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Combining CEST and 1H MR Spectroscopy for simultaneous determination of metabolite concentrations and effects of magnetization exchange 
Maike Hoefemann1, André Döring1, and Roland Kreis1
1Departments of Radiology and Biomedical Research, University of Bern, Bern, Switzerland

Synopsis

A new sequence design was used to combine the CEST saturation method with traditional MRS. Using non-water suppressed metabolite-cycled spectroscopy offers the time-saving simultaneous recording of the traditional CEST z-spectrum and the metabolite spectrum under frequency selective saturation and allows the detection of exchange and magnetization transfer effects on metabolites and macromolecules. This technique might offer additional possibilities for quantifying the metabolite and macromolecular content or give further insight into the composition of the traditional CEST z-spectrum and is also relevant for judging the influence of water-suppression on absolute metabolite signals.

Introduction

CEST MRI is by now an established method to investigate metabolites that show magnetization exchange with water, thus complementing traditional spectroscopy for a specific range of metabolites with the benefit of drastically improved sensitivity, but also with the challenge of limited specificity (spectral overlap, other effects on exchange rates) and applicability. Aspects of sequence design and quantification of the components of the z-spectrum have recently been reviewed in detail1–4. Spectroscopy has been combined with CEST previously to correct the z-spectrum for fat signals in extracranial human applications5 and in rat brain6. Specific magnetization transfer (MT) effects from water to metabolites have also been studied in human and animal brain and muscle7–10. However, the acquisition of the complete metabolite spectrum in combination with CEST saturation over the whole spectral range has not been reported for human studies previously, and furthermore the currently proposed method allows for acquisition of MRS and CEST water data in simultaneous fashion.

Methods

Sequence Design:
The basic design of the sequence is shown in Figure 1. A CEST saturation block consisting of a train of Gaussian RF pulses and spoiler gradients is placed before a metabolite-cycled semiLASER spectroscopy localization sequence. The saturation parameters (number of pulses, duty cycle, flip angle, saturation duration) are adjustable to allow optimization of the saturation for a specific target.

Data acquisition:
Data was acquired on 10 healthy volunteers (aged 37±16 years) with the following conditions: 3T MR scanner (Prisma, Siemens, Germany), 64-channel headcoil; supraventricular voxel (45x70x20 mm3); second-order shim (option “brain”); TR 3300 ms; TE 45 ms; 41 measurements with saturation from -6 to 6 ppm (0.3 ppm spacing; one scan at -100 ppm), 24 averages each (60 min acquisition); 2000 ms saturation, duty cycle 80% (see Figure 1), 50 pulses (32 ms each), flip angle 180° (B1 =0.36 µT); additional reference scan without CEST train with 64 averages.

Data evaluation:
Metabolite-cycled data was aligned and eddy-current-corrected in MATLAB and residual water removed using HLSVD. Z-spectra were calculated from the water intensity of each measurement (second point in time domain) and fitted using a 8-pool Lorentzian model, including direct saturation, MT effect, exchange effects from amines, amides, guanidines, hydroxyls, plus two NOE pools (at -1.6 and -3.5 ppm). MT effect was approximated as Lorentzian given the small ppm range investigated. Metabolite spectra fitted in FitAID11 using a model consisting of 18 metabolites and a macromolecular background (MMBG) represented by 64 equally spaced Voigt lines (∆=0.05 ppm, 0.7-4.1 ppm, 5 Hz Gaussian, 9 Hz Lorentzian broadening). Offset, phase, Lorentzian/Gaussian broadening fitted simultaneously for the whole dataset, areas of metabolites and macromolecules (MM) allowed to adapt for each measurement independently in a subsequent step.

Results and Discussion

The effect of the saturation on water and metabolite signals is illustrated in Figure 2. Figure 3 illustrates the water signal intensity used to evaluate the traditional CEST z-spectrum for a representative subject. Fitting of the z-spectrum showed the expected exchange and NOE effects. The MT effect is small‑as expected for a low B1 value. The standard deviations of the fitting results for the cohort reflect good agreement between subjects. No NOE effect at -1.6 ppm (reported for rat brain12) was found in this study.
The magnetization transfer effect from water to metabolites is visualized in Figure 4 for a single subject and the cohort average. The average spectrum also reflects effects on certain parts of the MMBG, especially between 2.0 - 2.8 ppm and 3.4 - 4.1 ppm. Parts of the signal drop might be caused by interfering influence of direct saturation effects close to the water resonance. Furthermore, irradiation at -100 ppm did not have any effect on main metabolites compared to the non-saturated reference scan.
Figure 5 shows the fitted signal intensity of selected metabolites and selected MM regions vs. saturation frequency. Besides the signal drop due to direct saturation, an additional effect is apparent for some metabolites and the MMBG around the water frequency, visualizing the MT effect for single metabolites. For the cholines and largely also for N-acetylaspartate (NAA) this effect is strikingly missing. The simultaneous recording of the water signal and the metabolite spectrum under frequency-selective saturation provides the results from two time-consuming methods at the same time. Using an optimized voxel size13 yields high quality spectra regarding signal-to-noise-ratio even for a few acquisitions only. Recording of spectra under saturation promises further information on exchange factors and MT effects for metabolites and also MM.

Conclusions

Using non-water suppressed spectroscopy offers the time-saving simultaneous recording of the traditional CEST z-spectrum and the metabolite spectrum under frequency-selective saturation. In addition, exchange and MT effects on metabolites and MM can be detected, which might offer additional possibilities for quantifying the metabolite and MM content or give further insight into the composition of the traditional CEST z-spectrum. Effects on MMBG have been found which have previously not been reported. Future research will be directed at investigation of the effect of varying the B1 saturation amplitude. Detailed knowledge of MT effects is also relevant to judge the influence of water-suppression sequences on absolute metabolite signals.

Acknowledgements

This work is supported by the Swiss National Science Foundation (SNSF #320030‐175984).

References

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Figures

Figure 1 – Design of the sequence combining CEST saturation and spectroscopy acquisition: The CEST saturation block is designed as a train of Gaussian pulses with the stated adjustable parameters. It is followed by the metabolite cycling inversion pulses and a semi-LASER localization sequence.

Figure 2 – Impact of the frequency selective CEST saturation on the water and metabolite signal, recorded from the metabolite-cycled semi-LASER sequence and shown for a single subject. The water signal intensity drops significantly for saturation close to its resonance frequency. For the metabolite spectra, the loss in signal intensity is also visible in this view primarily for direct saturation. The ppm values are given in CEST reference (water at 0 ppm) and spectroscopy reference (water at 4.7 ppm).

Figure 3 – Representative fit of a z-spectrum with the multiple pool Lorentzian model. Exchange effects downfield from water are multiplied by a factor of 10 for illustration. Saturation offset is given in CEST convention with water at 0 ppm. Direct water saturation and the broad MT effect define the main shape of the z-spectrum, whilst the exchange effects downfield and the NOE effects upfield describe the smaller drops in signal intensity at specific frequencies. Below the fitting results for all subjects are summarized.

Figure 4 - Comparison of metabolite spectra for M0 and saturation at water frequency for a representative subject (left) and the average of 10 subjects (right). Signal reduction is clearly visible for several metabolites, in particular Creatines, a broad signal at 2 ppm and also Lactate, while for total Choline no changes are apparent. The MM background shows alterations at 0.9 ppm and possibly in the area between 3.4 and 4.1 ppm. The cohort average also reveals downfield effects (potentially ATP at 8.2 and 8.5 ppm). Signal drops close to water are partly caused by direct saturation.

Figure 5 – Above: Intensity of selected metabolites over the saturation frequency range (spectroscopy convention, water at 4.7 ppm), averaged for all subjects with cohort standard deviations indicated. A signal drop for water irradiation is visible for most metabolites, only for total Choline no decrease is detectable. Below: Intensity of selected MM regions for fitting the averaged spectra from all subjects. A negative peak around 4.7 ppm hints at magnetization transfer between MM and water, which has not been reported previously.

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)
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