Diffusion-weighted MR spectroscopy: Consensus, recommendations, and resources from acquisition to modeling.

Brain cell structure and function reflect neurodevelopment, plasticity, and aging; and changes can help flag pathological processes such as neurodegeneration and neuroinflammation. Accurate and quantitative methods to noninvasively disentangle cellular structural features are needed and are a substantial focus of brain research. Diffusion-weighted MRS (dMRS) gives access to diffusion properties of endogenous intracellular brain metabolites that are preferentially located inside specific brain cell populations. Despite its great potential, dMRS remains a challenging technique on all levels: from the data acquisition to the analysis, quantification, modeling, and interpretation of results. These challenges were the motivation behind the organization of the Lorentz Center workshop on "Best Practices & Tools for Diffusion MR Spectroscopy" held in Leiden, the Netherlands, in September 2021. During the workshop, the dMRS community established a set of recommendations to execute robust dMRS studies. This paper provides a description of the steps needed for acquiring, processing, fitting, and modeling dMRS data, and provides links to useful resources.

Maximizing SNR per unit time in diffusion MRI with multiband T-Hex spirals.

PURPOSE: The characterization of tissue microstructure using diffusion MRI (dMRI) signals is rapidly evolving, with increasing sophistication of signal representations and microstructure models. However, this progress often requires signals to be acquired with very high b-values (e.g., b > 30 ms/µm2 ), along many directions, and using multiple b-values, leading to long scan times and extremely low SNR in dMRI images. The purpose of this work is to boost the SNR efficiency of dMRI by combining three particularly efficient spatial encoding techniques and utilizing a high-performance gradient system (Gmax ≤ 300 mT/m) for efficient diffusion encoding. METHODS: Spiral readouts, multiband imaging, and sampling on tilted hexagonal grids (T-Hex) are combined and implemented on a 3T MRI system with ultra-strong gradients. Image reconstruction is performed through an iterative cg-SENSE algorithm incorporating static off-resonance distributions and field dynamics as measured with an NMR field camera. Additionally, T-Hex multiband is combined with a more conventional EPI-readout and compared with state-of-the-art blipped-CAIPIRINHA sampling. The advantage of the proposed approach is furthermore investigated for clinically available gradient performance and diffusion kurtosis imaging. RESULTS: High fidelity in vivo images with b-values up to 40 ms/µm2 are obtained. The approach provides superior SNR efficiency over other state-of-the-art multiband diffusion readout schemes. CONCLUSION: The demonstrated gains hold promise for the widespread dissemination of advanced microstructural scans, especially in clinical populations.

Practical considerations of diffusion-weighted MRS with ultra-strong diffusion gradients.

Introduction: Diffusion-weighted magnetic resonance spectroscopy (DW-MRS) offers improved cellular specificity to microstructure-compared to water-based methods alone-but spatial resolution and SNR is severely reduced and slow-diffusing metabolites necessitate higher b-values to accurately characterize their diffusion properties. Ultra-strong gradients allow access to higher b-values per-unit time, higher SNR for a given b-value, and shorter diffusion times, but introduce additional challenges such as eddy-current artefacts, gradient non-uniformity, and mechanical vibrations. Methods: In this work, we present initial DW-MRS data acquired on a 3T Siemens Connectom scanner equipped with ultra-strong (300 mT/m) gradients. We explore the practical issues associated with this manner of acquisition, the steps that may be taken to mitigate their impact on the data, and the potential benefits of ultra-strong gradients for DW-MRS. An in-house DW-PRESS sequence and data processing pipeline were developed to mitigate the impact of these confounds. The interaction of TE, b-value, and maximum gradient amplitude was investigated using simulations and pilot data, whereby maximum gradient amplitude was restricted. Furthermore, two DW-MRS voxels in grey and white matter were acquired using ultra-strong gradients and high b-values. Results: Simulations suggest T2-based SNR gains that are experimentally confirmed. Ultra-strong gradient acquisitions exhibit similar artefact profiles to those of lower gradient amplitude, suggesting adequate performance of artefact mitigation strategies. Gradient field non-uniformity influenced ADC estimates by up to 4% when left uncorrected. ADC and Kurtosis estimates for tNAA, tCho, and tCr align with previously published literature. Discussion: In conclusion, we successfully implemented acquisition and data processing strategies for ultra-strong gradient DW-MRS and results indicate that confounding effects of the strong gradient system can be ameliorated, while achieving shorter diffusion times and improved metabolite SNR.

Macromolecular background signal and non-Gaussian metabolite diffusion determined in human brain using ultra-high diffusion weighting.

PURPOSE: Definition of a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterization of non-Gaussian diffusion of brain metabolites with strongly diffusion-weighted MR spectroscopy. METHODS: Short echo time MRS with strong diffusion-weighting with b-values up to 25 ms/µm2 at two diffusion times was implemented on a Connectom system and applied in combination with simultaneous spectral and diffusion decay modeling. Motion-compensation was performed with a combined method based on the simultaneously acquired water and a macromolecular signal. RESULTS: The motion compensation scheme prevented spurious signal decay reflected in very small apparent diffusion constants for macromolecular signal. Macromolecular background signal patterns were determined using multiple fit strategies. Signal decay corresponding to non-Gaussian metabolite diffusion was represented by biexponential fit models yielding parameter estimates for human gray matter that are in line with published rodent data. The optimal fit strategies used constraints for the signal decay of metabolites with limited signal contributions to the overall spectrum. CONCLUSION: The determined macromolecular spectrum based on diffusion properties deviates from the conventional one derived from longitudinal relaxation time differences calling for further investigation before use as experimental basis spectrum when fitting clinical MR spectra. The biexponential characterization of metabolite signal decay is the basis for investigations into pathologic alterations of microstructure.

Quantification of NAD+ in human brain with 1 H MR spectroscopy at 3 T: Comparison of three localization techniques with different handling of water magnetization.

PURPOSE: The detection of nicotinamide-adenine-dinucleotide (NAD+ ) is challenging using standard 1 H MR spectroscopy, because it is of low concentration and affected by polarization-exchange with water. Therefore, this study compares three techniques to access NAD+ quantification at 3 T-one with and two without water presaturation. METHODS: A large brain volume in 10 healthy subjects was investigated with three techniques: semi-LASER with water-saturation (WS) (TE = 35 ms), semi-LASER with metabolite-cycling (MC) (TE = 35 ms), and the non-water-excitation (nWE) technique 2D ISIS-localization with chemical-shift-selective excitation (2D I-CSE) (TE = 10.2 ms). Spectra were quantified with optimized modeling in FiTAID. RESULTS: NAD+ could be well quantified in cohort-average spectra with all techniques. Obtained apparent NAD+ tissue contents are all lower than expected from literature confirming restricted visibility by 1 H MRS. The estimated value from WS-MRS (58 µM) was considerably lower than those obtained with non-WS techniques (146 µM for MC-semi-LASER and 125 µM for 2D I-CSE). The nWE technique with shortest TE gave largest NAD+ signals but suffered from overlap with large amide signals. MC-semi-LASER yielded best estimation precision as reflected in relative Cramer-Rao bounds (14%, 21 µM/146 µM) and also best robustness as judged by the coefficient-of-variance over the cohort (11%, 10 µM/146 µM). The MR-visibility turned out as 16% with WS and 41% with MC. CONCLUSION: Three methods to assess NAD+ in human brain at 3 T have been compared. NAD+ could be detected with a visibility of ∼41% for the MC method. This may open a new window for the observation of pathological changes in the clinical research setting.

Combining chemical exchange saturation transfer and 1 H magnetic resonance spectroscopy for simultaneous determination of metabolite concentrations and effects of magnetization exchange.

PURPOSE: A new sequence combining chemical-exchange saturation-transfer (CEST) with traditional MRS is used to simultaneously determine metabolite content and effects of magnetization exchange. METHODS: A CEST saturation block consisting of a train of RF-pulses is placed before a metabolite-cycled semi-LASER single-voxel spectroscopy sequence. The saturation parameters are adjustable to allow optimization of the saturation for a specific target. Data were collected in brain from 20 subjects in experiments with different B1 -settings (0.4-2.0 µT) on a 3T MR scanner. CEST Z-spectra were calculated from water intensities and fitted with a multi-pool Lorentzian model. Interrelated metabolite spectra were fitted in fitting tool for arrays of interrelated datasets (FiTAID). RESULTS: Evaluation of traditional Z-spectra from water revealed exchange effects from amides, amines, and hydroxyls as well as an upfield nuclear Overhauser effect. The magnetization transfer effect was evaluated on metabolites and macromolecules for the whole spectral range and for the different B1 levels. A correction scheme for direct saturation on metabolites is proposed. Both magnetization-transfer and direct saturation proved to differ for individual metabolites. CONCLUSION: Using non-water-suppressed spectroscopy offers time-saving simultaneous recording of the traditional CEST Z-spectrum from water and the metabolite spectrum under frequency-selective saturation. In addition, exchange and magnetization-transfer effects on metabolites and macromolecules can be detected, which might offer additional possibilities for quantification or give further insight into the composition of the traditional CEST Z-spectrum. Apparent magnetization-transfer effects on macromolecular signals in the 1 H-MR spectrum have been found. Detailed knowledge of magnetization-transfer effects is also relevant for judging the influence of water-suppression on the quantification of metabolite signals.

Magnetic resonance spectroscopy extended by oscillating diffusion gradients: Cell-specific anomalous diffusion as a probe for tissue microstructure in human brain.

PURPOSE: To demonstrate that oscillating gradient spin-echo sequences can be combined with diffusion-weighted magnetic resonance spectroscopy even on clinical MR systems to study human brain at short diffusion times to provide apparent diffusion coefficients (ADCs) sensitive to a narrower cellular length scale than pulsed gradient spin-echo sequences at long diffusion time. METHODS: Measurements were performed on a 3T MR system using a semiLaser sequence with diffusion-weighting realized by oscillating and pulsed gradient modules, encoding diffusion times <10 ms and >50 ms, respectively. Metabolite-cycling was included to measure metabolites and water simultaneously. The sequence was tested in a phantom and in a parieto-occipital cerebral region of interest with mixed gray/white matter content of 6 subjects. The water reference was used for phase, frequency, and eddy-current correction as well as motion compensation. ADCs were estimated by 1D sequential and 2D simultaneous fitting. RESULTS: Measurements in the phantom established that both sequences yield equal ADCs, independent of diffusion time, as expected for free diffusion. In contrast, averaged metabolite diffusion in vivo was found to be 1.9 times faster at short (8.3 ms) than at long (155 ms) diffusion times. The difference in ADC was found to be statistically significant for the creatines, cholines, N-acetylaspartate, myo-inositol, and glutamate. The water ADC was measured to be 1.3 times larger at short than at long diffusion time. CONCLUSION: It is demonstrated that application of oscillating gradients in diffusion-weighted MRS is feasible on clinical MR systems to establish the dependence of ADCs on diffusion times in humans. The initial results largely confirm earlier reports for mice' and rats' brain at short and long diffusion times. ADCs representing diffusion at short and ultra-short diffusion times are of interest to probe cellular or subcellular changes in disease. The presented methodology may thus open the door for investigation of pathophysiological changes in cell-specific microstructures in human cohorts.

Diffusion-weighted magnetic resonance spectroscopy boosted by simultaneously acquired water reference signals.

PURPOSE: To combine the metabolite-cycling technique with diffusion-weighted 1 H-MR spectroscopy and to use the inherent water reference for compensation of motion-related signal loss for improved estimation of metabolite apparent diffusion coefficients (ADCs). METHODS: Diffusion-weighted spectra of water and metabolites were acquired simultaneously using metabolite-cycling at 3 T. The water information was used for signal correction of phase, frequency, and eddy currents, as well as for compensation of motion-induced signal loss. ADCs were estimated by 2D simultaneous fitting. The quality of ADC restoration was investigated in vitro. Subsequently, the new approach was applied in 13 subjects for enhanced metabolite ADC estimation in gray matter. RESULTS: Metabolite-cycled diffusion 1 H-MRS is suitable to measure metabolite and water ADCs simultaneously. The water reference facilitates signal amplitude restoration, compensating for motion-related artefacts. 2D fitting stabilizes the fitting procedure and allows the estimation of ADCs even for low signal-to-noise metabolites. Use of the motion-compensation scheme leads to estimation of smaller ADCs for virtually all metabolites (44% smaller ADC on average), to a reduction of fitting uncertainties for metabolite ADCs in individual subjects and reduced variance over the cohort (45% smaller SD on average). CONCLUSION: Using the simultaneously acquired water signal as internal reference allows not only for compensation of phase and frequency fluctuations but also for signal amplitude restoration, and thus improved metabolite ADC estimation. Combination with 2D simultaneous fitting promises access to the diffusion properties even for low signal-to-noise metabolites. The combination of both techniques increases the specificity and sensitivity of estimated metabolite ADC values in the cohort.

Fitting interrelated datasets: metabolite diffusion and general lineshapes.

OBJECTIVE: Simultaneous modeling of true 2-D spectroscopy data, or more generally, interrelated spectral datasets has been described previously and is useful for quantitative magnetic resonance spectroscopy applications. In this study, a combined method of reference-lineshape enhanced model fitting and two-dimensional prior-knowledge fitting for the case of diffusion weighted MR spectroscopy is presented. MATERIALS AND METHODS: Time-dependent field distortions determined from a water reference are applied to the spectral bases used in linear-combination modeling of interrelated spectra. This was implemented together with a simultaneous spectral and diffusion model fitting in the previously described Fitting Tool for Arrays of Interrelated Datasets (FiTAID), where prior knowledge conditions and restraints can be enforced in two dimensions. RESULTS: The benefit in terms of increased accuracy and precision of parameters is illustrated with examples from Monte Carlo simulations, in vitro and in vivo human brain scans for one- and two-dimensional datasets from 2-D separation, inversion recovery and diffusion-weighted spectroscopy (DWS). For DWS, it was found that acquisitions could be substantially shortened. CONCLUSION: It is shown that inclusion of a measured lineshape into modeling of interrelated MR spectra is beneficial and can be combined also with simultaneous spectral and diffusion modeling.