Influence of running on femoroacetabular joint bone-to-bone distances.

There is limited data quantifying the influence of running on hip cartilage mechanics. The goal of this investigation was to quantify changes in hip joint bone-to-bone distance in response to a 3-mile treadmill run. We acquired magnetic resonance (MR) images of the dominant hip of eight young, asymptomatic runners (five males, three females) before and immediately after they ran 3 miles at a self-selected pace on a level treadmill. The femoral heads and acetabula were semiautomatically segmented from the pre- and post-exercise MR images to generate three-dimensional models of each participant's hip that were used to compute changes in the bone-to-bone distances incurred by the running exercise. We observed a significant 3% decrease in bone-to-bone distance from 3.47 ± 0.20 to 3.36 ± 0.22 mm between the femoral head and acetabulum after a 3-mile treadmill run (mean ± 95% confidence interval; p = 0.03). These findings provide new baseline data describing how running impacts the hip joint in young, asymptomatic runners.

Vespa: Integrated applications for RF pulse design, spectral simulation and MRS data analysis.

PURPOSE: The Vespa package (Versatile Simulation, Pulses, and Analysis) is described and demonstrated. It provides workflows for developing and optimizing linear combination modeling (LCM) fitting for 1 H MRS data using intuitive graphical user interface interfaces for RF pulse design, spectral simulation, and MRS data analysis. Command line interfaces for embedding workflows in MR manufacturer platforms and utilities for synthetic dataset creation are included. Complete provenance is maintained for all steps in workflows. THEORY AND METHODS: Vespa is written in Python for compatibility across operating systems. It embeds the PyGAMMA spectral simulation library for spectral simulation. Multiprocessing methods accelerate processing and visualization. Applications use the Vespa database for results storage and cross-application access. Three projects demonstrate pulse, sequence, simulation, and data analysis workflows: (1) short TE semi-LASER single-voxel spectroscopy (SVS) LCM fitting, (2) optimizing MEGA-PRESS (MEscher-GArwood Point RESolved Spectroscopy) flip angle and LCM fitting, and (3) creating a synthetic short TE dataset. RESULTS: The LCM workflows for in vivo basis set creation and spectral analysis showed reasonable results for both the short TE semi-LASER and MEGA-PRESS. Examples of pulses, simulations, and data fitting are shown in Vespa application interfaces for various steps to demonstrate the interactive workflow. CONCLUSION: Vespa provides an efficient and extensible platform for characterizing RF pulses, pulse design, spectral simulation optimization, and automated LCM fitting via an interactive platform. Modular design and command line interface make it easy to embed in other platforms. As open source, it is free to the MRS community for use and extension. Vespa source code and documentation are available through GitHub.

The association between language-based task-functional magnetic resonance imaging hemodynamics and baseline GABA+ and glutamate-glutamine measured in pre-supplementary motor area: A pilot study in an aging model.

Aging is a natural phenomenon that elicits slow and progressive cerebrovascular and neurophysiological changes that eventually lead to cognitive decline. The objective of this pilot study is to examine the association of GABA+ and glutamate-glutamine (Glx) complex with language-based blood oxygen level dependent (BOLD) hemodynamics in an aging model. More specifically, using standard BOLD we will first attempt to validate whether previously reported findings for BOLD amplitude and resting neurochemical relationships hold in an aging model. Secondly, we will investigate how our recently established neurosensitized task-BOLD energetics relate to resting GABA+ and Glx, especially accounting for titration of task difficulty. To support the above endeavors, we optimize the baseline fitting for edited magnetic resonance spectroscopy (MRS) difference spectra to sensitize GABA+ and Glx concentrations to aging-related differences. We identify a spline-knot spacing of 0.6ppm to yield the optimal aging-related differences in GABA+ and Glx. The optimized MRS values were then graduated to relate to task-BOLD hemodynamics. Our results did not replicate previous findings that relate task-BOLD amplitude and resting GABA+ and Glx. However, we did identify neurochemistry relationships with the vascularly-driven dispersion component of the hemodynamic response function, specifically in older participants. In terms of neuro-sensitized BOLD energetics and the underlying role of GABA+ and Glx, our data suggests that the task demands are supported by both neurometabolites depending on the difficulty of the task stimuli. Another novelty is that we developed task-based functional parcellation of pre-SMA using both groups. In sum, we are the first to demonstrate that multimodal task-fMRI and MRS studies are beneficial to improve our understanding of the aging brain physiology, and to set the platform to better inform approaches for clinical care in aging-related neurovascular diseases. We also urge future studies to replicate our findings in a larger population incorporating a lifespan framework.

NIfTI-MRS: A standard data format for magnetic resonance spectroscopy.

PURPOSE: Multiple data formats in the MRS community currently hinder data sharing and integration. NIfTI-MRS is proposed as a standard spectroscopy data format, implemented as an extension to the Neuroimaging informatics technology initiative (NIfTI) format. This standardized format can facilitate data sharing and algorithm development as well as ease integration of MRS analysis alongside other imaging modalities. METHODS: A file format using the NIfTI header extension framework incorporates essential spectroscopic metadata and additional encoding dimensions. A detailed description of the specification is provided. An open-source command-line conversion program is implemented to convert single-voxel and spectroscopic imaging data to NIfTI-MRS. Visualization of data in NIfTI-MRS is provided by development of a dedicated plugin for FSLeyes, the FMRIB Software Library (FSL) image viewer. RESULTS: Online documentation and 10 example datasets in the proposed format are provided. Code examples of NIfTI-MRS readers are implemented in common programming languages. Conversion software, spec2nii, currently converts 14 formats where data is stored in image-space to NIfTI-MRS, including Digital Imaging and Communications in Medicine (DICOM) and vendor proprietary formats. CONCLUSION: NIfTI-MRS aims to solve issues arising from multiple data formats being used in the MRS community. Through a single conversion point, processing and analysis of MRS data are simplified, thereby lowering the barrier to use of MRS. Furthermore, it can serve as the basis for open data sharing, collaboration, and interoperability of analysis programs. Greater standardization and harmonization become possible. By aligning with the dominant format in neuroimaging, NIfTI-MRS enables the use of mature tools present in the imaging community, demonstrated in this work by using a dedicated imaging tool, FSLeyes, for visualization.

Design and validation of a semi-automatic bone segmentation algorithm from MRI to improve research efficiency.

Segmentation of medical images into different tissue types is essential for many advancements in orthopaedic research; however, manual segmentation techniques can be time- and cost-prohibitive. The purpose of this work was to develop a semi-automatic segmentation algorithm that leverages gradients in spatial intensity to isolate the patella bone from magnetic resonance (MR) images of the knee that does not require a training set. The developed algorithm was validated in a sample of four human participants (in vivo) and three porcine stifle joints (ex vivo) using both magnetic resonance imaging (MRI) and computed tomography (CT). We assessed the repeatability (expressed as mean ± standard deviation) of the semi-automatic segmentation technique on: (1) the same MRI scan twice (Dice similarity coefficient = 0.988 ± 0.002; surface distance = - 0.01 ± 0.001 mm), (2) the scan/re-scan repeatability of the segmentation technique (surface distance = - 0.02 ± 0.03 mm), (3) how the semi-automatic segmentation technique compared to manual MRI segmentation (surface distance = - 0.02 ± 0.08 mm), and (4) how the semi-automatic segmentation technique compared when applied to both MRI and CT images of the same specimens (surface distance = - 0.02 ± 0.06 mm). Mean surface distances perpendicular to the cartilage surface were computed between pairs of patellar bone models. Critically, the semi-automatic segmentation algorithm developed in this work reduced segmentation time by approximately 75%. This method is promising for improving research throughput and potentially for use in generating training data for deep learning algorithms.

Lumbar intervertebral disc diurnal deformations and T2 and T1rho relaxation times vary by spinal level and disc region.

PURPOSE: Magnetic resonance imaging (MRI) is routinely used to evaluate spine pathology; however, standard imaging findings weakly correlate to low back pain. Abnormal disc mechanical function is implicated as a cause of back pain but is not assessed using standard clinical MRI. Our objective was to utilize our established MRI protocol for measuring disc function to quantify disc mechanical function in a healthy cohort. METHODS: We recruited young, asymptomatic volunteers (6 male/6 female; age 18-30 years; BMI < 30) and used MRI to determine how diurnal deformations in disc height, volume, and perimeter were affected by spinal level, disc region, MRI biomarkers of disc health (T2, T1rho), and Pfirrmann grade. RESULTS: Lumbar discs deformed by a mean of -6.1% (95% CI: -7.6%, -4.7%) to -8.0% (CI: -10.6%, -5.4%) in height and -5.4% (CI: -7.6%, -3.3%) to -8.5% (CI: -11.0%, -6.0%) in volume from AM to PM across spinal levels. Regional deformations were more uniform in cranial lumbar levels and concentrated posteriorly in the caudal levels, reaching a maximum of 13.1% at L5-S1 (CI:-16.1%, -10.2%). T2 and T1rho relaxation times were greatest in the nucleus and varied circumferentially within the annulus. T2 relaxation times were greatest at the most cranial spinal levels and decreased caudally. In this young healthy cohort, we identified a weak association between nucleus T2 and the diurnal change in the perimeter. CONCLUSIONS: Spinal level is a key factor in determining regional disc deformations. Interestingly, deformations were concentrated in the posterior regions of caudal discs where disc herniation is most prevalent.

Influence of editing pulse flip angle on J-difference MR spectroscopy.

PURPOSE: To investigate the editing-pulse flip angle (FA) dependence of editing efficiency and ultimately to maximize the edited signal of commonly edited MR spectroscopy (MRS) signals, such as gamma-aminobutyric acid (GABA) and lactate. METHODS: Density-matrix simulations were performed for a range of spin systems to find the editing-pulse FA for maximal editing efficiency. Simulations were confirmed by phantom experiments and in vivo measurements in 10 healthy participants using a 3T Philips scanner. Four MEGA-PRESS in vivo measurements targeting GABA+ and lactate were performed, comparing the conventional editing-pulse FA (FA = 180°) to the optimal one suggested by simulations (FA = 210°). RESULTS: Simulations and phantom experiments show that edited GABA and lactate signals are maximal at FA = 210°. Compared to conventional editing (FA = 180°), in vivo signals from GABA+ and lactate signals increase on average by 8.5% and 9.3%, respectively. CONCLUSION: Increasing the FA of editing-pulses in the MEGA-PRESS experiment from 180° to 210° increases the edited signals from GABA+ and lactate by about 9% in vivo.

Across-vendor standardization of semi-LASER for single-voxel MRS at 3T.

The semi-adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single-shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high- and ultra-high fields. Across-vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B1 requirements of the adiabatic inversion pulses and maximum B1 limitations on some platforms. The aims of this study were to design a short-echo sLASER sequence that can be executed within a B1 limit of 15 µT by taking advantage of gradient-modulated RF pulses, to implement it on three major platforms and to evaluate the between-vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel-based first and second order B0 shimming and voxel-based B1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient-modulated pulses considered (GOIA, FOCI and BASSI), GOIA-WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B1 of 15 µT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter-pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE 'Braino' phantom between vendors. High-quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal-to-noise ratio > 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi-site studies with clinical cohorts.

Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations.

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.

Global brain volume and N-acetyl-aspartate decline over seven decades of normal aging.

We characterize the whole-brain N-acetyl-aspartate (WBNAA) and brain tissue fractions across the adult lifespan and test the hypothesis that, despite age-related atrophy, neuronal integrity (reflected by WBNAA) is preserved in normal aging. Two-hundred-and-seven participants: 133 cognitively intact older adults (73.6 ± 7.4 mean ± standard deviation, range: 60-90 year old) and 84 young (37.9 ± 11, range: 21-59 year old) were scanned with proton magnetic resonance spectroscopy and T1-weighted MRI. Their WBNAA, fractional brain parenchyma, and gray and white matter volumes (fBPV, fGM, and fWM) were compared and modeled as functions of age and sex. Compared with young, older-adults' WBNAA was lower by ~35%, and fBPV, fGM and fWM were lower by ~10%. Linear regressions found 0.5%/year WBNAA and 0.2%/year fBPV and fGM declines, whereas fWM rose to age ~40 years, and declined thereafter. fBPV and fGM were 1.8% and 4% higher in women, with no sex decline rates difference. We conclude that contrary to our hypothesis, atrophy was accompanied by WBNAA decline. Across the entire age range, women's brains showed less atrophy than men's. Formulas to estimate WBNAA and brain tissue fractions in healthy adults are provided to help differentiate normal from abnormal aging.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations.

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Dynamic perfluorinated gas MRI reveals abnormal ventilation despite normal FEV1 in cystic fibrosis.

We hypothesized that dynamic perfluorinated gas MRI would sensitively detect mild cystic fibrosis (CF) lung disease. This cross-sectional study enrolled 20 healthy volunteers and 24 stable subjects with CF, including a subgroup of subjects with normal forced expiratory volume in the first second (FEV1; >80% predicted, n = 9). Dynamic fluorine-19-enhanced MRI (19F MRI) were acquired during sequential breath holds while breathing perfluoropropane (PFP) and during gas wash-out. Outcomes included the fraction of lung without significant ventilation (ventilation defect percent, VDP) and time constants that described PFP wash-in and wash-out kinetics. VDP values (mean ± SD) of healthy controls (3.87% ± 2.7%) were statistically different from moderate CF subjects (19.5% ± 15.5%, P = 0.001) but not from mild CF subjects (10.4% ± 9.9%, P = 0.24). In contrast, the fractional lung volume with slow gas wash-out was elevated both in subjects with mild (9.61% ± 4.87%; P = 0.0066) and moderate CF (16.01% ± 5.01%; P = 0.0002) when compared with healthy controls (3.84% ± 2.16%) and distinguished mild from moderate CF (P = 0.006). 19F MRI detected significant ventilation abnormalities in subjects with CF. The ability of gas wash-out kinetics to distinguish between healthy and mild CF lung disease subjects makes 19F MRI a potentially valuable method for the characterization of early lung disease in CF. This study has been registered at ClinicalTrials.gov (NCT03489590).

Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Proton MRS (1 H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good-quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi-adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0 ) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.

AutoVOI: real-time automatic prescription of volume-of-interest for single voxel spectroscopy.

PURPOSE: To develop a fast and automated volume-of-interest (VOI) prescription pipeline (AutoVOI) for single-voxel MRS that removes the need for manual VOI placement, allows flexible VOI planning in any brain region, and enables high inter- and intra-subject consistency of VOI prescription. METHODS: AutoVOI was designed to transfer pre-defined VOIs from an atlas to the 3D anatomical data of the subject during the scan. The AutoVOI pipeline was optimized for consistency in VOI placement (precision), enhanced coverage of the targeted tissue (accuracy), and fast computation speed. The tool was evaluated against manual VOI placement using existing T1 -weighted data sets and corresponding VOI prescriptions. Finally, it was implemented on 2 scanner platforms to acquire MRS data from clinically relevant VOIs that span the cerebrum, cerebellum, and the brainstem. RESULTS: The AutoVOI pipeline includes skull stripping, non-linear registration of the atlas to the subject's brain, and computation of the VOI coordinates and angulations using a minimum oriented bounding box algorithm. When compared against manual prescription, AutoVOI showed higher intra- and inter-subject spatial consistency, as quantified by generalized Dice coefficients (GDC), lower intra- and inter-subject variability in tissue composition (gray matter, white matter, and cerebrospinal fluid) and higher or equal accuracy, as quantified by GDC of prescribed VOI with targeted tissues. High quality spectra were obtained on Siemens and Philips 3T systems from 6 automatically prescribed VOIs by the tool. CONCLUSION: Robust automatic VOI prescription is feasible and can help facilitate clinical adoption of MRS by avoiding operator dependence of manual selection.

A convolutional neural network to filter artifacts in spectroscopic MRI.

PURPOSE: Proton MRSI is a noninvasive modality capable of generating volumetric maps of in vivo tissue metabolism without the need for ionizing radiation or injected contrast agent. Magnetic resonance spectroscopic imaging has been shown to be a viable imaging modality for studying several neuropathologies. However, a key hurdle in the routine clinical adoption of MRSI is the presence of spectral artifacts that can arise from a number of sources, possibly leading to false information. METHODS: A deep learning model was developed that was capable of identifying and filtering out poor quality spectra. The core of the model used a tiled convolutional neural network that analyzed frequency-domain spectra to detect artifacts. RESULTS: When compared with a panel of MRS experts, our convolutional neural network achieved high sensitivity and specificity with an area under the curve of 0.95. A visualization scheme was implemented to better understand how the convolutional neural network made its judgement on single-voxel or multivoxel MRSI, and the convolutional neural network was embedded into a pipeline capable of producing whole-brain spectroscopic MRI volumes in real time. CONCLUSION: The fully automated method for assessment of spectral quality provides a valuable tool to support clinical MRSI or spectroscopic MRI studies for use in fields such as adaptive radiation therapy planning.

A magnetic resonance imaging framework for quantifying intervertebral disc deformation in vivo: Reliability and application to diurnal variations in lumbar disc shape.

Low back pain is a significant socioeconomic burden in the United States and lumbar intervertebral disc degeneration is frequently implicated as a cause. The discs play an important mechanical role in the spine, yet the relationship between disc function and back pain is poorly defined. The objective of this work was to develop a technique using magnetic resonance imaging (MRI) and three-dimensional modeling to measure in vivo disc deformations. Using this method, we found that disc geometry was measurable with precision less than the in-plane dimensions of a voxel (≈100 µm, 10% of the MRI pixel size). Furthermore, there was excellent agreement between mean disc height, disc perimeter, disc volume and regional disc height measurements for multiple trials from an individual rater (standard deviation <3.1% across all measurements) and between mean height, perimeter, and volume measurements made by two independent raters (error <1.5% across all measurements). We then used this measurement system to track diurnal deformations in the L5-S1 disc in a young, healthy population (n = 8; age 24.1 ±â€¯3.3 yrs; 2 M/6F). We measured decreases in the mean disc height (-8%) and volume (-9%) with no changes in perimeter over an eight-hour workday. We found that the largest height losses occurred in the posterior (-13%) and posterior-lateral (-14%) regions adjacent to the outer annulus fibrosus. Diurnal annulus fibrosus (AF) strains induced by posterior and posterior-lateral height loss may increase the risk for posterior disc herniation or posterior AF tears. These preliminary findings lay a foundation for determining how deviations from normal deformations may contribute to back pain.

Whole brain neuronal abnormalities in focal epilepsy quantified with proton MR spectroscopy.

OBJECTIVE: To test the hypothesis that localization-related epilepsy is associated with widespread neuronal dysfunction beyond the ictal focus, reflected by a decrease in patients' global concentration of their proton MR spectroscopy (1H-MRS) observed marker, N-acetyl-aspartate (NAA). METHODS: Thirteen patients with localization-related epilepsy (7 men, 6 women) 40±13 (mean±standard-deviation)years old, 8.3±13.4years of disease duration; and 14 matched controls, were scanned at 3 T with MRI and whole-brain (WB) 1H MRS. Intracranial fractions of brain volume, gray and white matter (fBV, fGM, fWM) were segmented from the MRI, and global absolute NAA creatine (Cr) and choline (Cho) concentrations were estimated from their WB 1H MRS. These metrics were compared between patients and controls using an unequal variance t test. RESULTS: Patients' fBV, fGM and fWM: 0.81±0.07, 0.47±0.04, 0.31±0.04 were not different from controls' 0.79±0.05, 0.48±0.04, 0.32±0.02; nor were their Cr and Cho concentrations: 7.1±1.1 and 1.3±0.2 millimolar (mM) versus 7.7±0.7 and 1.4±0.1mM (p>0.05 all). Patients' global NAA concentration: 11.5±1.5 mM, however, was 12% lower than controls' 13.0±0.8mM (p=0.004). CONCLUSIONS: These findings indicate that neuronal dysfunction in localization-related epilepsy extends globally, beyond the ictal zone, but without atrophy or spectroscopic evidence of other pathology. This suggests a diffuse decline in the neurons' health, rather than their number, early in the disease course. WB 1H-MRS assessment, therefore, may be a useful tool for quantification of global neuronal dysfunction load in epilepsy.

Global brain metabolic quantification with whole-head proton MRS at 3 T.

Total N-acetyl-aspartate + N-acetyl-aspartate-glutamate (NAA), total creatine (Cr) and total choline (Cho) proton MRS (1 H-MRS) signals are often used as surrogate markers in diffuse neurological pathologies, but spatial coverage of this methodology is limited to 1%-65% of the brain. Here we wish to demonstrate that non-localized, whole-head (WH) 1 H-MRS captures just the brain's contribution to the Cho and Cr signals, ignoring all other compartments. Towards this end, 27 young healthy adults (18 men, 9 women), 29.9 ± 8.5 years old, were recruited and underwent T1 -weighted MRI for tissue segmentation, non-localizing, approximately 3 min WH 1 H-MRS (TE /TR /TI  = 5/10/940 ms) and 30 min 1 H-MR spectroscopic imaging (MRSI) (TE /TR  = 35/2100 ms) in a 360 cm3 volume of interest (VOI) at the brain's center. The VOI absolute NAA, Cr and Cho concentrations, 7.7 ± 0.5, 5.5 ± 0.4 and 1.3 ± 0.2 mM, were all within 10% of the WH: 8.6 ± 1.1, 6.0 ± 1.0 and 1.3 ± 0.2 mM. The mean NAA/Cr and NAA/Cho ratios in the WH were only slightly higher than the "brain-only" VOI: 1.5 versus 1.4 (7%) and 6.6 versus 5.9 (11%); Cho/Cr were not different. The brain/WH volume ratio was 0.31 ± 0.03 (brain ≈ 30% of WH volume). Air-tissue susceptibility-driven local magnetic field changes going from the brain outwards showed sharp gradients of more than 100 Hz/cm (1 ppm/cm), explaining the skull's Cr and Cho signal losses through resonance shifts, line broadening and destructive interference. The similarity of non-localized WH and localized VOI NAA, Cr and Cho concentrations and their ratios suggests that their signals originate predominantly from the brain. Therefore, the fast, comprehensive WH-1 H-MRS method may facilitate quantification of these metabolites, which are common surrogate markers in neurological disorders.