Fundamentals of MR Spectroscopy

3.16

Fundamentals of MR Spectroscopy

MA McLean, Cancer Research UK Cambridge Research Institute, Cambridge, UK ã 2014 Elsevier B.V. All rights reserved.

3.16.1 3.16.1.1 3.16.1.2 3.16.1.3 3.16.1.4 3.16.1.5 3.16.1.6 3.16.1.7 3.16.1.8 3.16.1.9 3.16.1.10 3.16.2 3.16.2.1 3.16.2.2 3.16.2.3 3.16.2.4 3.16.3 3.16.3.1 3.16.3.2 3.16.3.3 3.16.3.4 3.16.3.5 3.16.3.6 3.16.3.6.1 3.16.3.6.2 3.16.3.6.3 3.16.3.7 3.16.4 3.16.4.1 3.16.4.2 3.16.4.3 3.16.4.4 References

Basic Concepts Nuclear Spin The Chemical Shift The Free Induction Decay and the Spectrum Phase Adjustment The Problem of Signal Strength And the Other Problem: Field Inhomogeneity Peak Patterns and J-Coupling Data Sampling and Spectral Resolution T1 Relaxation T2 Relaxation Nuclei that Can Be Used for MRS 13 C-MRS 19 F-MRS 31 P-MRS 1 H-MRS Key Methodologies Prescan Optimization Localization Outer Volume Suppression Lipid Suppression Water Suppression Metabolite Specificity Sequence optimization Spectral editing Multiple quantum filtration Broadband Decoupling Complexities and Caveats Chemical Shift Displacement Phased Array Coils Spurious Echoes Motion

Glossary Chemical shift Difference in Larmor frequency resulting from different chemical environments, due to shielding. Echo time (TE) Time to the peak MR signal from the initial excitation. ISIS (image-selected in vivo spectroscopy) Unlike STEAM and PRESS, which can be performed in a single experiment, ISIS requires eight difference experiments, with an add/ subtract scheme to cancel out signals from regions outside the voxel of interest. Useful for 31P MRS since the signals are acquired directly after the detection pulse. J-coupling The magnetic field of one nucleus influences the external magnetic field sensed by the neighboring nucleus. This is mediated by binding electrons in the bond between the two coupled nuclei (these are weak spin–spin interactions). This results in a spectrum with the resonance

Comprehensive Biomedical Physics

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of the coupled nucleus split into two lines, such that a doublet of two peaks is seen, for example, the lactate doublet. The coupling constant denotes the difference in frequency between the two peaks. Localization Selection of three orthogonal slices such that the region at the intersection of the slices is the source of the signal. PRESS (point-resolved spectroscopy) Acquires the second echo from a 90
–180
–180
RF pulse sequence. PRESS provides improved SNR but previously required longer echo times, although recent advances allow PRESS to be performed at short TE. PRESS is less sensitive to motion than STEAM. Proton decoupling Weak interactions between phosphorus atoms and protons in the molecules or in surrounding water lead to a broadening of spectral lines. By proton

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Fundamentals of MR Spectroscopy

decoupling, 31P spectrum will contain sharper lines and proportionally higher peak intensities (given that the peak area is constant). Repetition time (TR) of an MR pulse sequence Time between successive excitations. Shimming Correction of magnetic field inhomogeneities by adjusting static gradients. A key component of preparation for MRS, without which the FID decays rapidly, the signal intensity will appear lower than its true value, and the Lorentzians obtained with transformation into the frequency domain will be widened and distorted.

STEAM (STimulated Echo Acquisition Mode) Uses 90
RF pulses to acquire a stimulated echo from the voxel, requires gradient suppression, and has lower SNR than PRESS or ISIS (see other two single-voxel techniques); but it requires shorter echo times. Can detect more complicated spin systems such as glutamate and glutamine. Zero filling With the fast Fourier transform, the acquisition time is often set to record the FID until well past the point where the signal disappears into the noise. Instead of recording a signal with nothing in it but noise, the signal is lengthened by adding zeros.

Nomenclature and Symbols

NAAG PCr PDE Pi PME PRESS SNR STEAM STIR T TE TR VOI Vx DE s

ATP CHESS Cho Cr CSD CSI DQF FFT FID FWHM GABA ISIS k mIns MRSI NAA

3.16.1 3.16.1.1

Adenosine triphosphate Chemical shift selective Choline Creatine Chemical shift displacement Chemical shift imaging Double quantum filtration Fast Fourier transform Free induction decay Full width at half maximum height g-Amino butyric acid Image-selected in vivo spectroscopy Boltzmann constant Myo-inositol Magnetic resonance spectroscopic imaging N-acetyl aspartate

Basic Concepts Nuclear Spin

Magnetic resonance spectroscopy (MRS), similar to magnetic resonance imaging (MRI), starts with the observation that certain nuclei possess a magnetic moment associated with their quantum spin properties. When placed in a magnetic field, they align themselves either with or against it. These two different states (e.g., quantum spin m ¼ ½) have different energies. Transitions between energy levels can be induced by applying an oscillating magnetic field of the correct frequency. These transitions release energy that can be detected.

3.16.1.2

The Chemical Shift

Since nuclei are spinning, they do not point along the applied field but instead precess around B0 with a frequency o related to the applied field strength, o ¼ g B0 (see Chapter 3.01). In spectroscopy, this Larmor equation is modified: the local field a nucleus experiences, and thus the frequency at which it precesses, is influenced by the electron cloud surrounding it. These orbiting electrons shield the nuclei to varying extents dependent on the chemical bonds the atom participates in. A hydrogen atom bonded to the highly electronegative oxygen will be shielded to

N-acetyl aspartyl glutamate Phosphocreatine Phosphodiester Inorganic phosphate Phosphomonoesters Point-resolved spectroscopy Signal-to-noise ratio STimulated Echo Acquisition Mode Short-time inversion recovery Temperature in Kelvin Echo time Repetition time Volume of interest Voxel size Energy of transition Shielding constant in the Larmor equation

a lesser extent than one bonded to carbon. This is represented by including the shielding constant s in the Larmor equation: o ¼ gB0 ð1  sÞ

[1]

Shielding causes frequency shifts about a million times smaller than o, so s is commonly reported in the dimensionless unit of parts per million (ppm). A chemical will (under the same conditions) always produce peaks at the same frequency in ppm, although the frequency shift in hertz is a function of field strength. It is therefore possible to identify chemicals by their position on the ppm scale. Zero for hydrogen is defined by a chemical not found in vivo called tetramethylsilane. Water is at 4.7 ppm and is used as the reference point for the frequency scale in vivo. Note that ppm increases from right to left and not left to right.

3.16.1.3

The Free Induction Decay and the Spectrum

A plot of signal intensity versus frequency is known as a spectrum (right panel of Figure 1). One frequency in the spectrum is seen in the time domain (which plots signal detected vs. time) as a single sine wave, its amplitude decreasing over time as the signal decays. Multiple frequencies give decaying sine waves with different wavelengths, which co-add with a

Fundamentals of MR Spectroscopy

Spectrum

Free induction decay

PCr

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Figure 1 A 31P-MRS spectrum (right) and corresponding free induction decay (left) from a human leg in vivo, showing peaks from free inorganic phosphate (Pi), phosphodiesters (PDE), phosphocreatine (PCr), and the g-, a-, and b-peaks of adenosine triphosphate (ATP).

complicated pattern of constructive and destructive interference. The resulting free induction decay (FID) is analyzed by mathematical processing techniques to extract these frequencies. Analysis generally begins with the Fourier transform so that we work in the frequency domain, but direct analysis of the decaying time domain signal is also possible and has several advantages (Belkic´ & Belkic´ 2010).

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3.16.1.4

Phase Adjustment

Following Fourier transformation, spectral peaks have arbitrary phase. An adjustment is generally applied before integrating peak areas so that all (or most) point up. In the first step (the ‘zero-order’ phase correction), the same phase is applied across the entire spectrum. In 1H-MRS, this is sometimes automated: one can calculate the amount of correction required to phase the water peak and then apply that across the entire spectrum. The second adjustment, which may be needed (the ‘first-order’ phase correction), involves applying a linearly varying phase across the spectrum (e.g., 2
per ppm). This can help handle distortions caused by mistimed data collection.

3.16.1.5

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SD of noise

0 4

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-1

Frequency (ppm) Figure 2 Spectral quality assessment on 1H-MR spectrum from normal brain. SNR is peak height divided by the standard deviation of noise; full width at half of this maximum height (FWHM) of the peak reflects magnetic field homogeneity.

The Problem of Signal Strength

A fundamental limitation of MRS is signal strength. The population distribution between the two possible energy states (þ½ or ½) follows the Boltzmann distribution: the ratio of spins in the lower and higher energy states is exp(DE/kT ), where DE is the energy of transition between the states (¼gB0h/ 2p), k is the Boltzmann constant and T is the temperature in Kelvin. At physiological temperatures, thermal energy kT  DE, so this ratio is nearly 1: transitions in one direction are almost entirely canceled out by transitions in the other direction and net signal is low. (For an exception, see 13C hyperpolarization in Section 3.16.2.1.) The largest peaks appearing in hydrogen (1H) MRS in vivo arise from water at 4.7 ppm and fat at about 1 ppm. Most metabolites of interest give peaks in the narrow range of frequencies between water and fat and are of very much lower intensity because of their lower concentration in the tissue. A kilogram of tissue contains 30–50 mol of water but only 0.001–0.01 moles of chemicals such as phosphocreatine

(PCr), choline-containing compounds, or N-acetyl aspartate (NAA). Therefore methods are applied to suppress or exclude water and fat (Section 3.16.3). This difference in concentration between water and metabolites also explains the fundamental limitation of signal-tonoise ratio (SNR) on in vivo MRS. MRI, which relies on the highly abundant water and fat signals, can be used to create images where the individual pixels have dimensions on the order of 1  1  1 mm. In MRS, where the chemicals are >1000 times less abundant, ‘voxels’ (volume elements) are studied with a minimum size of about 1  1  1 cm. SNR is further maximized by averaging multiple transients. Signal increases linearly with the number of averages (n), whereas the noise pffiffiffi pffiffiffi increases as n. Therefore SNR increases as n. SNR is measured as the height of a given peak above the baseline divided by the standard deviation of points over a region free from visible peaks (Figure 2). SNR is an important indication of spectral quality, since there is obviously little

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point in analyzing spectra where peaks of interest are indistinguishable from baseline noise.

3.16.1.6

And the Other Problem: Field Inhomogeneity

The other main measure of spectral quality is the width of the peaks, which is limited by magnetic field homogeneity. If B0 varies over the spectroscopic volume of interest (VOI) then peak frequencies also vary. Averaging over the entire VOI broadens the peaks and worsens overlap between them. Some degree of peak overlap can be accommodated by parametric analysis (Belkic´ and Belkic´, 2010), but the best and most reproducible results are obtained when peaks do not overlap. Field homogeneity is assessed as the full width at half maximum height (FWHM) of one or more spectral peaks (Figure 2). Traditionally, FWHM is reported in units of hertz rather than ppm, because the intrinsic linewidth does not depend directly on field strength, although measured linewidths are usually wider at higher field because of the increased susceptibility effects. Since peak width in vivo is mainly determined by B0 homogeneity rather than intrinsic chemical effects, most peaks of interest have similar width. Indeed, if a spectral peak has FWHM much lower than the metabolite average, it may be an artefactual spike. Similarly, if a peak has a FWHM much larger than most of the metabolites, it may be due to macromolecules (e.g., proteins or lipids) rather than to small molecules (e.g., amino acids and sugars). Nowadays, on clinical scanners, homogeneity adjustment (shimming) is a largely automated procedure based on field mapping, but on preclinical machines and in more challenging anatomic sites in humans, it may be necessary to intervene and adjust the shim currents manually.

First, peaks have different areas depending on how many equivalent atoms contribute. For example, the methyl group (–CH3) of lactate has three hydrogen atoms. The methyl group rotates around its bond to the rest of the molecule so rapidly (while the whole molecule also tumbles in solution) that these three hydrogens are magnetically indistinguishable. Thus, they all resonate at the same frequency and contribute to a peak at 1.33 ppm, which is three times larger than it would be if only one hydrogen atom was present. Second, the local magnetic field experienced by a nucleus is affected by not only the electrons surrounding it but also any other magnetic nuclei nearby. The lactate methyl group is affected by the hydrogen attached to the adjacent carbon (Figure 3). This neighbor can be aligned either with or against the main field, causing either an increase or a decrease in the local field experienced by the methyl hydrogens (Figure 4). Therefore, the signal is observed at either slightly higher or

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Lactate: HOOC-CHOH-CH3

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3.16.1.7

Peak Patterns and J-Coupling

4.0

Although peak areas are proportional to the amount of chemical present, peaks from within the same molecule can differ (e.g., the individual phosphorus moieties of adenosine triphosphate (ATP) in Figure 1, and the peaks of lactate in vitro (Figure 3)) for the following reasons. Neighbours 1

2

3

Possible alignment

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Frequency (ppm)

Figure 3 1H-MR spectrum of lactate at 3T (TE ¼ 280 ms) and its chemical structure. The large doublet peak at 1.33 ppm (intensity ratio 1:1) arises from the CH3 group, and the small quartet at 4.1 ppm (intensity ratio 1:3:3:1) arises from the hydrogen on the middle carbon.

Predicted spectrum J

Examples Lactate 1.3 ppm a- & g-ATP

GABA 2.3 ppm b-ATP

J

J Lactate 4.1 ppm

Figure 4 Prediction of spectral peak patterns from the number of neighboring magnetic nuclei. All permutations of possible alignment with and against the nucleus of interest are examined and divided into those that will increase or decrease the local magnetic field experienced or leave it unchanged. The frequency separation between adjacent peaks is J, the coupling constant.

Fundamentals of MR Spectroscopy

lower frequency than in the absence of a neighbor. Instead of one ‘singlet’ peak, two peaks are recorded (a doublet), each having half the total area. The peaks’ separation is J, the coupling constant, typically 5–10 Hz for small metabolites. If a nucleus has >1 magnetic neighbors, there are multiple possibilities for how those neighbors are aligned with or against the field (Figure 4). Two neighbors produce a triplet with intensity ratios1:2:1; three neighbors give a quartet, 1:3:3:1; four neighbors give five peaks, 1:4:6:4:1; and so on, following the pattern of Pascal’s triangle. In practice, these more complicated ‘multiplet’ structures are only observed in vitro (e.g., Figure 3). The measurement of multiplet peaks is further complicated by their phase evolution. The echo time of 280 ms in Figure 3 was chosen because the phase of coupled peaks in a spin-echo experiment modulates with a periodicity of 2/J, and since J  7 Hz for lactate, 2/J  280 ms. At TE ¼ 2/J, 4/J, 6/J, etc., coupled peaks appear in phase with each other and with uncoupled peaks; at TE ¼ 1/J, 3/J, 5/J, etc., they are antiphase (i.e., pointing down relative to the uncoupled peaks); at intermediate echo times they are a messy mixture of in-phase and antiphase signals, which destructively interfere and cannot be reliably measured. Most long-TE spectra are recorded at echo times around either 280 or 140 ms so that doublet peaks from lactate and alanine are either in phase or antiphase. (The antiphase option has the advantage of discriminating between these inverted coupled metabolites and upright macromolecule signal.)

3.16.1.8

Data Sampling and Spectral Resolution

Another limit on data analysis in the frequency domain is data sampling. In MRI, only a brief sample of the echo is needed to determine the magnitude (and sometimes phase) of the signal. In MRS using conventional Fourier-based processing, to resolve two peaks with a separation of 5 Hz, the FID should be collected for at least 1/5 Hz or 0.2 s. The rate of data sampling is the inverse of the spectral width, and the total sampling time is this multiplied by the number of points collected. ‘Zero filling,’ or padding the end of the FID with zeros, is sometimes applied: in the frequency domain, this is the equivalent of interpolating between adjacent spectral points (Figure 5). Although sampling pffiffiffi the entire echo as for imaging would increase SNR by 2, it is customary to start sampling in the center of the echo and collect an FID, as shown in Figure 1. Indeed, some MRS sequences are not based on echoes: signal is stimulated and acquired beginning immediately at the end of the excitation pulse. The time delay of the hardware switching (as well as any time needed for refocusing gradients if slice selection is used) can cause loss of the initial points of the FID, which distorts the baseline, but this can be compensated for in the analysis. Failure to sample the full decay of the FID (truncation) is like convolving the FID with a rectangle (an abrupt on/off switch). The Fourier transform of this is a sinc function in the frequency domain. Thus, spectral peaks have sharp wiggles at the base. This effect can be minimized by applying a Gaussian

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Figure 5 1H-MR spectrum of water illustrating truncation artifact. Undersampling and interpolation introduce a step change in the FID (top left) and sinc-modulated wiggles around the base of prominent peaks in the spectrum (bottom left). Multiplication of the FID by a Gaussian filter smoothes this step change (top right) and removes the wiggles (bottom right).

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Table 1 Estimated T1 (s) and T2 (ms) relaxation times of commonly studied metabolite peaks in 1H-MRS spectra of healthy adult cerebral white matter at 1.5 and 3 T

NAA 2.0 ppm Creatine 3.0 ppm Choline 3.2 ppm Myo-inositol 3.6 ppm Glutamate 2.35 ppm Macromolecule 0.9 ppm Water 4.7 ppm

T1 at 1.5 T (s)

T1 at 3 T (s)

T2 at 1.5 T (ms)

T2 at 3 T (ms)

1.30a 1.40a 1.10a 1.19c

1.35b 1.24b 1.08b 1.01b 1.17b

436a 239a 375a 270c

295b 156b 187b

d

0.25f 0.85g

d

1.05g

d

d

200e

44f 80g

d

60g

a

Rutgers DR, Kingsley PB, and van der Grond J (2003) Saturation-corrected T1 and T2 relaxation times of choline, creatine and N-acetyl aspartate in human cerebral white matter at 1.5 T. NMR in Biomedicine 16: 286–288. b Mlynarik V, Gruber S, and Moser E (2001) Proton T(1) and T(2) relaxation times of human brain metabolites at 3 Tesla. NMR in Biomedicine 14: 325–331. c Kreis R, Ernst T, and Ross BD (1993) Development of the human brain: In vivo quantification of metabolite and water content with proton magnetic resonance spectroscopy. Magnetic Resonance in Medicine 30: 424–437. d No report found. e Choi C, Coupland NJ, Bhardwaj PP, et al. (2006a) T2 measurement and quantification of glutamate in human brain in vivo. Magnetic Resonance in Medicine 56: 971–977. f Behar KL, Rothman DL, Spencer DD, and Petroff OAC (1994) Analysis of macromolecule resonances in 1H NMR spectra of human brain. Magnetic Resonance in Medicine 32: 294–302. g De Graaf RA (2007) In vivo NMR Spectroscopy: Principles and Techniques, 2nd edn. Chichester: Wiley.

or Lorentzian filter in the time domain before transformation (Figure 5). This ‘apodization’ (foot removal) smoothes over the abrupt transition in the FID, and the wiggles disappear.

3.16.1.9

T1 Relaxation

T1 relaxation has similar effects on MRS and MRI experiments. After excitation, the nucleus requires five times the T1 interval to recover to equilibrium. If the repetition time (TR) is less than this, the signal S detected per excitation is reduced (saturated) according to S ¼ S0 ð1  expðTR=T1 ÞÞ

[2]

where S0 is the unsaturated signal (i.e., at a TR of 6–10 s). Shorter TRs can nonetheless be advantageous, since averaging over multiple TRs may recover this lost signal and more. The relative signal per unit time for a given TR (assuming the excitation flip angle is 90
) can be calculated pffiffiffiffiffiffiby dividing the signal per transient above by a factor of TR to account for the number of averages. The optimal TR to maximize signal is about the same as T1, 1–1.5 s for 1H metabolites in the brain. However, the heavy saturation at this TR complicates attempts at quantification, which becomes dependent on the exact value of T1: therefore longer TRs of 2–6 s are often used. For other nuclei (e.g., 31P), smaller excitation angles are often used to maximize signal and the optimum flip angle can be calculated as cos1(exp(TR/T1)). As in MRI, the T1 of metabolites can be measured through either saturation recovery or inversion recovery experiments. In saturation recovery, spectra are generated at a range of TRs, and signal for each metabolite is fit to eqn [2] above. In inversion recovery experiments, a constant TR is used throughout, and measurements are acquired at a range of inversion times TI. The fit is then performed to the modified equation: S ¼ S0 ð1  2expðTI=T1 ÞÞ

[3]

The T1s of small metabolites in the brain tend to be fairly long, around 1–1.5 s, whereas the T1s of macromolecules are

short (Table 1). This difference can be exploited to separate their signals. Short-time inversion (STIR) pulses can be used to null the signal from macromolecules as in MRI. However, it can be difficult to combine these pulses with water suppression in the pre-excitation interval, and a significant proportion of the metabolite signal also is nulled, which again makes quantification sensitive to the exact T1 of the metabolites. Behar et al. (1994) proposed nulling the metabolites instead. The metabolites of interest have sufficiently similar T1s that an inversion time of around 600 ms at 1.5 T cancels nearly all their signal while the signal from macromolecules is retained. Subtracting acquisitions with and without the inversion pulse gives the metabolite signal free from macromolecules. However, this method suffers the same motion sensitivity as all subtraction-based techniques (Section 3.16.3.6), and pathological lipids seen in tumors may have elevated T1 more similar to metabolites. One further complication of tumors is that MRS is often performed after the administration of gadolinium (Gd) contrast agents, which can affect the T1 of metabolites and water. It has been reported that contrast administration does not greatly affect the peak ratios (Murphy et al., 2002), but it should be borne in mind as a possible confounding factor.

3.16.1.10

T2 Relaxation

In MRI, increasing the echo time of a sequence leads to a straightforward exponential decrease in the signal intensity recorded because of the loss of phase coherence of the nuclear spins. The signal from tissue water decays rapidly (Table 1), while the T2 of free fluid in ventricles or cysts is very long. The T2s of several brain metabolites are also fairly long (Table 1). 1H-MRS can therefore be performed at long echo times to reduce the contribution of water, lipids, and other macromolecules to the spectrum and give a flatter baseline from which to assess metabolite peak areas. However, attempts

Fundamentals of MR Spectroscopy

at quantification can be further hampered since the signals are so heavily T2-weighted, particularly if water is to be used as a reference. Short echo times have several further advantages. Since the overall signal is stronger, time signals can be acquired more quickly and/or from smaller voxels (improving the temporal and/or spatial resolution). In addition, several metabolites of interest can be detected which are not seen at long echo times. Their signal decreases through not only T2 decay but also the effects of J-coupling described above. The T2s of uncoupled metabolites can be assessed by acquiring a series of FIDs at increasing TE. As in MRI, T2 can be calculated by a fit of the resulting signal (S) to the equation: S ¼ S0 expðTE=T2 Þ

[4]

Determining the T2 of coupled metabolites requires the use of methods such as selective refocusing to counteract the J-coupling effects (Choi et al., 2006a; see Section 3.16.3.6.2).

3.16.2

Nuclei that Can Be Used for MRS

A limited number of elements in the periodic table can be observed using MRS, including hydrogen 1H, phosphorus 31 P, carbon 13C, and fluorine 19F. Generally, only nuclei with odd atomic weights produce signal, although there are exceptions such as deuterium 2H. These nuclei possess a net magnetic dipole moment.

3.16.2.1

13

C-MRS

For example, 13C exhibits magnetic resonance but 12C and 14C do not. This limits signal detection since only about 1.1% of carbon nuclei contribute. Tracer studies can exploit this limited indigenous signal: 13 C-labeled sugars, amino acids, etc. can be added to the medium in a cell culture, injected into a blood vessel, or ingested. Studies of in vivo metabolism of 13C labeled glucose have been performed in humans in brain (Gruetter et al., 1994), liver (Beckmann et al., 1993), and muscle (Shulman et al., 1990). In the brain, rates of tricarboxylic acid (TCA) cycle metabolism and neurotransmitter cycling can be determined. In the liver, rates of glycogen synthesis and breakdown are of interest. Naturally abundant 13C can also be used to measure glycogen in the liver and muscle (Jue et al., 1989) without the need for tracer administration. Relative content of saturated and mono- and polyunsaturated fatty acids in liver and adipose tissue can also be determined, with or without dietary adjustment (Thomas et al., 1996). A new development in 13C studies is hyperpolarization, which uses either para-hydrogen species (Bowers and Weitekamp, 1987) or a combination of cryogens and microwaves (dynamic nuclear polarization; Ardenkjaer-Larsen et al., 2003) to manipulate the population distribution of spins. Normally, thermal equilibrium ensures that almost identical numbers of nuclei inhabit the higher and lower energy states, such that we can detect only a tiny percentage of the atoms present. Hyperpolarization induces a short-lived state wherein

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this population difference is enhanced, leading to a dramatic increase in MR signal. Although the hyperpolarization rapidly decays, the signal can be maintained long enough to enable injection into an organism. In Figure 6, conversion of 13C-pyruvate to lactate is tracked in a mouse glioma model. Tumor proliferation causes avid metabolism, which is shown to be reduced by anticancer treatment. A phase I trial in prostate cancer is underway, in the hopes that this may enable early assessment of drug efficacy (Kurhanewicz et al., 2011).

3.16.2.2

19

F-MRS

Tracer studies may also be performed from anticancer drugs containing the stable 19F isotope, such as 5-fluorouracil. When this analog of uracil is incorporated into DNA, the fluorine blocks further replication, and cell proliferation is halted. The 19 F isotope is 100% abundant and nearly as MR-sensitive as 1 H, and mammals lack indigenous background signal, so detection of moderate drug doses is possible. Signals may also be resolved from anabolic products (nucleotides) and catabolic products such as fluoro-b-alanine (Wolf et al., 2000). Fluorine is also finding an increasing range of molecular imaging applications (Lanza et al., 2005). For example, contrast agents can be labeled with fluorine so that their concentration in the tissue can be quantified as well as their effect on water relaxation. Fluorine can also be used to label ion chelators for in vitro measurement of intracellular levels of such species as calcium, magnesium, lead, and zinc (Smith et al., 1983).

3.16.2.3

31

P-MRS

Most early MRS in vivo used phosphorus, 31P. Although the sensitivity is less than 1H and the additional hardware costs money, several technical challenges are alleviated: the wide spread in frequency of peaks reduces demands on B0 homogeneity, and no suppression of unwanted signals (e.g., water, and fat) is needed, which simplifies experimental design. A simple surface coil placed over muscle can detect PCr, ATP, and inorganic phosphate (Pi) as seen in Figure 1, and can follow changes during and after exercise. PCr is the main energy reserve of the tissue. It is very high at rest, falls rapidly on initiation of exercise, and rapidly recovers to baseline values on cessation. In contrast, ATP does not change appreciably during exercise: it is replenished by the PCr reserves at first and thereafter by a combination of oxidative and anaerobic metabolism of glucose. Peaks from adenosine diphosphate are also present but are not generally resolved from the overlapping g- and aATP. Other bases besides adenosine can also be phosphorylated, so sometimes the more general term NTP is used, for nucleoside triphosphate. Pi increases during exercise as the PCr is expended, and it may also shift in frequency because of binding of hydrogen ions. This can be used to calculate the intracellular pH of the tissue: the calibration curve of frequency against pH follows a sigmoidal distribution, with a pKa of about 7.0. Most of the Pi signal observed is intracellular, since the extracellular space makes up a small proportion of muscle tissue volume, so the

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Fundamentals of MR Spectroscopy

1

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Lactate Pyruvate

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120 110 100 e m fro

c je in

90 80 70 60 50 40 30 CSI 20 10 n tio

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175 170 Chemical shift (ppm)

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Figure 6 13C spectroscopic data from a glioma-bearing rat. Spectra were generated using a surface coil, following administration of 2 ml 75 mM hyperpolarized [1-13C] pyruvate. The peaks in the summed spectrum are (1) lactate, 185 ppm; (2) pyruvate hydrate, 181 ppm; (3) alanine, 178 ppm; and (4) pyruvate, 173 ppm. In some experiments, a bicarbonate signal at 162 ppm was also visible. The first 120 s of data acquisition are shown, and the back edge shows a summation of all the spectra. The changes, with time, of the pyruvate and lactate peak integrals are also shown. The time window used for acquisition of the CSI is indicated, at approximately 20–31 s after pyruvate injection. Reproduced from Day SE, Kettunen MI, Cherukuri MK, et al. (2011) Detecting response of rat C6 glioma tumors to radiotherapy using hyperpolarized [1-13C]pyruvate and 13C magnetic resonance spectroscopic imaging. Magnetic Resonance in Medicine 65: 557–563, with permission from John Wiley and Sons.

estimate is denoted pHi. Other methods are available for estimating extracellular pH (pHe); however, these are generally invasive, requiring injection of pH-sensitive indicators into the tissue, which are not taken up into the cells but remain in the extracellular space (Zhang et al., 2010). During recovery, the Pi peak rapidly returns to baseline values and the pHi also normalizes. Unfortunately, when the pH is changing most rapidly, the Pi peak often disappears because of an undershoot in its recovery curve, making the estimation of pHi impossible. Nonetheless, some diagnostic information can be obtained: for example, the lack of muscle acidity during exercise in McArdle’s syndrome was first observed 30 years ago (Ross et al., 1981). Phosphorus studies have also been performed in the heart, a specialized muscle with added complexities. Not only must the motion be taken into account in some way (e.g., by gating acquisition to the cardiac cycle) but also the comparison of rest and exercise is complicated since the heart is always working to some degree. Changes in heart rate with exercise can also cause practical problems with data acquisition. In addition, placement of an RF coil over the heart is insufficient for spatial localization, since stronger PCr signals arise from the skeletal muscle of the chest wall; therefore more complicated pulse sequences are needed (Section 3.16.3.2). 31 P-MRS in the brain has similarities to muscle: large reserves of PCr may be depleted during ischemic insults, accompanied by acidification of pHi, although in the brain such tissue damage tends to be irrecoverable. Milder chronic metabolic abnormalities may perhaps be observed in epilepsy, migraine, psychiatric disorders, dementias, etc., but the spectral patterns tend to lack sufficient specificity for conclusive

diagnosis of brain disorders. Similar to the estimation of pH, local magnesium ion concentration can be inferred from the frequency of the b-ATP peaks, which may be of interest in conditions such as subarachnoid hemorrhage (Yang et al. 2008). 31 P MRS can also be used to examine membrane turnover: phospholipids incorporated into cell membranes are too immobile to produce much MR signal, but intermediates in the buildup and breakdown of cell membranes can be seen, such as phosphocholine and phosphoethanolamine, known collectively as phosphomonoesters (PME). Similar to the choline peak in 1H-MRS, the PME peaks can be elevated in conditions involving high-membrane turnover, such as in proliferating tumors. Changes in PME have also been found to help indicate response to cancer therapy. Reductions in the ratio of PME to nucleotide triphosphate in superficial lymph nodes following treatment were found to predict favorable response to therapy in non-Hodgkins lymphoma (Griffiths et al., 2002). Kettelhack et al. (2002) reported that post-therapeutic changes in ratios of PME to b-ATP were indicative of response to isolated limb perfusion in soft tissue tumors. Abnormalities in phosphodiesters such as glycerophosphocholine and glycerophosphoethanolamine have also been observed in psychiatric conditions such as schizophrenia (Puri, 2006).

3.16.2.4

1

H-MRS

Since the early 1990s, most MRS studies have used 1H due to technological advances making such studies more feasible

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Residual of fit NAA

Cho

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Estimated baseline 4.0 3.8 3.6 3.4 3.2 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 0.80 0.60 0.40

Chemical shift (ppm) Figure 7 A H-MR spectrum generated from data acquired at 1.5 T with echo time ¼ 35 ms and repetition time ¼ 1.5 s from an 8-cm3 voxel in the white matter of the centrum semiovale, fitted against a library of model spectra using LCModel (Provencher, 1993). The fit is shown in bold red overlaid on the raw data in black. The C-spline fit to the baseline and the residual signal also are shown. Peaks are N-acetyl aspartate (NAA), creatine (Cr), choline-containing compounds (Cho), myo-inositol (Ins), macromolecules (MM), and overlapping multiplets of glutamate, glutamine, and other amino acids (Glx). 1

(and to the better spatial resolution obtainable than with other nuclei). A typical spectrum from normal brain is shown in Figure 7. The largest peak in the spectrum of healthy adult brain comes from NAA, although it is unclear why so much is needed (Birken and Oldendorf, 1989). It may be involved in myelin synthesis, storage of aspartate, or merely metabolism of the minor neurotransmitter N-acetyl aspartyl glutamate (NAAG). It is called a ‘neuronal marker’ because it is present in neurons but not in differentiated glial cells (Urenjak et al., 1993) and is reduced in most conditions involving neuronal damage or death. At short echo times, the neurotransmitter NAAG is also detectable, apparently localized mostly in the white matter (Pouwels and Frahm, 1997). Owing to overlap between NAA and NAAG in brain spectra, some report their sum, NAA þ NAAG. The next largest signal is the overlapping peaks of creatine (Cr) and PCr. Since depletion of PCr leads to increases in Cr, the total peak area is not sensitive to mild or moderate brain insults and is often used as an internal reference. Reporting metabolite ratios to Cr compensates for any variability in hardware performance, B0, and B1 variability, etc., which would otherwise affect the comparison of results between and within individuals. However, the content of creatine does vary considerably between white and gray matter in the brain (McLean et al., 2000), so this normalization must be interpreted with caution (Figure 8). The third largest peak comes from choline-containing compounds (Cho). Choline is a constituent of cell membranes and therefore present at high concentrations; however, when it is

incorporated into membranes, its molecular mobility is greatly reduced and so is its MR signal. The majority of what we detect therefore comes from the small molecules phosphocholine and glycerophosphocholine (Bluml et al., 1999), which are intermediates in the synthesis and breakdown of membranes and myelin. The choline peak is therefore (sometimes reversibly) elevated in conditions involving cell proliferation, such as tumors, or breakdown of the membranes or myelin, such as multiple sclerosis. In brain tumors, there is some evidence linking the amount of choline with the degree of proliferation (Matsumura et al., 2005). However, there is substantial choline in healthy cerebral tissue, while choline levels may be very low in higher-grade glioma, as the mobile lipids characteristic of necrosis begin to dominate. Thus, brain tumors may have choline that is either higher or lower than normal-appearing tissue (Howe et al., 2003). Outside the brain, attempts to use choline in differential diagnosis and grading of tumors and benign lesions have often been disappointing, since benign growths may also exhibit large choline peaks, and choline is not always detected in malignancy. The careful characterization of spectral quality may help to distinguish methodology-related false negatives from tumors where choline can more confidently be said to be below a certain threshold concentration. At long echo times (>100 ms), NAA, Cr, and Cho are the major peaks seen in healthy brain (e.g., Figure 2, TE ¼ 144 ms). Mobile lipid peaks in high-grade brain tumors or lactate (Section 3.16.1.7) in hypoxia may also be seen at long echo times. At shorter echo times, additional peaks of interest are detected. Myo-inositol (mIns), a sugar involved in osmotic

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NAA area

NAA/Cr

Figure 8 The effect of inhomogeneous coil sensitivity on metabolite measurement. A 12 12 grid of brain spectra was generated using MRSI at 3 T in a healthy volunteer, and the central 5  5 voxels falling within the PRESS-localized volume were analyzed (left). NAA peak areas show a strong gradient from top to bottom of the head due to inhomogeneous coil sensitivity (middle), which is eliminated in a display of NAA/Cr (right). (The left–right variability in NAA/Cr is due to voxels along the midline containing more gray matter and therefore more creatine.)

homeostasis and (at very low levels) in cell signaling, is present at concentrations of several millimoles per liter in healthy brain. It arises principally from glia and may increase in conditions involving glial cell proliferation, such as astrocytoma or gliosis associated with chronic epilepsy (Woermann et al., 1999) or multiple sclerosis (Fernando et al., 2004). Since the hydrogens on the sugar ring of mIns are nearly but not quite equivalent, they give rise to a heavily overlapping structure of coupled multiplets. At low field strengths (1.5 T and below), this multiplet structure collapses into a large pseudo-singlet, which can be assessed at short TE. However, the peak cannot be seen at longer TE due to coupling interactions, and at higher field strengths the collapse into a pseudo-singlet is not complete. Individual peaks can be detected, but since they are lower, they can be harder to assess reliably. Several amino acids can also be detected at short echo times in healthy brain, for example, glutamate, glutamine, and g-amino butyric acid (GABA), closely linked metabolites central to neurotransmission. Glutamate is the main excitatory and GABA the main inhibitory neurotransmitter in the cerebrum. Following release, they are taken up by the postsynaptic neuron and surrounding astrocytes, where they are converted to glutamine and exported to the neurons for reuse. This transmitter cycling has been determined to be the main consumer of energy in the brain (Sibson et al., 1998). A variety of techniques for improved detection of these metabolites have been developed (Section 3.16.3.6). Finally, spectroscopy of the healthy prostate gland reveals a strong signal from citrate at 2.6 ppm, which decreases in cancer (Section 3.16.3.6.1). Spermine may also be detected. Prostate spectroscopy is reviewed extensively in Chapter 3.18. This section gives only an abbreviated highlight of the 40 metabolites that have been detected in 1H-MRS in vivo under various conditions. For a more comprehensive list, see (de Graaf, 2007) or (Govindaraju et al., 2000).

3.16.3 3.16.3.1

Key Methodologies Prescan Optimization

Performing 1H-MRS on a clinical scanner is similar to performing MRI: control settings are loaded from a stored protocol, a

VOI is prescribed graphically, and a fully automated prescan is performed. Historically, and on preclinical scanners, more user interaction is needed, because every sample is different and therefore interacts differently with the RF coil (demanding calibration of RF transmission and reception) and the applied magnetic field (demanding shimming). In addition, ‘tune and match’ capacitors on the coil may need adjustment to attain maximum sensitivity, unless it is designed to be broadly in tune over a wide range of filling factors.

3.16.3.2

Localization

Some localization is achieved simply by placing the anatomy of interest in proximity to the RF coil. This may be sufficient, for example, for phosphorus metabolites in skeletal muscle, as in Section 3.16.2.4. Similarly, liver metabolism of fluorinecontaining anticancer drugs can be performed by placing a surface coil over the liver. Other tissues close to the coil are unlikely to contribute much signal. However, spatial localization is usually mandatory. It can be achieved, as in imaging, through a combination of sliceselective pulses and phase encoding (frequency encoding is not used, as it would discard the chemical specificity). Phase encoding can be applied in one-, two-, or three dimensions: this is called chemical shift imaging (CSI), or preferably magnetic resonance spectroscopic imaging (MRSI). With the TR of 1 s commonly used in spectroscopy, it is unfeasible to acquire very many phase encoding steps in three dimensions, but matrices on the order of 12  12  8 steps are feasible, and larger matrices can be acquired using fast imaging techniques (Maudsley et al., 2009; see 00321). Slice selection can be used either in conjunction with phase encoding or on its own. In MRI, slice-selective 90
and 180
RF pulses usually are both applied along the same axis (Z), thereby reinforcing selection of the same slice. If the 180
pulse were instead applied along X or Y, this would select a slab. In a double spin-echo experiment, the 90
and both 180
pulses are applied along mutually orthogonal axes (X, Y, and Z), selecting a cuboid region of tissue where the three slices intersect. This is the basis of point-resolved spectroscopy (PRESS) (Bottomley, 1987; Figure 9 top). Although PRESS is now the most commonly used technique for 1H-MRS, on early scanners with poor gradient hardware performance it was impossible to obtain echo times shorter than about 60 ms. Although this was adequate for NAA, creatine, and choline, shorter TE species were not accessible. The other main disadvantage of PRESS is that 180
pulses have lower bandwidth, and therefore poorer spatial selectivity than 90
pulses (see Section 3.16.4.1). A rival technique is STimulated Echo Acquisition Mode (STEAM; Figure 9 bottom). Here, the voxel is defined by three orthogonal 90
pulses. This delivers not only better slice profiles than PRESS, and a lower specific absorption rate (SAR) due to the smaller pulse amplitudes, but also shorter echo times because of differences in timing between stimulated and spin echoes (Frahm et al., 1989). However, STEAM sacrifices half the SNR achievable from the same volume of tissue by PRESS, and the effect of stimulated echoes on J-coupling is complex (Ernst and Hennig, 1991).

Fundamentals of MR Spectroscopy

PRESS 90˚

180˚

180˚

RF

Gz

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Gx TE Echo

STEAM 90˚

90˚

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However, signal yield compares favorably with STEAM for short-T2 species. ISIS tends to use ‘adiabatic’ pulses for localization. These are long pulses, often in multiple segments, particularly well suited for inversion, such as the hyperbolic secant pulse (Silver et al., 1984) and BIR-4 (a 4-segment B1-insensitive rotation; Garwood and Ke, 1991). Such pulses are particularly advantageous when used with surface coils or in other circumstances of inhomogeneous B1 fields, because the flip angle delivered is less dependent on the local B1 field. Adiabatic pulses can also be used in single-shot sequences such as PRESS: this improves slices profiles, particularly at high field, because of the higher bandwidths used. Such ‘localization by adiabatic selective refocusing’ (LASER; Garwood and DeLaBarre, 2001) requires relatively long echo times to play out the lengthy train of adiabatic pulses, but nonetheless retains good SNR for coupled metabolites (coupling evolution is partially suppressed by the adiabatic pulse train, so peak patterns are more similar to those seen at much shorter TE in conventional PRESS). Also, because the pulses have long duration but relatively low amplitude, they are associated with lower heat deposition in the tissue, which is a particular limitation at high field strengths. Hybrid techniques using conventional excitation and adiabatic refocusing combine some advantages of both (semi-LASER; Scheenen et al., 2008).

3.16.3.3 TE/2

TM

TE/2 Echo

Figure 9 Pulse sequence diagrams for the common localization methods PRESS and STEAM. Each involves three slice-selective pulses with gradients applied along orthogonal axes X, Y, and Z to select a cuboid volume at their intersection, and crusher gradients (shaded in gray) to dephase signals from outside this voxel.

Localization for 31P and other short-lived isotopes can be achieved using phase encoding alone (3D-CSI), or 2D-CSI, where the phase encodes immediately follow a single sliceselective excitation pulse. If single-voxel localization is desired, it can be achieved using techniques such as image-selected in vivo spectroscopy (ISIS; Ordidge et al., 1986), where at the beginning of each TR period, one or more 180
pulses are used to invert one or more orthogonal slices immediately before (nonselective) excitation. Since the magnetization remains along B0, no T2 decay occurs before excitation. The number and orientation of the inversion pulses is varied in subsequent TR periods, so that over the course of an eight-step cycle, data are collected with all 23 combinations of inversion on/off along the three axes, and data from the cuboid VOI desired are calculated through a series of additions and subtractions. Simpler schemes of ISIS can be used: for example, slice selection along a single direction requires only a two-step cycle. Since localization along all axes depends on 180
pulses, ISIS has poor slice profiles and high SAR, and the eight-step cycle confers an undesirable degree of motion sensitivity.

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Outer Volume Suppression

Poor voxel definition can be improved using outer-volume suppression (OVS), to suppress the intense lipid signals from the scalp in brain MRS. Imaging studies also use ‘saturation bands’ to suppress signal from adipose tissue or from sources of magnetic susceptibility and motion such as the gut, lungs, and heart. In OVS, a slice of tissue is selectively excited and dephased: for MRS, typically at least six such slices are saturated, killing signal alongside the six faces of the cuboid VOI. Additional slices oriented oblique to the VOI may be optionally prescribed: for example, in prostate MRSI, a long train of OVS pulses with sharp excitation profiles can be used to better saturate fat at the expense of water suppression (Tran et al., 2000). OVS pulses can even replace slice selection. For example, prescription of a cuboid PRESS box within the brain for MRSI would preclude sampling many areas of eloquent cortex, whereas prescription of an octagonal band of narrow suppression slabs to crush the signal from the scalp may enable acquisition of data out to the edges of the brain. In practice, lipid suppression efficiency may not suffice for short-TE MRSI, but it can produce acceptable spectra at TE 272 ms over several slices acquired simultaneously in the brain (Duyn et al., 1993). A more common application of OVS for localization is a technique known as overpress (Tran et al., 2000), where a PRESS box is selected with dimensions 10–40% larger than desired, and OVS pulses are used to trim the edges. Since the high-bandwidth OVS pulses define the box shape rather than the lower bandwidth 90
and (particularly) 180
pulses of PRESS, the box edges are sharpened and the effects of chemical shift misregistration are reduced (Section 3.16.4.1).

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3.16.3.4

Lipid Suppression

An alternative approach to lipid suppression is to null macromolecule signal using a STIR pulse (with TI  200 ms), as has been shown for 3D mapping of metabolites over the entire brain using echo planar spectroscopic imaging (Maudsley et al., 2009). Since the metabolite T1s are only 1–1.5 s, such inversion unavoidably decreases the metabolite signal and complicates quantification, but whole-brain coverage would be very difficult to achieve without it.

3.16.3.5

Water Suppression

Although it is possible to analyze metabolite signals in 1H-MR spectra without suppressing the very intense signal from tissue water, generally some suppression is applied in order to reduce artifacts. For example, tiny distortions at the base of the water peak can be seen because of mechanical vibrations in the scanner hardware (Clayton et al., 2001; Figure 10). These can extend over a wide range of frequencies, and although they are small in relation to the water peak, if the water is unsuppressed then they can swamp the metabolites of interest. They can be identified by the way they are symmetrically reflected about the water peak with mirrored phase. The application of water suppression reduces the size of these artifacts to the point that they may be lost in the noise. Similarly, eddy currents in the scanner hardware distort the measured shape of peaks at short echo times. If spectra are generated both with and without water suppression, a correction can be applied (Klose, 1990). The most common technique for water suppression uses chemical shift selective (CHESS) pulses (Haase et al., 1985). A narrow band of frequencies (50–150 Hz) centered on water is selectively excited and then dephased using crusher gradients. This cycle of excitation and dephasing is repeated typically three times at the beginning of each TR. The excitation flip angles are tailored to ensure that a small but consistent

3 ´ 105

2 ´ 105

1 ´ 105

0

residual water peak remains, which can be used to determine phase adjustment. Variants on this technique such as VAPOR (variable pulse power and optimized relaxation delays; Tkac et al., 1999) further fine-tune the number, timings, and powers of the CHESS pulses in order to achieve better performance in demanding circumstances (e.g., ultra-short TE experiments at high field). This technique reduces the dependence of suppression performance on B1 and T1 inhomogeneity. Frequency-selective water suppression pulses can also be inserted within the spin-echo period rather than before excitation (e.g., MEGA; Mescher et al., 1998). This helps to suppress T1 recovery of water signal during the spin-echo experiment. These pulses can also double up as spectral editing pulses (see Section 3.16.3.6.2). It is possible to exploit instead the short T1 of water to null its signal (e.g., to examine metabolite resonances very close to 4.7 ppm). However, the difference in T1 between water and metabolites is not huge, so metabolite signal is also reduced and quantification complicated, as in the case of lipid suppression.

3.16.3.6

Metabolite Specificity

A fundamental problem of 1H-MRS is the narrow range of frequencies of the peaks of interest, but there are several methods for singling out an individual needle from this haystack. Sequence optimization, spectral editing, and multiple quantum filtration are described briefly below, while 2D NMR techniques are discussed later (see Chapter 3.23).

3.16.3.6.1 Sequence optimization Metabolite specificity can sometimes be achieved through adjustment of simple parameters such as the echo time. For example, selecting TE140 ms causes inversion of the doublet peaks of lactate (Section 3.16.1.7). In conditions such as inborn errors of metabolism, which are not characterized by accumulation of mobile lipids, this may allow quantification of lactate. Long echo times may also be used to discriminate the long-T2 singlet peak of glycine from the short-T2 multiplet of mIns. Discrimination between more complicated multiplet structures may require numerical optimizations to suggest the best sequence timings, which may depend on field strength. For example, the citrate multiplet at 2.6 ppm (a valuable marker of healthy prostate tissue) can be observed in phase at echo times of around 130 ms at 1.5 T, while at 3 T an echo time >240 ms would be needed (Trabesinger et al., 2005). Similarly, a TE of 80 ms at 3 T has been suggested for assessment of glutamate as a pseudo-singlet with the adjacent glutamine largely dephased and the underlying macromolecule signal decayed (Schubert et al., 2004), although other techniques may give better repeatability in vivo (Hancu, 2009).

3.16.3.6.2 Spectral editing

-1 ´ 105 5.2

5.0

4.8

4.6

4.4

4.2

Frequency (ppm) Figure 10 Harmonic artifact. When the vertical scale of the water spectrum from Figure 5 is increased 32, distortions appear due to mechanical vibrations in the scanner hardware. The upfield and downfield signals mirror each other.

Spectral editing exploits situations where atoms that are close neighbors on the same molecule are distant neighbors in spectral frequency. Their frequency separation enables manipulation of one signal without directly affecting the other (by using very sharp chemical shift selective pulses as in water suppression). Their physical proximity (the basis of J-coupling) means that perturbations of one affect the signal of the other.

Fundamentals of MR Spectroscopy

269

NAA off Cr on

Cho off Lac on 3.5

3.0

2.5 2.0 Frequency (ppm)

1.5

1.0

3.5

3.0

2.5 2.0 Frequency (ppm)

1.5

Figure 11 Spectral editing of lactate. Left: stacked display of interleaved spectra from a phantom containing physiological concentrations of lactate, NAA, creatine, choline, myo-inositol, and glutamate (‘off’: conventional spectrum at TE 144 ms, where the lactate CH3 doublet is inverted; ‘on’: frequency-selective inversion pulses are applied at 4.1 ppm, and the doublet appears upright). Right: ‘on’ ‘off’ yields the full lactate signal while most other peaks are nulled (dashed line); ‘on’ þ ‘off’ gives uncoupled peaks with lactate removed (solid line).

For example, the methyl peak of lactate at 1.3 ppm is coupled to a proton at 4.1 ppm, and selective inversion of the latter reverses phase evolution of the former. If spectra are generated at TE 144 ms without editing pulses, the doublet is inverted relative to uncoupled peaks (Section 3.16.1.7); if two editing pulses with optimized timings are inserted, signal is refocused as a positive doublet (Figure 11). Subtraction of (editing on–editing off) therefore yields 100% of the lactate signal, while peaks that are not coupled to any protons in the region of 4.1 ppm (such as NAA, Cr, Cho, and – ideally – lipids) appear the same in the two experiments, so subtraction nulls them. Addition of signals from the two experiments instead yields these uncoupled signals free of lactate. Although uncoupled peaks are well filtered, other coupled metabolites may pass through the net, for example, lactate at 1.33 ppm can be overlapped by threonine at 1.31 ppm, coupled to a proton at 4.25 ppm (Choi et al., 2006b); alanine at 1.4 ppm, coupled to a proton at 3.8 ppm; and macromolecules. Contribution of macromolecules can be diminished through a further cycling step (ibid) or the use of T1 nulling techniques (Section 3.16.1.9). Spectral editing has been used for both coupled and uncoupled signals (100% of lactate signal can theoretically be recovered, although for more complicated spin systems such as the triplet of GABA the yield is only 50%). However, similar to other subtraction techniques, it is sensitive to motion between the two acquisitions and to imperfections or drift in hardware performance. As shown in Figure 11, generated spectra with editing pulses on and off should be interleaved to minimize the effect of variability over the acquisition period.

3.16.3.6.3 Multiple quantum filtration In multiple quantum filtration, coupled spins are induced to enter a state of magnetization that uncoupled spins do not enter, for example, a double quantum state in double quantum filtration (DQF). Application of a gradient causes the coupled spins to acquire phase at twice the rate of uncoupled spins. When they are brought back to the ground state, application of a gradient twice as large rephases these coupled spins but dephases spins that had not been in the DQ state. Triple or

zero quantum filtration experiments can also be performed, although DQF is the most common. DQF strongly suppresses uncoupled signals, but the maximum theoretical signal yield is only 50%, since only half of the coupled species’ magnetization can enter the DQ state. Some unwanted coupled signal (e.g., macromolecules) may also pass the filter as in spectral editing, so further methods may be needed to remove contamination. DQF is a single-shot technique (i.e., not based on subtraction), so it is inherently less sensitive to motion than spectral editing.

3.16.3.7

Broadband Decoupling

As in homonuclear J-coupling (Section 3.16.1.7), interactions also occur between atoms of different isotopes (heteronuclear coupling), for example, most 13C peaks are multiplets because of coupling with nearby hydrogens. Sensitivity is reduced, because split peaks have lower individual SNR. Broadband decoupling, similarly to spectral editing, selectively saturates one nucleus to inhibit coupling interactions involving it. To inhibit all 1H–13C interactions, the full range of 1H frequencies must be targeted. Such ‘broadband’ decoupling requires long pulse trains. For example, WALTZ-16 (Shaka et al., 1983) uses 16 composite pulses played out during data acquisition. Heat deposition can limit application in vivo, particularly at higher field strengths.

3.16.4

Complexities and Caveats

Although acquisition of MR time signals is relatively straightforward, there are some hurdles in interpretation that can trip the unwary.

3.16.4.1

Chemical Shift Displacement

Chemical shift displacement (CSD) is well known in MRI: fat and water images are shifted relative to each other in the frequency encoding dimension. In spectroscopy, all three dimensions may use slice selection, so CSD occurs in each.

270

Fundamentals of MR Spectroscopy

The magnitude of CSD (Dx) between two peaks can be calculated from

Phased Array Coils

The trend for clinical 1H-MRS is for signal reception (and transmission) to use arrays of small surface coils. Phased array reception can improve SNR and enable sensitivity encoding to reduce scan times in MRSI; however, it adds further complexity to attempts at quantification. In addition, weighted coherent combination of signal from multiple coils can be difficult in spectra lacking strong landmark peaks.

3.16.4.3

Spurious Echoes

When a voxel is selected by applying RF pulses along three orthogonal axes (Section 3.16.3.2), the desired spin echo in PRESS (or stimulated echo in STEAM) is not the only echo produced. Each pair of pulses produces an echo occurring at a different time. Elimination of these spurious coherences is the purpose of the large ‘crusher’ gradients in PRESS and STEAM (Figure 9). For spins that see all three RF pulses (i.e., those within the cuboid VOI), these gradients balance; for spins that are within the slice selected in 1 or 2 of the planes only, the gradients do not balance and the spins are dephased. The slice order of the three pulses (e.g., sagittal–coronal–axial) should be chosen such that slices that excite more air spaces are played out earlier and therefore are exposed to more of the crusher gradients (Ernst and Chang, 1996).

3.16.4.4

Lipid

[5]

where Do is the separation of their chemical shifts, Vx is the voxel size in that dimension, and BW is the bandwidth of the pulse used for slice selection. CSD worsens for: high field, since the peak separations in hertz increase linearly with field strength; PRESS vs. STEAM, since 180
pulses use lower bandwidths; and larger VOIs, as often selected for MRSI experiments. Spectra in outer rows and columns of the MRSI VOI therefore have abnormal peak ratios and should be discarded. CSD can be reduced by refocusing pulse flip angles <180
, adiabatic pulses (e.g., LASER, Section 3.16.3.2), or spatial saturation pulses to define the voxel (Section 3.16.3.3). In addition, offsetting the transmit frequency to the middle of the spectrum does not change the gross displacement between choline and NAA but does reduce the net displacement of each from the nominal voxel position.

3.16.4.2

NAA

Motion

In MRI, motion is visible as smearing in the phase-encoding dimension or dimensions. In MRSI, all spatial dimensions can employ phase encoding so the signal can be smeared in any direction. For MRSI of the brain, if the signal is visible outside the head, it is a good indication that the patient has moved. In single-voxel experiments, it may be possible to gauge the extent of motion by looking at the variation over time of spectra (Figure 12), particularly in the lipid peaks between

Time

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Cho Cr

4

3

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0

Figure 12 Patient motion can be inferred from variations over time in the size and phase of the lipid peaks 0.9 ppm, while the NAA, creatine, and choline peaks remain stable.

0.5 and 1.6 ppm. It is advisable to perform this check whenever the patient has been observed to move during acquisition, where the lipid peaks themselves are of interest, or in voxels close to regions of physiological motion (e.g., vessels or bowel).

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Relevant Website http://www.cis.rit.edu – The basis of MRI.