (GPE) and glycerophosphocholine (GPC). MRS, magnetic resonance spectroscopy; r.f., radiofrequency.
Figure 7
Figure 7
13C NMR spectra from the liver. (a) C-1 glycogen of a doublet peak at 100.1 p.p.m. clearly exhibited together with the lipid peaks from the hepatic lipid carbons. The inlayed trace is zoomed clearly demonstrating the C-1 glycogen doublet. (b) The time course spectra of glycogen peaks at 100.1 p.p.m. demonstrate a clear reduction of C-1 glycogen during a hypoglycemic clamp on a control subject. NMR, nuclear magnetic resonance.
Figure 8
Figure 8
Dietary effect of PUFA and MUFA diets. The differences in PUFA levels are clearly delineated in peak 2 (double-bond peaks in PUFA) and 3 (methylene peaks in between two double bonds in PUFA) in response to the diets. (a) Spectrum from a subject on PUFA (fish oil) diet for >7 years. (b) Spectrum from a control subject who was not on any special diet. (c) Spectrum from a subject on a MUFA (Lorenzo's oil) diet for 8 years. All of the PUFA peaks (2 and 3 peaks) were increased in a subject that had been on a fish oil diet compared with normal and MUFA diets with reference to peak 1 (all double-bond peaks, including MUFA). MUFA, monounsaturated fatty acid; PUFA, polyunsaturated fatty acid.
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