Proton and phosphorus magnetic resonance spectroscopy of the healthy human breast at 7 T

2.1 Experimental details

A group of eight healthy female volunteers (21–30 years) underwent two MRI scan sessions of the right breast with a dual-tuned ¹H–³¹P quadrature coil (MR Coils BV, Drunen, the Netherlands)21 on a 7-T scanner (Philips Healthcare, Cleveland, OH, USA). Each volunteer was scanned twice on the same day to minimize any effects of hormonal fluctuations/physiological variations on the measurements. The protocol consisted of imaging (scout, fat-suppressed T₁-weighted imaging), a B₀ map used for shimming, ³¹P magnetic resonance spectroscopic imaging (MRSI) and metabolite-cycled ¹H semi-LASER spectroscopy. ¹H spectroscopy was focused on the measurement of the tChol signal and was performed with a water- and fat-suppressed semi-LASER proton sequence15 with metabolite cycling16, 17 of the choline resonance at 3.2 ppm and a voxel of 15 × 15 × 15 mm³ carefully placed in fibroglandular tissue. The semi-LASER sequence was performed with offset independent trapezoid pulses with a duration of 3.92 ms at a maximum γB₁ of 1065 Hz and had a 95% inversion bandwidth of 6 kHz. During the first scan session, a screen print was made of the voxel placement (in three directions) and, during the second scan session, this screen print was used as a map to visually place the voxel at approximately the same position for the second scan session. As water was used as an internal reference for quantification, any variation in fibroglandular tissue content in the voxel would be accounted for and would not lead to different tChol concentrations as long as the tChol concentration is homogeneous over the fibroglandular tissue. Water suppression was performed by a VAPOR scheme13 and fat suppression by a MEGA scheme14 with narrow-band adiabatic full passage (AFP) pulses. Metabolite cycling for tChol was performed by measuring a dynamic series of 2 × 14 scans for each TE (118, 119, 120 and 121 ms) and selectively inverting (with a narrow-band AFP pulse with a frequency sweep of 300 Hz) the signal at 3.2 ppm in the even scans, and subsequently subtracting even from odd scans after phasing the residual water signal, which was a few per cent of the unsuppressed water signal. ¹H spectroscopy was cardiac triggered with a TR of three heart beats for the choline scan (at four different TEs: 118, 119, 120 and 121 ms) and nine heart beats for the water reference scan with TE = 26 ms. The total scan time for the ¹H spectroscopy protocol at an average heart rate of 60 beats/min was 6 min and 12 s.

³¹P MRSI was performed by AMESING26 with the following parameters: TR = 6 s; TE = 45 ms; matrix, 8 × 8 × 8; 4 × 2 × 4 cm³ (RL × AP × FH) voxels; spherical k-space sampling; acquiring one free induction decay (FID) and five full echoes; a bandwidth of 8200 Hz and 256 data points for the echoes. The adiabatic pulses were driven with γB₁ = 1700 Hz, and the pulse durations of the adiabatic half passage (AHP) and BIR-4 refocusing pulses were 2 and 8 ms, respectively. Their respective 95% excitation/refocusing bandwidths were 1400 Hz and 1100 Hz. The total scan time of the ³¹P spectroscopy protocol was 25 min and 36 s. No proton decoupling was applied, as this contributes merely to SAR and not to the signal-to-noise ratio (SNR) in vivo in the breast at 7 T, because of the spectral line widths, which are several times the coupling constants between ¹H and ³¹P. All volunteers gave written informed consent to participate in this study.

2.2 Post-processing of ³¹P MRSI data and ¹H semi-LASER data

³¹P MRSI data were spatially Hanning filtered and subsequently apodized by 10 Hz with a Lorentzian line shape and zero filled to 2048 data points in the time domain. After zero- and first-order phasing, the baselines of the FID spectra were corrected by fitting a second-order spline. All spectral FIDs and echoes were frequency aligned to Pi. The voxel with the highest SNR was chosen for further analysis by maximizing the amount of glandular tissue in the selected voxel by voxel shifting.

¹H spectra at the four different TEs were phased and frequency aligned on the residual water signal, and averaged subsequently. The averaged spectra from the even scans were subtracted from the averaged odd scans in order to obtain the tChol signal.

2.3 Spectral fitting of ³¹P data

The acquired data were analyzed on a group level and on an individual level. Spectral fitting was performed with Lorentzian line shapes in JMRUI31 using the AMARES25 algorithm, employing a priori constraints for the chemical shift difference between PE and PC of 0.5 ppm32 and 0.56 ppm for the chemical shift difference between (diacyl-)glycerophosphatidylethanolamine (GPtE) + GPC and (diacyl-)glycerophosphatidylcholine (GPtC).33 In addition, a 10-Hz additional line width in the FID spectra for the PDEs, relative to Pi and PMEs, was set to compensate for the much shorter T₂ times of the mobile phospholipid PDE signals in the breast.22, 34 Fibroglandular tissue also contains small amounts of adenosine monophosphate (AMP),35 with a chemical shift in between PE and PC at physiological pH.36 The signal of GPE in the breast overlaps partially with the GPtE-MPL (membrane phospholipid) resonance, and concentrations of GPE in the breast are too low to give sufficient signal intensity for quantification. Line widths for PE, PC and Pi were kept free but identical, and line widths for γ-nucleoside triphosphate (γ-NTP) and α-NTP were also kept free but identical. As the spectral resolution in the breast at 7 T is insufficient to distinguish multiplets from J coupling with protons, multiplets were not considered and fitted as single resonances. Spectral fitting with these a priori constraints was used to obtain the values of the line widths and chemical shifts for all metabolites per volunteer.

2.4 Spectral fitting of ¹H data and calculation of tChol concentrations

Spectral fitting was performed with Lorentzian line shapes in JMRUI31 using the AMARES25 algorithm. The frequency of the singlet peak from tChol was constrained between 3.1 and 3.3 ppm and the line width was not constrained. In a second analysis, we verified the influence of constraint of the tChol line width to the line width of the water peak in the sum of even and odd spectra (i.e. the summed spectrum in which tChol should cancel out and residual water and fat peaks should not).

The quantification of tChol was based on a comparison with the reference water scan of the same voxel volume. Longitudinal and transverse relaxation times of water at 7 T were taken from Haddadin et al,9 and were 2.27 s and 36 ms, respectively. For tChol, the T₁ value was taken to be equal to that of water and a T₂ value of 200 ms was assumed (see Discussion).

2.5 T₂ analyses of ³¹P metabolites

Metabolite T₂ values were determined based on the weighted averaged group spectra (one FID and five echoes) of the eight volunteers. Each volunteer was measured twice, and so the group-averaged FID is the Pi-weighted average of 16 FID spectra. Weighted averaging was chosen to maximize SNR of the group spectra. Likewise, the group-averaged echo spectra were also weighted with the Pi intensity of the FID. Weighted averaged spectra were subsequently spectrally fitted for PE, PC, Pi, GPC + GPtE, GPtC, PCr, γ-NTP, α-NTP and NAD in JMRUI31 with the AMARES25 algorithm. Spectral peak areas of all metabolites in the FID and echoes were fitted mono-exponentially as a function of TE. The spectral amplitudes of PE, PC and GPC + GPtE were also fitted bi-exponentially. For the PMEs, it was assumed that, at short TE, the signal shows contributions from nucleoside monophosphate, for which a T₂ similar to that of γ-NTP was chosen. The GPC + GPtE resonance was fitted assuming a T₂ of GPtE similar to GPtC.

2.6 Reproducibility

All volunteers were measured twice on the same day (to minimize physiological influences) and the spectral fitting of these two datasets for each volunteer was used to calculate a standard deviation and a coefficient of variation for each metabolite in all volunteers. The standard deviation of the fitted relative peak area (with respect to the total ³¹P signal) A_m,n of a metabolite m in volunteer n can be written as:

(1)

where is the average of the fitted peak area of metabolite m over the two measurements of volunteer n. Subsequently, the coefficient of variation CoV in the fitted peak area of a metabolite m in volunteer n can be written as:

(2)

Analogously, we can define the average standard deviation and the average coefficient of variation for the peak area of a metabolite m over the whole group of eight volunteers as:

(3)

and

(4)

respectively.

3.1 T₂ analysis of ³¹P metabolites in fibroglandular breast tissue

For ³¹P spectroscopy, the measured line widths are in the range 35–50 Hz (0.3–0.4 ppm). The group-averaged FID and echo spectra (echo spacing, 45 ms) based on the spectra of the eight volunteers are shown in Figure 1. It should be noted that the peak labeled GPtC is no longer visible from Echo 2 onwards, comparable with the rapid disappearance of γ-NTP. The short apparent T₂ of γ-NTP is affected by J modulation because of homonuclear ³¹P coupling.37 In addition, it should be noted that the peak labeled GPC + GPtE loses substantial intensity from FID to the first echo (GPtE has a short T₂), after which the decrease in intensity is much slower, leaving only the slowly decaying GPC signal. The short T₂ PDE signals (GPtC and GPtE) are thought to originate from highly mobile membrane phospholipids.34, 38, 39 In the FID spectrum, there appears to be some signal between the peaks labeled PE and PC that seems to disappear in the echoes; this signal could be nucleoside monophosphate (NMP).35

The β-NTP signal could not be observed above noise level and therefore the spectra are only shown between 10 and −10 ppm. The reason for the apparent absence of the β-NTP signal in the FID spectrum may be two-fold. First, the 95% excitation bandwidth of the AHP pulse is only 1400 Hz and the transmitter offset is approximately 2500 Hz away from the β-NTP resonance. Second, the β-NTP resonance is dependent on the Mg²⁺ concentration, which may be low in healthy breast fibroglandular tissue.

The group-averaged spectra depicted in Figure 1 allow for a pH estimation of fibroglandular tissue based on the chemical shift of Pi. As the small PCr signal most probably originates from voxel bleeding from the pectoralis muscle (which may have a B₀ offset because shimming was aimed at the glandular tissue), it is safer to use the signal from GPC and/or α-NTP as chemical shift reference value and take, for these resonances, chemical shift values that have been measured in vivo, in the presence of PCr, which is by definition 0.0. Here, we adopt for GPC and α-NTP, values of 2.97 ppm and −7.57 ppm, respectively, as measured in mammalian brain.40 For the FID spectrum, we use the α-NTP resonance as it is most clear, whereas the GPC signal in FID is affected by mobile phospholipid; for the echo spectra, we take GPC as chemical shift reference. In this way, we have six measurements (one FID and five echoes) for the chemical shift of Pi which is, on average, 5.31 ± 0.05 ppm, corresponding to a pH value of 7.51 ± 0.07.

Figure 2 shows the T₂ fits for the different ³¹P metabolites. It should be noted that the FID signal amplitudes of PE + NMP, PC + NMP and GPC + GPtC all appear well above the fitted mono-exponential curve. The additional bi-exponential fit for these resonances shows a better agreement with the data. As the T₂ values of the NMP and GPtC components are not known, we assume a similar T₂ for NMP as for the apparent T₂ of γ-NTP that we measured and, likewise, a similar T₂ of GPtC as for the GPtE component that we measured. An overview of the fitted T2 data is shown in Table 1.

The relative metabolite abundances expressed as a percentage of the total ³¹P signal, for this group of volunteers measured twice, as obtained from the data in Figures 1 and 2, are: PE = 8%; AMP = 5%; PC = 4%; Pi =29%; GPE ~ 0%; GPC = 4%; GPtE =10%; GPtC =17%; γ-NTP = 13%; α-NTP = 8%; NADP =2%.

3.2 Reproducibility of ³¹P measurements

The average relative errors (Equation 4) in the amplitudes of the different metabolite signals, derived from spectral fitting of the FID spectra and the T₂-weighted (T2w) average spectra, are shown in Figure 3a,b. Errors on the individual monoester signals are largest because these signals have, on average (see Figure 1), the lowest SNR, overlap partially and are also influenced by the presence of a disturbing signal from NMP. The sum of monoesters, however, shows only small variability. Note the reduction in the relative error and standard deviation of the relative error when making use of T2w spectra, which combine FID and echo spectra, relative to FID spectra, which results in increased SNR and more reliable fitting.

3.3 ¹H spectroscopy

Figure 4 shows an example of the voxel placement for the semi-LASER ¹H MRS in a single volunteer for the duplicate measurements. The line width of water in the small ¹H MRS voxel is in the range 20–50 Hz (0.07–0.17 ppm). The tChol concentrations, determined in duplicate, for a voxel of fibroglandular tissue of the eight volunteers are shown in Table 2. In the case of volunteers 3 and 5, one of the two determinations gave insufficient signal to determine a tChol concentration. Spectral fitting was performed with an unconstrained line width for tChol and also with a fixed line width for tChol, equal to the line width of the water signal, whilst adding the (frequency aligned) odd and even scans (i.e. tChol cancels out and residual water and fat peaks do not). The group-averaged tChol concentration of the data analyzed with a free line width for tChol, as well as with a fixed line width, from Table 2 is 0.54 mM (or, more precisely, mmol/kg_water). Correcting for the water content of fibroglandular tissue being approximately 60%,41 this would reduce to 0.32 mM.

The calculated tChol concentration depends on the T₁ and T₂ values that were assumed for tChol. As these values are not known in the breast at 7 T, they had to be estimated. For the T₁ of tChol, we assumed a value similar to the T₁ of water (2.27 s) at 7 T, as tabulated by Haddadin et al.9 For the T₂ of tChol, we assumed a value of 200 ms. Reported T₂ values of tChol in the breast at 1.5 T range between 181 and 360 ms, whereas, at 4 T, a value of 399 ± 133 ms was measured, as reviewed by Haddadin et al.9 A value of 178 ± 28 ms for tChol was measured at 9.4 T in rat brain.42 Therefore, a value in the range 150–250 ms for T₂ of tChol at 7 T seems plausible. A value of T₂ = 150 ms for tChol would lead to approximately 30% higher tChol concentrations than at T₂ = 200 ms, and a value of 250 ms would lead to approximately 20% lower concentrations than reported here.

The relative error in the ¹H tChol determination, calculated analogously to the ³¹P data (Equation 4), as shown in Figure 3c, is 34% for the spectral fitting with free line width and 26% for the spectral fitting with fixed line width for tChol.

The interpretation of the relative errors depicted in Figure 3 should also take into consideration the difference in voxel sizes used for ³¹P and ¹H spectroscopy. Here, we used 4 × 2 × 4 cm³ (nominal resolution) voxels for ³¹P MRSI of healthy glandular tissue, whereas, in a clinical setting with breast cancer patients, we would use smaller voxels of 2 × 2 × 2 cm³. Considering the acquisition-weighted k-space sampling and the applied Hanning filter in the MRSI sequence, the true voxel size in our study is even larger: an ellipsoid of approximately 82 cm³. In a worst case, this would mean an increase in the coefficient of variation for ³¹P spectroscopy of a factor of four on using the 2 × 2 × 2 cm³ nominal voxel size. As the larger voxel size does not imply that these voxels are completely filled with glandular tissue, they may contain fatty tissue (without ³¹P signal) as well, such that the factor of four in the coefficient of variation is the limiting case.

Although the intrinsic sensitivity of ³¹P MRS remains less than that of ¹H MRS, the absence of disturbing signals from lipids and water and the insensitivity of the AMESING sequence to B₀ inhomogeneities provide substantial advantages of ³¹P MRS over ¹H MRS in the robust detection of phospholipid metabolites. With the larger voxel sizes, longer scan times and absence of artifacts, ³¹P MRS could detect the phospholipid metabolite signals with an order of magnitude improved coefficient of variation (Figure 3) than with ¹H MRS.

Figure 5 shows an example of ³¹P MR spectra and metabolite cycled ¹H MR tChol spectra for volunteer 2 measured in duplicate. Although the noise level is expected to be the same in all ³¹P acquisitions, the noise pattern of the ³¹P spectrum in the top right of Figure 5 seems to include a higher spectral noise density than in the remaining spectra. This may be caused by truncation artifacts as a result of the relatively short acquisition window of 16 ms of FID acquisition, which affects the spectral region most strongly around sharp and high-intensity peaks.

Estimates of the average PME and PDE concentrations in healthy fibroglandular tissue based on a combination of ³¹P and ¹H MRS, using the ³¹P data shown in Figures 1 and 2, and the average tChol value of Table 1 of 0.54 mM, are PE = 0.4 mM (two protons), PC = 0.2 mM (nine protons) and GPC = 0.2 mM (nine protons), where it was assumed that the free choline concentration can be neglected. The estimated concentrations of PMEs and PDEs are therefore an upper limit. Correction for 60% water content of fibroglandular tissue39 would lead to approximate values, expressed in mmol/kg of tissue (assuming a tissue density of approximately 1 kg/L), which are 60% of the values expressed in mM. An assessment by liquid chromatography-mass spectrometry of three samples of healthy breast tissue by Mimmi et al43 led to values for PC in the range 0.03–0.21 mmol/kg; this corresponds well with our value for PC expressed in the same units (mmol/kg of tissue) of 0.1 mmol/kg_tissue.

This study shows the feasibility of combining ³¹P MRSI with localized ¹H MRS in vivo in the breast at 7 T. The combination of these techniques may be of value in monitoring the response to chemotherapy in breast cancer patients, where it may possibly better discriminate between responders and non-responders than ³¹P or ¹H MRS alone. From ex vivo analysis43, 44 of breast cancer samples, it is known that the free choline concentrations are small, compared with PC; therefore, combined ³¹P and ¹H MRS in vivo in breast cancer will enable, to a good approximation, absolute concentration measurements of key metabolites of cell membrane metabolism.