Radiation damping at clinical field strength: Characterization and compensation in quantitative measurements.

PURPOSE: In any MR experiment, the bulk magnetization acts on itself, caused by the induced current in the RF receiver circuit that generates an oscillating damping field. This effect, known as "radiation damping" (RD), is usually weak and, therefore, unconsidered in MRI, but can affect quantitative studies performed with dedicated coils that provide a high SNR. The current work examined RD in a setup for investigations of small tissue specimens including a quantitative characterization of the spin-coil system. THEORY AND METHODS: A custom-made Helmholtz coil (radius and spacing 16 mm) was interfaced to a transmit-receive (Tx/Rx) switch with integrated passive feedback for modulation or suppression of RD similar to preamplifier decoupling. Pulse sequences included pulse-width arrays to demonstrate the absence/ presence of RD and difference techniques employing gradient pulses or composite RF pulses to quantify RD effects during free precession and transmission, respectively. Experiments were performed at 3T in small samples of MnCl2 solution. RESULTS: Significant RD effects may impact RF pulse application and evolution periods. Effective damping time constants were comparable to typical T2 * times or echo spacings in multi-echo sequences. Measurements of the phase relation showed that deviations from the commonly assumed 90° angle between the damping field and the transverse magnetization may occur. CONCLUSION: Radiation damping may affect the accuracy of quantitative MR measurements performed with dedicated RF coils. Efficient mitigation can be achieved hardware-based or by appropriate consideration in the pulse sequence.

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.

High-resolution magnetization-transfer imaging of post-mortem marmoset brain: Comparisons with relaxometry and histology.

Cell membranes and macromolecules or paramagnetic compounds interact with water proton spins, which modulates magnetic resonance imaging (MRI) contrast providing information on tissue composition. For a further investigation, quantitative magnetization transfer (qMT) parameters (at 3T), including the ratio of the macromolecular and water proton pools, F, and the exchange-rate constant as well as the (observed) longitudinal and the effective transverse relaxation rates (at 3T and 7T), R1obs and R2*, respectively, were measured at high spatial resolution (200 µm) in a slice of fixed marmoset brain and compared to histology results obtained with Gallyas' myelin stain and Perls' iron stain. R1obs and R2* were linearly correlated with the iron content for the entire slice, whereas distinct differences were obtained between gray and white matter for correlations of relaxometry and qMT parameters with myelin content. The combined results suggest that the macromolecular pool interacting with water consists of myelin and (less efficient) non-myelin contributions. Despite strong correlation of F and R1obs, none of these parameters was uniquely specific to myelination. Due to additional sensitivity to iron stores, R1obs and R2* were more sensitive for depicting microstructural differences between cortical layers than F.

Rapid volumetric brain changes after acute psychosocial stress.

Stress is an important trigger for brain plasticity: Acute stress can rapidly affect brain activity and functional connectivity, and chronic or pathological stress has been associated with structural brain changes. Measures of structural magnetic resonance imaging (MRI) can be modified by short-term motor learning or visual stimulation, suggesting that they also capture rapid brain changes. Here, we investigated volumetric brain changes (together with changes in T1 relaxation rate and cerebral blood flow) after acute stress in humans as well as their relation to psychophysiological stress measures. Sixty-seven healthy men (25.8±2.7 years) completed a standardized psychosocial laboratory stressor (Trier Social Stress Test) or a control version while blood, saliva, heart rate, and psychometrics were sampled. Structural MRI (T1 mapping / MP2RAGE sequence) at 3T was acquired 45 min before and 90 min after intervention onset. Grey matter volume (GMV) changes were analysed using voxel-based morphometry. Associations with endocrine, autonomic, and subjective stress measures were tested with linear models. We found significant group-by-time interactions in several brain clusters including anterior/mid-cingulate cortices and bilateral insula: GMV was increased in the stress group relative to the control group, in which several clusters showed a GMV decrease. We found a significant group-by-time interaction for cerebral blood flow, and a main effect of time for T1 values (longitudinal relaxation time). In addition, GMV changes were significantly associated with state anxiety and heart rate variability changes. Such rapid GMV changes assessed with VBM may be induced by local tissue adaptations to changes in energy demand following neural activity. Our findings suggest that endogenous brain changes are counteracted by acute psychosocial stress, which emphasizes the importance of considering homeodynamic processes and generally highlights the influence of stress on the brain.

High angular resolution susceptibility imaging and estimation of fiber orientation distribution functions in primate brain.

Uncovering brain-tissue microstructure including axonal characteristics is a major neuroimaging research focus. Within this scope, anisotropic properties of magnetic susceptibility in white matter have been successfully employed to estimate primary axonal trajectories using mono-tensorial models. However, anisotropic susceptibility has not yet been considered for modeling more complex fiber structures within a voxel, such as intersecting bundles, or an estimation of orientation distribution functions (ODFs). This information is routinely obtained by high angular resolution diffusion imaging (HARDI) techniques. In applications to fixed tissue, however, diffusion-weighted imaging suffers from an inherently low signal-to-noise ratio and limited spatial resolution, leading to high demands on the performance of the gradient system in order to mitigate these limitations. In the current work, high angular resolution susceptibility imaging (HARSI) is proposed as a novel, phase-based methodology to estimate ODFs. A multiple gradient-echo dataset was acquired in an entire fixed chimpanzee brain at 61 orientations by reorienting the specimen in the magnetic field. The constant solid angle method was adapted for estimating phase-based ODFs. HARDI data were also acquired for comparison. HARSI yielded information on whole-brain fiber architecture, including identification of peaks of multiple bundles that resembled features of the HARDI results. Distinct differences between both methods suggest that susceptibility properties may offer complementary microstructural information. These proof-of-concept results indicate a potential to study the axonal organization in post-mortem primate and human brain at high resolution.

Convergent imaging-transcriptomic evidence for disturbed iron homeostasis in Gilles de la Tourette syndrome.

Gilles de la Tourette syndrome (GTS) is a neuropsychiatric movement disorder with reported abnormalities in various neurotransmitter systems. Considering the integral role of iron in neurotransmitter synthesis and transport, it is hypothesized that iron exhibits a role in GTS pathophysiology. As a surrogate measure of brain iron, quantitative susceptibility mapping (QSM) was performed in 28 patients with GTS and 26 matched controls. Significant susceptibility reductions in the patients, consistent with reduced local iron content, were obtained in subcortical regions known to be implicated in GTS. Regression analysis revealed a significant negative association of tic scores and striatal susceptibility. To interrogate genetic mechanisms that may drive these reductions, spatially specific relationships between susceptibility and gene-expression patterns from the Allen Human Brain Atlas were assessed. Correlations in the striatum were enriched for excitatory, inhibitory, and modulatory neurochemical signaling mechanisms in the motor regions, mitochondrial processes driving ATP production and iron­sulfur cluster biogenesis in the executive subdivision, and phosphorylation-related mechanisms affecting receptor expression and long-term potentiation in the limbic subdivision. This link between susceptibility reductions and normative transcriptional profiles suggests that disruptions in iron regulatory mechanisms are involved in GTS pathophysiology and may lead to pervasive abnormalities in mechanisms regulated by iron-containing enzymes.

Germany's journey toward 14 Tesla human magnetic resonance.

Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths.

Multi-echo investigations of positive and negative CBF and concomitant BOLD changes.

Unlike the positive blood oxygenation level-dependent (BOLD) response (PBR), commonly taken as an indication of an 'activated' brain region, the physiological origin of negative BOLD signal changes (i.e. a negative BOLD response, NBR), also referred to as 'deactivation' is still being debated. In this work, an attempt was made to gain a better understanding of the underlying mechanism by obtaining a comprehensive measure of the contributing cerebral blood flow (CBF) and its relationship to the NBR in the human visual cortex, in comparison to a simultaneously induced PBR in surrounding visual regions. To overcome the low signal-to-noise ratio (SNR) of CBF measurements, a newly developed multi-echo version of a center-out echo planar-imaging (EPI) readout was employed with pseudo-continuous arterial spin labeling (pCASL). It achieved very short echo and inter-echo times and facilitated a simultaneous detection of functional CBF and BOLD changes at 3 T with improved sensitivity. Evaluations of the absolute and relative changes of CBF and the effective transverse relaxation rate, R2*, the coupling ratios, and their dependence on CBF at rest, CBFrest, indicated differences between activated and deactivated regions. Analysis of the shape of the respective functional responses also revealed faster negative responses with more pronounced post-stimulus transients. Resulting differences in the flow-metabolism coupling ratios were further examined for potential distinctions in the underlying neuronal contributions.

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.

Brain Damage With Heart Failure: Cardiac Biomarker Alterations and Gray Matter Decline.

RATIONALE: Heart failure (HF) following heart damage leads to a decreased blood flow due to a reduced pump efficiency of the heart muscle. A consequence can be insufficient oxygen supply to the organism including the brain. While HF clearly shows neurological symptoms, such as fatigue, nausea, and dizziness, the implications for brain structure are not well understood. Few studies show regional gray matter decrease related to HF; however, the underlying mechanisms leading to the observed brain changes remain unclear. OBJECTIVE: To study the relationship between impaired heart function, hampered blood circulation, and structural brain change in a case-control study. METHODS AND RESULTS: Within a group of 80 patients of the Leipzig Heart Center, we investigated a potential correlation between HF biomarkers and the brain's gray matter density (GMD) obtained by magnetic resonance imaging. We observed a significant positive correlation between cardiac ejection fraction and GMD across the whole frontal and parietal medial cortex reflecting the consequence of HF onto the brain's gray matter. Moreover, we also obtained a relationship between GMD and the NT-proBNP (N-terminal prohormone of brain natriuretic peptide)-a biomarker that is used for screening, diagnosis, and prognosis of HF. Here, we found a significant negative correlation between NT-proBNP and GMD in the medial and posterior cingulate cortex but also in precuneus and hippocampus, which are key regions implicated in structural brain changes in dementia. CONCLUSIONS: We obtained significant correlations between brain structure and markers of heart failure including ejection fraction and NT-proBNP. A diminished GMD was found with decreased ejection fraction and increased NT-proBNP in wide brain regions including the whole frontomedian cortex as well as hippocampus and precuneus. Our observations might reflect structural brain damage in areas that are related to cognition; however, whether these structural changes facilitate the development of cognitive alterations has to be proven by further longitudinal studies.

Deconvolution-based distortion correction of EPI using analytic single-voxel point-spread functions.

PURPOSE: To develop a postprocessing algorithm that corrects geometric distortions due to spatial variations of the static magnetic field amplitude, B0 , and effects from relaxation during signal acquisition in EPI. THEORY AND METHODS: An analytic, complex point-spread function is deduced for k-space trajectories of EPI variants and applied to corresponding acquisitions in a resolution phantom and in human volunteers at 3 T. With the analytic point-spread function and experimental maps of B0 (and, optionally, the effective transverse relaxation time, T2* ) as input, a point-spread function matrix operator is devised for distortion correction by a Thikonov-regularized deconvolution in image space. The point-spread function operator provides additional information for an appropriate correction of the signal intensity distribution. A previous image combination algorithm for acquisitions with opposite phase blip polarities is adapted to the proposed method to recover destructively interfering signal contributions. RESULTS: Applications of the proposed deconvolution-based distortion correction ("DecoDisCo") algorithm demonstrate excellent distortion corrections and superior performance regarding the recovery of an undistorted intensity distribution in comparison to a multifrequency reconstruction. Examples include full and partial Fourier standard EPI scans as well as double-shot center-out trajectories. Compared with other distortion-correction approaches, DecoDisCo permits additional deblurring to obtain sharper images in cases of significant T2* effects. CONCLUSION: Robust distortion corrections in EPI acquisitions are feasible with high quality by regularized deconvolution with an analytic point-spread function. The general algorithm, which is publicly released on GitHub, can be straightforwardly adapted for specific EPI variants or other acquisition schemes.

Increased sensitivity and signal-to-noise ratio in diffusion-weighted MRI using multi-echo acquisitions.

Post-mortem diffusion MRI (dMRI) enables acquisitions of structural imaging data with otherwise unreachable resolutions - at the expense of longer scanning times. These data are typically acquired using highly segmented image acquisition strategies, thereby resulting in an incomplete signal decay before the MRI encoding continues. Especially in dMRI, with low signal intensities and lengthy contrast encoding, such temporal inefficiency translates into reduced image quality and longer scanning times. This study introduces Multi Echo (ME) acquisitions to dMRI on a human MRI system - a time-efficient approach, which increases SNR (Signal-to-Noise Ratio) and reduces noise bias for dMRI images. The benefit of the introduced ME-dMRI method was validated using numerical Monte Carlo simulations and showcased on a post-mortem brain of a wild chimpanzee. The proposed Maximum Likelihood Estimation echo combination results in an optimal SNR without detectable signal bias. The combined strategy comes at a small price in scanning time (here 30% additional) and leads to a substantial SNR increase (here white matter: ~ 1.6x, equivalent to 2.6 averages, grey matter: ~ 1.9x, equivalent to 3.6 averages) and a general reduction of the noise bias.

Cortical laminar resting-state signal fluctuations scale with the hypercapnic blood oxygenation level-dependent response.

Calibrated functional magnetic resonance imaging can remove unwanted sources of signal variability in the blood oxygenation level-dependent (BOLD) response. This is achieved by scaling, using information from a perfusion-sensitive scan during a purely vascular challenge, typically induced by a gas manipulation or a breath-hold task. In this work, we seek for a validation of the use of the resting-state fluctuation amplitude (RSFA) as a scaling factor to remove vascular contributions from the BOLD response. Given the peculiarity of depth-dependent vascularization in gray matter, BOLD and vascular space occupancy (VASO) data were acquired at submillimeter resolution and averaged across cortical laminae. RSFA from the primary motor cortex was, thus, compared to the amplitude of hypercapnia-induced signal changes (tSDhc ) and with the M factor of the Davis model on a laminar level. High linear correlations were observed for RSFA and tSDhc ( R2 = 0.92 ± 0.06) and somewhat reduced for RSFA and M ( R2 = 0.62 ± 0.19). Laminar profiles of RSFA-normalized BOLD signal changes yielded good agreement with corresponding VASO profiles. Overall, this suggests that RSFA contains strong vascular components and is also modulated by baseline quantities contained in the M factor. We conclude that RSFA may replace the scaling factor tSDhc for normalizing the laminar BOLD response.

Modeling radio-frequency energy-induced heating due to the presence of transcranial electric stimulation setup at 3T.

PURPOSE: The purpose of the present study was to develop a numerical workflow for simulating temperature increase in a high-resolution human head and torso model positioned in a whole-body magnetic resonance imaging (MRI) radio-frequency (RF) coil in the presence of a transcranial electric stimulation (tES) setup. METHODS: A customized human head and torso model was developed from medical image data. Power deposition and temperature rise (ΔT) were evaluated with the model positioned in a whole-body birdcage RF coil in the presence of a tES setup. Multiphysics modeling at 3T (123.2 MHz) on unstructured meshes was based on RF circuit, 3D electromagnetic, and thermal co-simulations. ΔT was obtained for (1) a set of electrical and thermal properties assigned to the scalp region, (2) a set of electrical properties of the gel used to ensure proper electrical contact between the tES electrodes and the scalp, (3) a set of electrical conductivity values of skin tissue, (4) four gel patch shapes, and (5) three electrode shapes. RESULTS: Significant dependence of power deposition and ΔT on the skin's electrical properties and electrode and gel patch geometries was observed. Differences in maximum ΔT (> 100%) and its location were observed when comparing the results from a model using realistic human tissue properties and one with an external container made of acrylic material. The electrical and thermal properties of the phantom container material also significantly (> 250%) impacted the ΔT results. CONCLUSION: Simulation results predicted that the electrode and gel geometries, skin electrical conductivity, and position of the temperature sensors have a significant impact on the estimated temperature rise. Therefore, these factors must be considered for reliable assessment of ΔT in subjects undergoing an MRI examination in the presence of a tES setup.

Dual regression physiological modeling of resting-state EPI power spectra: Effects of healthy aging.

Aging and disease-related changes in the arteriovasculature have been linked to elevated levels of cardiac cycle-induced pulsatility in the cerebral microcirculation. Functional magnetic resonance imaging (fMRI), acquired fast enough to unalias the cardiac frequency contributions, can be used to study these physiological signals in the brain. Here, we propose an iterative dual regression analysis in the frequency domain to model single voxel power spectra of echo planar imaging (EPI) data using external recordings of the cardiac and respiratory cycles as input. We further show that a data-driven variant, without external physiological traces, produces comparable results. We use this framework to map and quantify cardiac and respiratory contributions in healthy aging. We found a significant increase in the spatial extent of cardiac modulated white matter voxels with age, whereas the overall strength of cardiac-related EPI power did not show an age effect.

Non-BOLD contrast for laminar fMRI in humans: CBF, CBV, and CMRO2.

Functional magnetic resonance imaging (fMRI) using the blood oxygenation level-dependent (BOLD) contrast indirectly probes neuronal activity changes via evoked cerebral blood flow (CBF), cerebral blood volume (CBV) and cerebral metabolic rate of oxygen (CMRO2) changes. The gradient-echo BOLD signal is mostly sensitive to ascending veins in the tissue and to pial veins. Thereby, the achievable spatial specificity to neuronal activation is limited. Furthermore, the non-linear interaction of CBF, CBV and CMRO2 can hamper quantitative interpretations of the BOLD signal across cortical depths with different baseline physiology. Measuring CBF, CBV or CMRO2 directly on a depth-dependent level has the potential to overcome these limitations. Here, we review these candidates of physiologically well-defined contrasts with the particular focus on arterial spin labeling (ASL), vascular space occupancy (VASO) and calibrated fMRI. These methods are reviewed with respect to their fMRI sequence parameter space and the applicability for neuroscientific studies in humans. We show representative results of depth-dependent 'non-BOLD-fMRI' in humans and their spatiotemporal characteristics. We conclude that non-BOLD methods are promising alternatives compared to conventional fMRI as they can provide improved spatial specificity, quantifiability and, hence, physiological interpretability as a function of cortical depth. At submillimeter resolution with inherently low signal-to-noise ratio (SNR), however, their use is still challenging. Nevertheless, we believe that 'non-BOLD-fMRI' is a useful alternative for depth-dependent investigations, by providing valuable insights into neurovascular coupling models that facilitate the interpretability of fMRI for neuroscientific applications.

A new approach to Z-spectrum acquisition: prospective baseline enhancement (PROBE) for CEST/Nuclear Overhauser Effect.

PURPOSE: To develop a prospective baseline enhancement that compensates for intermingled background effects in Z-spectra to achieve sensitivity enhancement of peaks related to CEST and nuclear Overhauser effect. METHODS: An MRI sequence-specific compensation of background effects is achieved through variation of the pulsed saturation power, ω1,max , with the chemical shift, δ . After a "scout acquisition" of a standard Z-spectrum, the background is modeled through an appropriate spin system. Subsequently, an optimization procedure yields ω1,max(δ) values that compensate for background contributions yielding a flat baseline. Contributions from metabolites not considered in the optimization procedure are enhanced as distinct perturbations to the baseline. For experimental verification, mapping of the lactate concentration in the presence of cross-linked bovine serum albumin was performed in phantoms at 7 T. As proof of concept, explorative experiments were performed in healthy human subjects at 3 T. RESULTS: Nuisance contributions from direct water saturation, macromolecular magnetization transfer, and exchanging background protons were successfully removed from the Z-spectrum in phantoms and in brain tissue. The lactate methyl, methine, and hydroxyl peaks were readily observable in vitro. The peak areas correlated linearly with known concentrations. Improvement of the detection limit was achieved by a sparse distribution of saturation frequencies, allowing for more efficient signal averaging. CONCLUSION: An optimization framework for high-resolution metabolite mapping by means of CEST/nuclear Overhauser effect was developed. It offers full flexibility to select spin-pool moieties, whose influence on the Z-spectrum will be compensated. Deviations from this background model will provide a contrast at the respective offset frequencies.

Influence of the extracellular matrix on water mobility in subcortical gray matter.

PURPOSE: Water mobility in tissues is related to the microstructure that modulates diffusion and spin relaxation. Previous work has shown that the extracellular matrix (ECM) impacts water diffusion in cartilage. To investigate if similar contributions to image contrast exist for brain, which is characterized by a substantially lower ECM content, diffusion and relaxation were studied in fixed samples from goat and human thalamus before and after enzymatic digestion of ECM compounds. Selected experiments in human corpus callosum were included for comparing subcortical gray matter and white matter. METHODS: Digestion of matrix components was achieved by treatment with hyaluronidase. Nonlocalized pulsed field gradient measurements were performed with b values between 0.6 and 18,000 s/mm2 at 3T and temperatures between 0°C and 20°C, in addition to T1 and T2 relaxation measurements. The data were fitted to multiexponential models to account for different water compartments. After the measurements, the samples were sliced and stained for ECM-sensitive markers to verify efficient digestion. RESULTS: Microstructural alterations associated with hyaluronan digestion did not lead to measurable effects on water diffusion or T 2 . However, T1 of the main relaxographic component, attributed to intra-/extracellular water, decreased by 7%. CONCLUSION: Investigations with very strong gradients did not reveal a detectable effect on water diffusion or T 2 after hyaluronan removal, indicating that the brain ECM content is too low to produce a detectable effect. The subtle alteration of T1 upon hyaluronidase treatment might reflect a modulation of intercompartmental water exchange properties.

Semi-automated generation of individual computational models of the human head and torso from MR images.

PURPOSE: Simulating the interaction of the human body with electromagnetic fields is an active field of research. Individualized models are increasingly being used, as anatomical differences affect the simulation results. We introduce a processing pipeline for creating individual surface-based models of the human head and torso for application in simulation software based on unstructured grids. The pipeline is designed for easy applicability and is publicly released on figshare. METHODS: The pipeline covers image acquisition, segmentation, generation of segmentation masks, and surface mesh generation of the single, external boundary of each structure of interest. Two gradient-echo sequences are used for image acquisition. Structures of the head and body are segmented using several atlas-based approaches. They consist of bone/skull, subarachnoid cerebrospinal fluid, gray matter, white matter, spinal cord, lungs, the sinuses of the skull, and a combined class of all other structures including skin. After minor manual preparation, segmentation images are processed to segmentation masks, which are binarized images per segmented structure free of misclassified voxels and without an internal boundary. The proposed workflow is applied to 2 healthy subjects. RESULTS: Individual differences of the subjects are well represented. The models are proven to be suitable for simulation of the RF electromagnetic field distribution. CONCLUSION: Image segmentation, creation of segmentation masks, and surface mesh generation are highly automated. Manual interventions remain for preparing the segmentation images prior to segmentation mask generation. The generated surfaces exhibit a single boundary per structure and are suitable inputs for simulation software.