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Bernhard Strasser

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13 papers

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YNIMG Journal 2025 Journal Article

A deep autoencoder for fast spectral–temporal fitting of dynamic deuterium metabolic imaging data at 7T

Aaron Paul Osburg
Amirmohammad Shamaei
Bernhard Strasser
Fabian Niess
Anna Duguid
Viola Bader
Sabina Frese
Lukas Hingerl

Deuterium metabolic imaging (DMI) is a non-invasive magnetic resonance spectroscopic imaging technique enabling in vivo mapping of glucose metabolism. Dynamic DMI provides time-resolved metabolite maps and allows spatially resolved fitting of metabolic models to capture metabolite concentration dynamics. However, conventional fitting tools often require long processing times for high-resolution datasets, limiting their practical utility. To address this bottleneck, we propose a deep autoencoder (DAE) for rapid spectral-temporal fitting of dynamic DMI data, supporting arbitrary parametric model constraints to describe metabolite concentration dynamics. The DAE was benchmarked against spectral-temporal fitting using FSL-MRS and LCModel. Fitting accuracy was evaluated on in vivo and synthetic whole-brain dynamic DMI data acquired at 7T using Bland-Altman metrics, Pearson correlation coefficients, structural similarity index measures, and root mean squared errors for both metabolite concentrations and model constraint parameters. The DAE achieved processing times of 0.29 ms per voxel, corresponding to an acceleration of more than three orders of magnitude compared to LCModel/FSL-MRS (0.55/0.65 s per voxel). On in vivo data, it showed excellent agreement with LCModel, and on synthetic data, it consistently outperformed both reference methods across all evaluation metrics. The proposed DAE enables accurate spectral-temporal fitting for whole-brain dynamic DMI scans within less than a second, matching or exceeding the performance of conventional state-of-the-art fitting methods. This makes it a promising tool for integration into efficient post-processing pipelines for research and clinical DMI workflows.

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YNIMG Journal 2025 Journal Article

Deep-ER: Deep Learning ECCENTRIC Reconstruction for fast high-resolution neurometabolic imaging

Paul J. Weiser
Georg Langs
Wolfgang Bogner
Stanislav Motyka
Bernhard Strasser
Polina Golland
Nalini Singh
Jorg Dietrich

INTRODUCTION: Altered neurometabolism is an important pathological mechanism in many neurological diseases and brain cancer, which can be mapped non-invasively by Magnetic Resonance Spectroscopic Imaging (MRSI). Advanced MRSI using non-cartesian compressed-sense acquisition enables fast high-resolution metabolic imaging but has lengthy reconstruction times that limits throughput and needs expert user interaction. Here, we present a robust and efficient Deep Learning reconstruction embedded in a physical model within an end-to-end automated processing pipeline to obtain high-quality metabolic maps. METHODS: isotropic resolution with acquisition times between 4:11-9:21 min:s using ECCENTRIC pulse sequence on a 7T MRI scanner. Data were acquired in a high-resolution phantom and 27 human participants, including 22 healthy volunteers and 5 glioma patients. A deep neural network using recurring interlaced convolutional layers with joint dual-space feature representation was developed for deep learning ECCENTRIC reconstruction (Deep-ER). 21 subjects were used for training and 6 subjects for testing. Deep-ER performance was compared to iterative compressed sensing Total Generalized Variation reconstruction using image and spectral quality metrics. RESULTS: Deep-ER demonstrated 600-fold faster reconstruction than conventional methods, providing improved spatial-spectral quality and metabolite quantification with 12%-45% (P<0.05) higher signal-to-noise and 8%-50% (P<0.05) smaller Cramer-Rao lower bounds. Metabolic images clearly visualize glioma tumor heterogeneity and boundary. Deep-ER generalizes reliably to unseen data. CONCLUSION: Deep-ER provides efficient and robust reconstruction for sparse-sampled MRSI. The accelerated acquisition-reconstruction MRSI is compatible with high-throughput imaging workflow. It is expected that such improved performance will facilitate basic and clinical MRSI applications for neuroscience and precision medicine.

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YNIMG Journal 2025 Journal Article

Exploring in vivo human brain metabolism at 10.5 T: Initial insights from MR spectroscopic imaging

Lukas Hingerl
Bernhard Strasser
Simon Schmidt
Korbinian Eckstein
Guglielmo Genovese
Edward J. Auerbach
Andrea Grant
Matt Waks

INTRODUCTION: Ultra-high-field magnetic resonance (MR) systems (7 T and 9.4 T) offer the ability to probe human brain metabolism with enhanced precision. Here, we present the preliminary findings from 3D MR spectroscopic imaging (MRSI) of the human brain conducted with the world's first 10.5 T whole-body MR system. METHODS: -weighted MRI were obtained. RESULTS: = 65 ± 11° within the MRSI volume of interest. DISCUSSION: These preliminary findings highlight the potential of 10.5 T MRSI as a powerful imaging tool for probing cerebral metabolism. By providing unprecedented spatial and spectral resolution, this technology could offer a unique view into the metabolic intricacies of the human brain, but further technical developments will be necessary to optimize data quality and fully leverage the capabilities of 10.5 T MRSI.

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YNIMG Journal 2025 Journal Article

Topographical mapping of metabolic abnormalities in multiple sclerosis using rapid echo-less 3D-MR spectroscopic imaging at 7T

Eva Niess
Assunta Dal-Bianco
Bernhard Strasser
Fabian Niess
Lukas Hingerl
Beata Bachrata
Stanislav Motyka
Paulus Rommer

OBJECTIVES: To assess topographical patterns of metabolic abnormalities in the cerebrum of multiple sclerosis (MS) patients and their relationship to clinical disability using rapid echo-less 3D-MR spectroscopic imaging (MRSI) at 7T. MATERIALS AND METHODS: This study included 26 MS patients (13 women; median age 34) and 13 age- and sex-matched healthy controls (7 women; median age 33). Metabolic maps were obtained using echo-less 3D-MRSI at 7T with a 64 × 64 × 33 matrix and a nominal voxel size of 3.4 × 3.4 × 4 mm³ in an 8-minute scan. After spatial normalization, voxel-wise comparisons between MS and controls were conducted to identify clusters of metabolic abnormalities, while correlations with clinical disability were analyzed using Expanded Disability Status Scale (EDSS) scores. RESULTS: Statistical mapping (FWE-corrected; P<.05) revealed elevated myo-inositol to total creatine (mI/tCr) ratios in the bilateral periventricular white matter and reduced N-acetylaspartate to total creatine (NAA/tCr) within and beyond lesions, notably near the lateral ventricles, cingulate gyrus, and superior frontal gyrus. Patients with sustained disability (EDSS≥2) showed additional reductions in the posterior parietal lobe. A strong negative association was found between NAA/tCr and EDSS in the precentral gyrus (Spearman's rank ρ=-0.58, P=.005), and a moderate positive association between mI/NAA and EDSS in the precentral and superior frontal gyri (ρ=0.47, P=.015). CONCLUSIONS: This study highlights the ability of 3D-MRSI at 7T to map widespread metabolic abnormalities in MS, with NAA reductions in prefrontal, motor, and sensory areas, linked to neuroaxonal damage and disability progression, and elevated mI in periventricular regions, reflecting gliosis.

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YNICL Journal 2023 Journal Article

Metabolic Insights into Iron Deposition in Relapsing-Remitting Multiple Sclerosis via 7 T Magnetic Resonance Spectroscopic Imaging

Alexandra Lipka
Wolfgang Bogner
Assunta Dal-Bianco
Gilbert J. Hangel
Paulus S. Rommer
Bernhard Strasser
Stanislav Motyka
Lukas Hingerl

OBJECTIVE: To investigate the metabolic pattern of different types of iron accumulation in multiple sclerosis (MS) lesions, and compare metabolic alterations within and at the periphery of lesions and newly emerging lesions in vivo according to iron deposition. METHODS: 7 T MR spectroscopic imaging and susceptibility-weighted imaging was performed in 31 patients with relapsing-remitting MS (16 female/15 male; mean age, 36.9 ± 10.3 years). Mean metabolic ratios of four neuro-metabolites were calculated for regions of interest (ROI) of normal appearing white matter (NAWM), "non-iron" (lesion without iron accumulation on SWI), and three distinct types of iron-laden lesions ("rim": distinct rim-shaped iron accumulation; "area": iron deposition across the entire lesions; "transition": transition between "area" and "rim" accumulation shape), and for lesion layers of "non-iron" and "rim" lesions. Furthermore, newly emerging "non-iron" and "iron" lesions were compared longitudinally, as measured before their appearance and one year later. RESULTS: Thirty-nine of 75 iron-containing lesions showed no distinct paramagnetic rim. Of these, "area" lesions exhibited a 65% higher mIns/tNAA (p = 0.035) than "rim" lesions. Comparing lesion layers of both "non-iron" and "rim" lesions, a steeper metabolic gradient of mIns/tNAA ("non-iron" +15%, "rim" +40%) and tNAA/tCr ("non-iron" -15%, "rim" -35%) was found in "iron" lesions, with the lesion core showing +22% higher mIns/tNAA (p = 0.005) and -23% lower tNAA/tCr (p = 0.048) in "iron" compared to "non-iron" lesions. In newly emerging lesions, 18 of 39 showed iron accumulation, with the drop in tNAA/tCr after lesion formation remaining significantly lower compared to pre-lesional tissue over time in "iron" lesions (year 0: p = 0.013, year 1: p = 0.041) as opposed to "non-iron" lesions (year 0: p = 0.022, year 1: p = 0.231). CONCLUSION: 7 T MRSI allows in vivo characterization of different iron accumulation types each presenting with a distinct metabolic profile. Furthermore, the larger extent of neuronal damage in lesions with a distinct iron rim was reconfirmed via reduced tNAA/tCr concentrations, but with metabolic differences in lesion development between (non)-iron-containing lesions. This highlights the ability of MRSI to further investigate different types of iron accumulation and suggests possible implications for disease monitoring.

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YNIMG Journal 2023 Journal Article

Reproducibility of 3D MRSI for imaging human brain glucose metabolism using direct (2H) and indirect (1H) detection of deuterium labeled compounds at 7T and clinical 3T

Fabian Niess
Bernhard Strasser
Lukas Hingerl
Eva Niess
Stanislav Motyka
Gilbert Hangel
Martin Krššák
Stephan Gruber

INTRODUCTION: H MRSI (QELT), respectively. The purpose of this study was to compare the dynamics of spatially resolved brain glucose metabolism, i.e., estimated concentration enrichment of deuterium labeled Glx (glutamate+glutamine) and Glc (glucose) acquired repeatedly in the same cohort of subjects using DMI at 7T and QELT at clinical 3T. METHODS: H FID-MRSI with a non-Cartesian concentric ring trajectory readout at clinical 3T. RESULTS: data GM (r=-0.61, p<0.001) and WM (r=-0.70, p<0.001). CONCLUSION: H DMI data acquired at 7T. This suggests significant potential for widespread application in clinical settings especially in environments with limited access to ultra-high field scanners and dedicated RF hardware.

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YNICL Journal 2020 Journal Article

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

Gilbert Hangel
Cornelius Cadrien
Philipp Lazen
Julia Furtner
Alexandra Lipka
Eva Hečková
Lukas Hingerl
Stanislav Motyka

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: 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.

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YNIMG Journal 2019 Journal Article

High-resolution metabolic mapping of gliomas via patch-based super-resolution magnetic resonance spectroscopic imaging at 7T

Gilbert Hangel
Saurabh Jain
Elisabeth Springer
Eva Hečková
Bernhard Strasser
Michal Považan
Stephan Gruber
Georg Widhalm

Objectives To demonstrate the feasibility of 7 T magnetic resonance spectroscopic imaging (MRSI), combined with patch-based super-resolution (PBSR) reconstruction, for high-resolution multi-metabolite mapping of gliomas. Materials and methods Ten patients with WHO grade II, III and IV gliomas (6/4, male/female; 45 ± 9 years old) were prospectively measured between 2014 and 2018 on a 7 T whole-body MR imager after routine 3 T magnetic resonance imaging (MRI) and positron emission tomography (PET). Free induction decay MRSI with a 64 × 64-matrix and a nominal voxel size of 3. 4 × 3. 4 × 8 mm³ was acquired in six minutes, along with standard T1/T2-weighted MRI. Metabolic maps were obtained via spectral LCmodel processing and reconstructed to 0. 9 × 0. 9 × 8 mm³ resolutions via PBSR. Results Metabolite maps obtained from combined 7 T MRSI and PBSR resolved the density of metabolic activity in the gliomas in unprecedented detail. Particularly in the more heterogeneous cases (e. g. post resection), metabolite maps enabled the identification of complex metabolic activities, which were in topographic agreement with PET enhancement. Conclusions PBSR-MRSI combines the benefits of ultra-high-field MR systems, cutting-edge MRSI, and advanced postprocessing to allow millimetric resolution molecular imaging of glioma tissue beyond standard methods. An ideal example is the accurate imaging of glutamine, which is a prime target of modern therapeutic approaches, made possible due to the higher spectral resolution of 7 T systems.

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YNIMG Journal 2019 Journal Article

Whole-slice mapping of GABA and GABA+ at 7T via adiabatic MEGA-editing, real-time instability correction, and concentric circle readout

Philipp Moser
Lukas Hingerl
Bernhard Strasser
Michal Považan
Gilbert Hangel
Ovidiu C. Andronesi
Andre van der Kouwe
Stephan Gruber

An adiabatic MEscher-GArwood (MEGA)-editing scheme, using asymmetric hyperbolic secant editing pulses, was developed and implemented in a B1 +-insensitive, 1D-semiLASER (Localization by Adiabatic SElective Refocusing) MR spectroscopic imaging (MRSI) sequence for the non-invasive mapping of γ-aminobutyric acid (GABA) over a whole brain slice. Our approach exploits the advantages of edited-MRSI at 7T while tackling challenges that arise with ultra-high-field-scans. Spatial-spectral encoding, using density-weighted, concentric circle echo planar trajectory readout, enabled substantial MRSI acceleration and an improved point-spread-function, thereby reducing extracranial lipid signals. Subject motion and scanner instabilities were corrected in real-time using volumetric navigators optimized for 7T, in combination with selective reacquisition of corrupted data to ensure robust subtraction-based MEGA-editing. Simulations and phantom measurements of the adiabatic MEGA-editing scheme demonstrated stable editing efficiency even in the presence of ±0. 15 ppm editing frequency offsets and B1 + variations of up to ±30% (as typically encountered in vivo at 7T), in contrast to conventional Gaussian editing pulses. Volunteer measurements were performed with and without global inversion recovery (IR) to study regional GABA levels and their underlying, co-edited, macromolecular (MM) signals at 2. 99 ppm. High-quality in vivo spectra allowed mapping of pure GABA and MM-contaminated GABA+ (GABA + MM) along with Glx (Glu + Gln), with high-resolution (eff. voxel size: 1. 4 cm3) and whole-slice coverage in 24 min scan time. Metabolic ratio maps of GABA/tNAA, GABA+/tNAA, and Glx/tNAA were correlated linearly with the gray matter fraction of each voxel. A 2. 15-fold increase in gray matter to white matter contrast was observed for GABA when enabling IR, which we attribute to the higher abundance of macromolecules at 2. 99 ppm in the white matter than in the gray matter. In conclusion, adiabatic MEGA-editing with 1D-semiLASER selection is as a promising approach for edited-MRSI at 7T. Our sequence capitalizes on the benefits of ultra-high-field MRSI while successfully mitigating the challenges related to B0/B1 + inhomogeneities, prolonged scan times, and motion/scanner instability artifacts. Robust and accurate 2D mapping has been shown for the neurotransmitters GABA and Glx.

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YNIMG Journal 2018 Journal Article

Key clinical benefits of neuroimaging at 7 T

Siegfried Trattnig
Elisabeth Springer
Wolfgang Bogner
Gilbert Hangel
Bernhard Strasser
Barbara Dymerska
Pedro Lima Cardoso
Simon Daniel Robinson

The growing interest in ultra-high field MRI, with more than 35. 000 MR examinations already performed at 7T, is related to improved clinical results with regard to morphological as well as functional and metabolic capabilities. Since the signal-to-noise ratio increases with the field strength of the MR scanner, the most evident application at 7T is to gain higher spatial resolution in the brain compared to 3T. Of specific clinical interest for neuro applications is the cerebral cortex at 7T, for the detection of changes in cortical structure, like the visualization of cortical microinfarcts and cortical plaques in Multiple Sclerosis. In imaging of the hippocampus, even subfields of the internal hippocampal anatomy and pathology may be visualized with excellent spatial resolution. Using Susceptibility Weighted Imaging, the plaque-vessel relationship and iron accumulations in Multiple Sclerosis can be visualized, which may provide a prognostic factor of disease. Vascular imaging is a highly promising field for 7T which is dealt with in a separate dedicated article in this special issue. The static and dynamic blood oxygenation level-dependent contrast also increases with the field strength, which significantly improves the accuracy of pre-surgical evaluation of vital brain areas before tumor removal. Improvement in acquisition and hardware technology have also resulted in an increasing number of MR spectroscopic imaging studies in patients at 7T. More recent parallel imaging and short-TR acquisition approaches have overcome the limitations of scan time and spatial resolution, thereby allowing imaging matrix sizes of up to 128×128. The benefits of these acquisition approaches for investigation of brain tumors and Multiple Sclerosis have been shown recently. Together, these possibilities demonstrate the feasibility and advantages of conducting routine diagnostic imaging and clinical research at 7T.

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YNIMG Journal 2018 Journal Article

Ultra-high resolution brain metabolite mapping at 7 T by short-TR Hadamard-encoded FID-MRSI

Gilbert Hangel
Bernhard Strasser
Michal Považan
Eva Heckova
Lukas Hingerl
Roland Boubela
Stephan Gruber
Siegfried Trattnig

MRSI in the brain at ≥7 T is a technique of great promise, but has been limited mainly by low B0/B1 +-homogeneity, specific absorption rate restrictions, long measurement times, and low spatial resolution. To overcome these limitations, we propose an ultra-high resolution (UHR) MRSI sequence that provides a 128×128 matrix with a nominal voxel volume of 1. 7×1. 7×8mm3 in a comparatively short measurement time. A clinically feasible scan time of 10–20min is reached via a short TR of 200 ms due to an optimised free induction decay-based acquisition with shortened water suppression as well as parallel imaging (PI) using Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration (CAIPIRINHA). This approach is not limited to a rectangular region of interest in the centre of the brain, but also covers cortical brain regions. Transversal pulse-cascaded Hadamard encoding was able to further extend the coverage to 3D-UHR-MRSI of four slices (100×100×4 matrix size), with a measurement time of 17min. Lipid contamination was removed during post-processing using L2-regularisation. Simulations, phantom and volunteer measurements were performed. The obtained single-slice and 3D-metabolite maps show the brain in unprecedented detail (e. g. , hemispheres, ventricles, gyri, and the contrast between grey and white matter). This facilitates the use of UHR-MRSI for clinical applications, such as measurements of the small structures and metabolic pathologic deviations found in small Multiple Sclerosis lesions.

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YNIMG Journal 2015 Journal Article

Mapping of brain macromolecules and their use for spectral processing of 1 H-MRSI data with an ultra-short acquisition delay at 7 T

Michal Považan
Gilbert Hangel
Bernhard Strasser
Stephan Gruber
Marek Chmelik
Siegfried Trattnig
Wolfgang Bogner

Long echo time (TE) MR spectroscopy (MRS) sequences are sensitive only to metabolites of low molecular weight. At shorter TE, significantly more metabolite signals are detectable, including broad signals of high-molecular-weight macromolecules (MMs). Although the presence of MM resonances can bias metabolite quantification at short TE, proper quantification of MMs is important since MMs themselves may serve as potentially valuable biomarkers for many pathologies. We have therefore developed an FID-based 2D-MR Spectroscopic Imaging (2D-MRSI) sequence to map MMs in healthy brain tissue at 7T within a scan time of ~17min and a repetition time of 879ms. This 2D-MRSI technique provides MM maps over a whole slice (i. e. , including cortical gray matter) at an ultra-short acquisition delay of 1. 3ms, using double inversion for efficient nulling of low-molecular-weight metabolites. The optimal sequence parameters were estimated using Bloch simulations, phantom testing, and in vivo validation. The acquired in vivo MM spectra (n =6) included nine distinct MM peaks in the range of ~0. 9–3. 7ppm. The measured average MM spectrum was incorporated into the LCModel basis set and utilized for further quantification of MRSI data sets without metabolite nulling, which were acquired in five additional volunteers. The quantification results for two basis sets, one including the MMs and one without MM spectrum, were compared. Due to the high spectral resolution and full signal detection provided by the FID-MRSI sequence, we could successfully map five important brain metabolites. Most quantified metabolite signal amplitudes were significantly lower since the inclusion of MMs into the basis set corrected the overestimation of metabolite signals. The precision of fit (i. e. , Cramér Rao lower bounds) remained unchanged. Our MM maps show that the overall MM contribution was higher in gray matter than in white matter. In conclusion, the acquired MM spectrum improved the accuracy of metabolite quantification and allowed the acquisition of high spatial resolution maps of five major brain metabolites and also MMs.

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YNIMG Journal 2014 Journal Article

3D GABA imaging with real-time motion correction, shim update and reacquisition of adiabatic spiral MRSI

Wolfgang Bogner
Borjan Gagoski
Aaron T. Hess
Himanshu Bhat
M. Dylan Tisdall
Andre J.W. van der Kouwe
Bernhard Strasser
Małgorzata Marjańska

Gamma-aminobutyric acid (GABA) and glutamate (Glu) are the major neurotransmitters in the brain. They are crucial for the functioning of healthy brain and their alteration is a major mechanism in the pathophysiology of many neuro-psychiatric disorders. Magnetic resonance spectroscopy (MRS) is the only way to measure GABA and Glu non-invasively in vivo. GABA detection is particularly challenging and requires special MRS techniques. The most popular is MEscher–GArwood (MEGA) difference editing with single-voxel Point RESolved Spectroscopy (PRESS) localization. This technique has three major limitations: a) MEGA editing is a subtraction technique, hence is very sensitive to scanner instabilities and motion artifacts. b) PRESS is prone to localization errors at high fields (≥3T) that compromise accurate quantification. c) Single-voxel spectroscopy can (similar to a biopsy) only probe steady GABA and Glu levels in a single location at a time. To mitigate these problems, we implemented a 3D MEGA-editing MRS imaging sequence with the following three features: a) Real-time motion correction, dynamic shim updates, and selective reacquisition to eliminate subtraction artifacts due to scanner instabilities and subject motion. b) Localization by Adiabatic SElective Refocusing (LASER) to improve the localization accuracy and signal-to-noise ratio. c) K-space encoding via a weighted stack of spirals provides 3D metabolic mapping with flexible scan times. Simulations, phantom and in vivo experiments prove that our MEGA-LASER sequence enables 3D mapping of GABA+ and Glx (Glutamate+Gluatmine), by providing 1. 66 times larger signal for the 3. 02ppm multiplet of GABA+ compared to MEGA-PRESS, leading to clinically feasible scan times for 3D brain imaging. Hence, our sequence allows accurate and robust 3D-mapping of brain GABA+ and Glx levels to be performed at clinical 3T MR scanners for use in neuroscience and clinical applications.

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