Effects of different macromolecular models on reproducibility of FID-MRSI at 7T

High-resolution 1H-MRSI at 9.4 T by integrating relaxation enhancement and subspace imaging

Achieving high-resolution and high signal-to-noise ratio (SNR) in vivo metabolic imaging via fast magnetic resonance spectroscopic imaging (MRSI) has been a longstanding challenge. This study combines the methods of relaxation enhancement (RE) and subspace imaging for the first time, enabling high-resolution and high-SNR in vivo MRSI of rodent brains at 9.4 T. Specifically, an RE-based chemical shift imaging sequence, which combines a frequency-selective pulse to excite only the metabolite frequencies with minimum perturbation of the water spins and a pair of adiabatic pulses to spatially localize the slice of interest, is designed and evaluated in vivo. This strategy effectively shortens the apparent T1 of metabolites, thereby increasing the SNR during relatively short repetition time ((TR) compared with acquisitions with only spatially selective wideband excitations, and does not require water suppression. The SNR was further enhanced via a state-of-the-art subspace reconstruction method. A novel subspace learning strategy tailored for 9.4 T and RE acquisitions is developed. In vivo, high-resolution (e.g., voxel size of 0.6 × 0.6 × 1.5 mm3) MRSI of both healthy mouse brains and a glioma-bearing mouse brain in 12.5 min has been demonstrated.

Macromolecule modelling for improved metabolite quantification using short echo time brain 1 H MRS at 3 T and 7 T: The PRaMM Model

Purpose

To improve reliability of metabolite quantification at both, 3 T and 7 T, we propose a novel parametrized macromolecules quantification model (PRaMM) for brain 1 H MRS, in which the ratios of macromolecule peak intensities are used as soft constraints.

Methods

Full- and metabolite-nulled spectra were acquired in three different brain regions with different ratios of grey and white matter from six healthy volunteers, at both 3 T and 7 T. Metabolite-nulled spectra were used to identify highly correlated macromolecular signal contributions and estimate the ratios of their intensities. These ratios were then used as soft constraints in the proposed PRaMM model for quantification of full spectra. The PRaMM model was validated by comparison with a single component macromolecule model and a macromolecule subtraction technique. Moreover, the influence of the PRaMM model on the repeatability and reproducibility compared to those other methods was investigated.

Results

The developed PRaMM model performed better than the two other approaches in all three investigated brain regions. Several estimates of metabolite concentration and their Cramér-Rao lower bounds were affected by the PRaMM model reproducibility, and repeatability of the achieved concentrations were tested by evaluating the method on a second repeated acquisitions dataset. While the observed effects on both metrics were not significant, the fit quality metrics were improved for the PRaMM method (p≤0.0001). Minimally detectable changes are in the range 0.5 - 1.9 mM and percent coefficients of variations are lower than 10% for almost all the clinically relevant metabolites. Furthermore, potential overparameterization was ruled out.

Conclusion

Here, the PRaMM model, a method for an improved quantification of metabolites was developed, and a method to investigate the role of the MM background and its individual components from a clinical perspective is proposed.

Noninvasive 3-Dimensional 1 H-Magnetic Resonance Spectroscopic Imaging of Human Brain Glucose and Neurotransmitter Metabolism Using Deuterium Labeling at 3T : Feasibility and Interscanner Reproducibility

OBJECTIVES

Noninvasive, affordable, and reliable mapping of brain glucose metabolism is of critical interest for clinical research and routine application as metabolic impairment is linked to numerous pathologies, for example, cancer, dementia, and depression. A novel approach to map glucose metabolism noninvasively in the human brain has been presented recently on ultrahigh-field magnetic resonance (MR) scanners (≥7T) using indirect detection of deuterium-labeled glucose and downstream metabolites such as glutamate, glutamine, and lactate. The aim of this study was to demonstrate the feasibility to noninvasively detect deuterium-labeled downstream glucose metabolites indirectly in the human brain via 3-dimensional (3D) proton ( 1 H) MR spectroscopic imaging on a clinical 3T MR scanner without additional hardware.

MATERIALS AND METHODS

This prospective, institutional review board-approved study was performed in 7 healthy volunteers (mean age, 31 ± 4 years, 5 men/2 women) after obtaining written informed consent. After overnight fasting and oral deuterium-labeled glucose administration, 3D metabolic maps were acquired every ∼4 minutes with ∼0.24 mL isotropic spatial resolution using real-time motion-, shim-, and frequency-corrected echo-less 3D 1 H-MR spectroscopic Imaging on a clinical routine 3T MR system. To test the interscanner reproducibility of the method, subjects were remeasured on a similar 3T MR system. Time courses were analyzed using linear regression and nonparametric statistical tests. Deuterium-labeled glucose and downstream metabolites were detected indirectly via their respective signal decrease in dynamic 1 H MR spectra due to exchange of labeled and unlabeled molecules.

RESULTS

Sixty-five minutes after deuterium-labeled glucose administration, glutamate + glutamine (Glx) signal intensities decreased in gray/white matter (GM/WM) by -1.63 ± 0.3/-1.0 ± 0.3 mM (-13% ± 3%, P = 0.02/-11% ± 3%, P = 0.02), respectively. A moderate to strong negative correlation between Glx and time was observed in GM/WM ( r = -0.64, P < 0.001/ r = -0.54, P < 0.001), with 60% ± 18% ( P = 0.02) steeper slopes in GM versus WM, indicating faster metabolic activity. Other nonlabeled metabolites showed no significant changes. Excellent intrasubject repeatability was observed across scanners for static results at the beginning of the measurement (coefficient of variation 4% ± 4%), whereas differences were observed in individual Glx dynamics, presumably owing to physiological variation of glucose metabolism.

CONCLUSION

Our approach translates deuterium metabolic imaging to widely available clinical routine MR scanners without specialized hardware, offering a safe, affordable, and versatile (other substances than glucose can be labeled) approach for noninvasive imaging of glucose and neurotransmitter metabolism in the human brain.

Test-retest reproducibility of human brain multi-slice 1 H FID-MRSI data at 9.4T after optimization of lipid regularization, macromolecular model, and spline baseline stiffness

PURPOSE

This study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and the reproducibility of respective metabolite ratio to total creatine (/tCr) maps for 10 brain metabolites.

METHODS

Measurements were performed twice on 5 volunteers using a short TR and TE FID MRSI 2D sequence at 9.4T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, Cramér-Rao lower bound, and metabolite ratio maps were investigated. Intra-subject, inter-session coefficient of variation and the test-retest reproducibility of the mean metabolite ratios (/tCr) of each slice was calculated.

RESULTS

Transversal, sagittal, and coronal slices of many metabolite ratio maps correspond to the anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement. L2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected.

CONCLUSION

Reproducible concentration ratio maps (/tCr) for 4 metabolites (total choline, N-acetylaspartate, glutamate, and myoinositol) spanning the majority of the cerebrum and 6 metabolites (N-acetylaspartylglutamate, γ-aminobutyric acid, glutathione, taurine, glutamine, and aspartate) covering 32 mm in the upper part of the brain were acquired at 9.4T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline.

Short symmetric and highly selective asymmetric first and second order gradient modulated offset independent adiabaticity (GOIA) pulses for applications in clinical MRS and MRSI

Gradient modulated RF pulses, especially gradient offset independent adiabaticity (GOIA) pulses, are increasingly gaining attention for high field clinical magnetic resonance spectroscopy and spectroscopic imaging (MRS/MRSI) due to the lower peak B₁ amplitude and associated power demands achievable relative to its non-modulated adiabatic full passage counterparts. In this work we describe the development of two GOIA RF pulses: 1) A power efficient, 3.0 ms wideband uniform rate with smooth truncation (WURST) modulated RF pulse with 15 kHz bandwidth compatible with a clinically feasible peak B₁ amplitude of 0.87 kHz (or 20 µT), and 2) A highly selective asymmetric 6.66 ms RF pulse with 20 kHz bandwidth designed to achieve a single-sided, fractional transition width of only 1.7%. Effects of potential asynchrony between RF and gradient-modulated (GM) waveforms for 3 ms GOIA-WURST RF pulses was evaluated by simulation and experimentally. Results demonstrate that a 20+ µs asynchrony between RF and GM functions substantially degrades inversion performance when using large RF offsets to achieve translation. A projection-based method is presented that allows a quick calibration of RF and GM asynchrony on pre-clinical/clinical MR systems. The asymmetric GOIA pulse was implemented within a multi-pulse OVS sequence to achieve power efficient, highly-selective, and B₁ and T₁-independent signal suppression for extracranial lipid suppression. The developed GOIA pulses were utilized with linear gradient modulation (X, Y, Z gradient fields), and with second-order-field modulations (Z2, X2Y2 gradient fields) to provide elliptically-shaped regions-of-interest for MRS and MRSI acquisitions. Both described GOIA-RF pulses have substantial clinical value; specifically, the 3.0 ms GOIA-WURST pulse is beneficial to realize short TE sLASER localized proton MRS/MRSI sequences, and the asymmetric GOIA RF pulse has applications in highly selective outer volume signal suppression to allow interrogation of tissue proximal to extracranial lipids with full-intensity.

Extensive Brain Pathologic Alterations Detected with 7.0-T MR Spectroscopic Imaging Associated with Disability in Multiple Sclerosis

Background MR spectroscopic imaging (MRSI) allows in vivo assessment of brain metabolism and is of special interest in multiple sclerosis (MS), where morphologic MRI cannot depict major parts of disease activity. Purpose To evaluate the ability of 7.0-T MRSI to depict and visualize pathologic alterations in the normal-appearing white matter (NAWM) and cortical gray matter (CGM) in participants with MS and to investigate their relation to disability. Materials and Methods Free-induction decay MRSI was performed at 7.0 T. Participants with MS and age- and sex-matched healthy controls were recruited prospectively between January 2016 and December 2017. Metabolic ratios were obtained in white matter lesions, NAWM, and CGM regions. Subgroup analysis for MS-related disability based on Expanded Disability Status Scale (EDSS) scores was performed using analysis of covariance. Partial correlations were applied to explore associations between metabolic ratios and disability. Results Sixty-five participants with MS (mean age ± standard deviation, 34 years ± 9; 34 women) and 20 age- and sex-matched healthy controls (mean age, 32 years ± 7; 11 women) were evaluated. Higher signal intensity of myo-inositol (mI) with and without reduced signal intensity of N-acetylaspartate (NAA) was visible on metabolic images in the NAWM of participants with MS. A higher ratio of mI to total creatine (tCr) was observed in the NAWM of the centrum semiovale of all MS subgroups, including participants without disability (marginal mean ± standard error, healthy controls: 0.78 ± 0.04; EDSS 0-1: 0.86 ± 0.03 [P = .02]; EDSS 1.5-3: 0.95 ± 0.04 [P < .001]; EDSS ≥3.5: 0.94 ± 0.04 [P = .001]). A lower ratio of NAA to tCr was found in MS subgroups with disabilities, both in their NAWM (marginal mean ± standard error, healthy controls: 1.46 ± 0.04; EDSS 1.5-3: 1.33 ± 0.03 [P = .03]; EDSS ≥3.5: 1.30 ± 0.04 [P = .01]) and CGM (marginal mean ± standard error, healthy controls: 1.42 ± 0.05; EDSS ≥3.5: 1.23 ± 0.05 [P = .006]). mI/NAA correlated with EDSS (NAWM of centrum semiovale: r = 0.47, P < .001; parietal NAWM: r = 0.43, P = .002; frontal NAWM: r = 0.34, P = .01; frontal CGM: r = 0.37, P = .004). Conclusion MR spectroscopic imaging at 7.0 T allowed in vivo visualization of multiple sclerosis pathologic findings not visible at T1- or T2-weighted MRI. Metabolic abnormalities in the normal-appearing white matter and cortical gray matter were associated with disability. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Barker in this issue.

In vivo macromolecule signals in rat brain 1 H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times

PURPOSE

Reliable detection and fitting of macromolecules (MM) are crucial for accurate quantification of brain short-echo time (TE) ¹ H-MR spectra. An experimentally acquired single MM spectrum is commonly used. Higher spectral resolution at ultra-high field (UHF) led to increased interest in using a parametrized MM spectrum together with flexible spline baselines to address unpredicted spectroscopic components. Herein, we aimed to: (1) implement an advanced methodological approach for post-processing, fitting, and parametrization of 9.4T rat brain MM spectra; (2) assess the concomitant impact of the LCModel baseline and MM model (ie, single vs parametrized); and (3) estimate the apparent T₂ relaxation times for seven MM components.

METHODS

A single inversion recovery sequence combined with advanced AMARES prior knowledge was used to eliminate the metabolite residuals, fit, and parametrize 10 MM components directly from 9.4T rat brain in vivo ¹ H-MR spectra at different TEs. Monte Carlo simulations were also used to assess the concomitant influence of parametrized MM and DKNTMN parameter in LCModel.

RESULTS

A very stiff baseline (DKNTMN ≥ 1 ppm) in combination with a single MM spectrum led to deviations in metabolite concentrations. For some metabolites the parametrized MM showed deviations from the ground truth for all DKNTMN values. Adding prior knowledge on parametrized MM improved MM and metabolite quantification. The apparent T₂ ranged between 12 and 24 ms for seven MM peaks.

CONCLUSION

Moderate flexibility in the spline baseline was required for reliable quantification of real/experimental spectra based on in vivo and Monte Carlo data. Prior knowledge on parametrized MM improved MM and metabolite quantification.

Accelerated MR spectroscopic imaging-a review of current and emerging techniques

Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.

Realistic head-shaped phantom with brain-mimicking metabolites for 7 T spectroscopy and spectroscopic imaging

PURPOSE

Moving to ultra-high fields (≥7 T), the inhomogeneity of both RF (B1 ) and static (B0 ) magnetic fields increases, which further motivates us to design a realistic head-shaped phantom, especially for spectroscopic imaging. Such phantoms provide images similar to the human brain and serve as a reliable tool for developing and examining methods in MRI. This study aims to develop and characterize a realistic head-shaped phantom filled with brain-mimicking metabolites for MRS and magnetic resonance spectroscopic imaging in a 7 T MRI scanner.

METHODS

A 3D head-shaped container with three sections-mimicking brain, muscle and precranial lipid-was constructed. The phantom was designed to provide robustness to heating, mechanical damage and leakage, with easy refilling. The head's shape and the agarose mixture were optimized to provide B0 and B1 distributions and T1 /T2 relaxation values similar to those of human brain. Eight brain-tissue-mimicking metabolites were included for spectroscopy. The phantom was evaluated for localized spectroscopy, fast spectroscopic imaging and fat suppression.

RESULTS

The B0 and B1 maps showed distribution similar to that of human brain, with increased B0 inhomogeneity near the nasal and ear areas and reduced B1 in the temporal lobe and brain stem regions, as expected in vivo. The metabolites' concentrations were verified by single-voxel spectroscopy, showing an average deviation of 11%. Fast spectroscopic imaging and imaging with fat suppression were demonstrated.

CONCLUSION

A 3D head-shaped phantom for human brain imaging and spectroscopic imaging in 7 T MRI was demonstrated, making it a realistic phantom for methodology development at 7 T.

High-resolution metabolic imaging of high-grade gliomas using 7T-CRT-FID-MRSI

OBJECTIVES

Successful neurosurgical intervention in gliomas depends on the precision of the preoperative definition of the tumor and its margins since a safe maximum resection translates into a better patient outcome. Metabolic high-resolution imaging might result in improved presurgical tumor characterization, and thus optimized glioma resection. To this end, we validated the performance of a fast high-resolution whole-brain 3D-magnetic resonance spectroscopic imaging (MRSI) method at 7T in a patient cohort of 23 high-grade gliomas (HGG).

MATERIALS AND METHODS

We preoperatively measured 23 patients with histologically verified HGGs (17 male, 8 female, age 53 ± 15) with an MRSI sequence based on concentric ring trajectories with a 64 × 64 × 39 measurement matrix, and a 3.4 × 3.4 × 3.4 mm3 nominal voxel volume in 15 min. Quantification used a basis-set of 17 components including N-acetyl-aspartate (NAA), total choline (tCho), total creatine (tCr), glutamate (Glu), glutamine (Gln), glycine (Gly) and 2-hydroxyglutarate (2HG). The resultant metabolic images were evaluated for their reliability as well as their quality and compared to spatially segmented tumor regions-of-interest (necrosis, contrast-enhanced, non-contrast enhanced + edema, peritumoral) based on clinical data and also compared to histopathology (e.g., grade, IDH-status).

RESULTS

Eighteen of the patient measurements were considered usable. In these patients, ten metabolites were quantified with acceptable quality. Gln, Gly, and tCho were increased and NAA and tCr decreased in nearly all tumor regions, with other metabolites such as serine, showing mixed trends. Overall, there was a reliable characterization of metabolic tumor areas. We also found heterogeneity in the metabolic images often continued into the peritumoral region. While 2HG could not be satisfyingly quantified, we found an increase of Glu in the contrast-enhancing region of IDH-wildtype HGGs and a decrease of Glu in IDH1-mutant HGGs.

CONCLUSIONS

We successfully demonstrated high-resolution 7T 3D-MRSI in HGG patients, showing metabolic differences between tumor regions and peritumoral tissue for multiple metabolites. Increases of tCho, Gln (related to tumor metabolism), Gly (related to tumor proliferation), as well as decreases in NAA, tCr, and others, corresponded very well to clinical tumor segmentation, but were more heterogeneous and often extended into the peritumoral region.

A novel method to measure T1 -relaxation times of macromolecules and quantification of the macromolecular resonances

PURPOSE

Macromolecular peaks underlying metabolite spectra influence the quantification of metabolites. Therefore, it is important to understand the extent of contribution from macromolecules (MMs) in metabolite quantification. However, to model MMs more accurately in spectral fitting, differences in T₁ relaxation times among individual MM peaks must be considered. Characterization of T₁ -relaxation times for all individual MM peaks using a single inversion recovery technique is difficult due to eventual contributions from metabolites. On the contrary, a double inversion recovery (DIR) technique provided flexibility to acquire MM spectra spanning a range of longitudinal magnetizations with minimal metabolite influence. Thus, a novel method to determine T₁ -relaxation times of individual MM peaks is reported in this work.

METHODS

Extensive Bloch simulations were performed to determine inversion time combinations for a DIR technique that yielded adequate MM signal with varying longitudinal magnetizations while minimizing metabolite contributions. MM spectra were acquired using DIR-metabolite-cycled semi-LASER sequence. LCModel concentrations were fitted to the DIR signal equation to calculate T₁ -relaxation times.

RESULTS

T₁ -relaxation times of MMs range from 204 to 510 ms and 253 to 564 ms in gray- and white-matter rich voxels respectively at 9.4T. Additionally, concentrations of 13 MM peaks are reported.

CONCLUSION

A novel DIR method is reported in this work to calculate T₁ -relaxation times of MMs in the human brain. T₁ -relaxation times and relaxation time corrected concentrations of individual MMs are reported in gray- and white-matter rich voxels for the first time at 9.4T.

Effects of different macromolecular models on reproducibility of FID-MRSI at 7T

PURPOSE

A properly characterized macromolecular (MM) contribution is essential for accurate metabolite quantification in FID-MRSI. MM information can be included into the fitting model as a single component or parameterized and included over several individual MM resonances, which adds flexibility when pathologic changes are present but is prone to potential overfitting. This study investigates the effects of different MM models on MRSI reproducibility.

METHODS

Clinically feasible, high-resolution FID-MRSI data were collected in ~5 min at 7 Tesla from 10 healthy volunteers and quantified via LCModel (version 6.3) with 3 basis sets, each with a different approach for how the MM signal was handled: averaged measured whole spectrum (full MM), 9 parameterized components (param MM) with soft constraints to avoid overparameterization, or without any MM information included in the fitting prior knowledge. The test-retest reproducibility of MRSI scans was assessed voxel-wise using metabolite coefficients of variation and intraclass correlation coefficients and compared between the basis sets. Correlations of concentration estimates were investigated for the param MM fitting model.

RESULTS

The full MM model provided the most reproducible quantification of total NAA, total Cho, myo-inositol, and glutamate + glutamine ratios to total Cr (coefficients of variations ≤ 8%, intraclass correlation coefficients ≥ 0.76). Using the param MM model resulted in slightly lower reproducibility (up to +3% higher coefficients of variations, up to -0.1 decreased intraclass correlation coefficients). The quantification of the parameterized macromolecules did not affect quantification of the overlapping metabolites.

CONCLUSION

Clinically feasible FID-MRSI with an experimentally acquired MM spectrum included in prior knowledge provides highly reproducible quantification for the most common neurometabolites in healthy volunteers. Parameterization of the MM spectrum may be preferred as a compromise between quantification accuracy and reproducibility when the MM content is expected to be pathologically altered.

Intra-session and inter-subject variability of 3D-FID-MRSI using single-echo volumetric EPI navigators at 3T

Purpose

In this study, we demonstrate the first combination of 3D FID proton MRSI and spatial encoding via concentric‐ring trajectories (CRTs) at 3T. FID‐MRSI has many benefits including high detection sensitivity, in particular for J‐coupled metabolites (e.g., glutamate/glutamine). This makes it highly attractive, not only for clinical, but also for, potentially, functional MRSI. However, this requires excellent reliability and temporal stability. We have, therefore, augmented this 3D‐FID‐MRSI sequence with single‐echo, imaging‐based volumetric navigators (se‐vNavs) for real‐time motion/shim‐correction (SHMOCO), which is 2× quicker than the original double‐echo navigators (de‐vNavs), hence allowing more efficient integration also in short‐TR sequences.

Methods

The tracking accuracy (position and B₀‐field) of our proposed se‐vNavs was compared to the original de‐vNavs in phantoms (rest and translation) and in vivo (voluntary head rotation). Finally, the intra‐session stability of a 5:40 min 3D‐FID‐MRSI scan was evaluated with SHMOCO and no correction (NOCO) in 5 resting subjects. Intra/inter‐subject coefficients of variation (CV) and intra‐class correlations (ICC) over the whole 3D volume and in selected regions of interest ROI were assessed.

Results

Phantom and in vivo scans showed highly consistent tracking performance for se‐vNavs compared to the original de‐vNavs, but lower frequency drift. Up to ~30% better intra‐subject CVs were obtained for SHMOCO (P < 0.05), with values of 9.3/6.9/6.5/7.8% over the full VOI for Glx/tNAA/tCho/m‐Ins ratios to tCr. ICCs were good‐to‐high (91% for Glx/tCr in motor cortex), whereas the inter‐subject variability was ~11–19%.

Conclusion

Real‐time motion/shim corrected 3D‐FID‐MRSI with time‐efficient CRT‐sampling at 3T allows reliable, high‐resolution metabolic imaging that is fast enough for clinical use and even, potentially, for functional MRSI.