Ultra-high Field Magnetic Resonance Research Articles

P31 magnetic resonance spectroscopy: principles and applications

Phosphorus-31 magnetic resonance spectroscopy (P31-MRS) is a non-invasive imaging modality that furnishes pivotal insights into metabolic processes and the phosphoenegertic status within biological entities. Recent advancements in Magnetic Resonance technology, notably within ultra-high field magnetic resonance systems (ultra-high field MRI), have elevated the perceived suitability of P31-MRS due to its enhanced capabilities. Despite these advancements, comprehensive documentation regarding the P31-MRS technique remains relatively obscure and is not widely disseminated among radiologists, radiographers, and clinicians. Therefore, this article endeavors to expound upon the fundamental technical intricacies and applications of the P31-MRS technique. Key words: P31-MRS; PCr; ATP; intracellular pH; ultra-high field MRI

Decrease of 7T MR short-term effects with repeated exposure

PurposeAlthough participants in 7 T magnetic resonance (MR) studies tolerate ultra-high field (UHF) well, subjectively experienced short-term effects, such as dizziness, inconsistent movement, nausea, or metallic taste, are reported. Evidence on subjectively experienced short-term effects in multiple exposures to UHF MR is scarce. The purpose of this study is to investigated experience of short-term effects, and occurrence of motion in healthy subjects exposed to seven weekly 7 T MR examinations.MethodsA questionnaire on short-term effects was completed by participants in an fMRI motor skill study. Seven UHF MR examinations were conducted over 7 weeks (exposure number: 1 to 7). Changes of experienced short-term effects were analyzed. Motion in fMRI images was quantified.ResultsThe questionnaire was completed 360 times by 67 participants after one to seven 7T MR examinations. Logistic mixed model analysis showed a significant association between dizziness, inconsistent movement, nausea, and headache and the examination numbers (p<0.03). Exposure to repeated examinations had no significant effect on peripheral nerve stimulation (PNS) or motion of the subjects. The overall experience of a 7T examination improved significantly (p<0.001) with increasing examination numbers.ConclusionDuring multiple 7T examinations, subjects adapt to the strong static field. The short-term effects dizziness, inconsistent movement, nausea, and headache decrease over time as the MR sessions continue and experienced comfort increases. There was no significant difference in motion during the multiple fMRI examinations.

Ligand-Mediated Magnetism-Conversion Nanoprobes for Activatable Ultra-High Field Magnetic Resonance Imaging.

Ultra-high field (UHF) magnetic resonance imaging (MRI) has emerged as a focal point of interest in the field of cancer diagnosis. Despite the ability of current paramagnetic or superparamagnetic smart MRI contrast agents to selectively enhance tumor signals in low-field MRI, their effectiveness at UHF remains inadequate due to inherent magnetism. Here, we report a ligand-mediated magnetism-conversion nanoprobe (MCNP) composed of 3-mercaptopropionic acid ligand-coated silver-gadolinium bimetallic nanoparticles. The MCNP exhibits a pH-dependent magnetism conversion from ferromagnetism to diamagnetism, facilitating tunable nanomagnetism for pH-activatable UHF MRI. Under neutral pH, the thiolate (-S- ) ligands lead to short τ'm and increased magnetization of the MCNPs. Conversely, in the acidic tumor microenvironment, the thiolate ligands are protonated and transform into thiol (-SH) ligands, resulting in prolonged τ'm and decreased magnetization of the MCNP, thereby enhancing longitudinal relaxivity (r1) values at UHF MRI. Notably, under a 9 T MRI field, the pH-sensitive changes in Ag-S binding affinity of the MCNP lead to a remarkable (>10-fold) r1 increase in an acidic medium (pH 5.0). In vivo studies demonstrate the capability of MCNPs to amplify MRI signal of hepatic tumors, suggesting their potential as a next-generation UHF-tailored smart MRI contrast agent.

Segmentation and quantification of venous structures and perivascular spaces in the thalamus in epilepsy using 7 Tesla MRI

Background and purposeEpilepsy is a complex neurological disorder affecting 50 million people worldwide. Persistent seizures may correlate with neural network, microstructural, and vascular changes within the thalamus. These thalamic changes may result from seizure activity or broader alterations involving neuronal vasculature and neuroinflammatory processes linked to glymphatic drainage. Improved resolution with Ultra-high field (UHF) magnetic resonance imaging (MRI) may be useful in identifying possible thalamic vascular abnormalities not otherwise detectable at lower field strengths. Materials and methodsWe outline a novel method which leverages UHF neuroimaging for detection and quantification of vessels and perivascular spaces (PVS) within the thalamus in 25 epilepsy patients and 16 controls, to uncover possible underlying imaging biomarkers of epilepsy. In our analysis, we optimize a MATLAB-based Frangi-based detection tool called Perivascular Space Semi-Automated Segmentation (PVSSAS) to detect thalamic PVSs, and additionally use a second Frangi-based segmentation tool method to automate detection of vascular structures in the thalamus. The resulting PVS and vessel masks were used to quantify differences in the number of vessels, PVS, overlaps, and number of PVS overlaps per vessel detected between groups, using a Hessian detection filter linked on an 18-connected network. ResultsWe found significantly more thalamic PVS (p = 0.0307) and a significant increase in the number of thalamic vessels (p = 0.038) in patients compared to controls. ConclusionHere we have developed a novel process which leverages UHF MRI to quantify and detect thalamic vessels and PVS that may provide a potential neuroimaging biomarker of epilepsy. Statement of SignificanceWe use 7T, ultra-high field MRI and employed an innovative combination of semi-automated perivascular space segmentation and automated vessel segmentation to visualize and quantify vessels and perivascular spaces (PVS) within the thalamus, a highly cited region of interest in epilepsy. To our knowledge, this is the first study to semi-automatically visualize and segment PVS in the thalamus and automatically detect thalamic vessels. We uncovered detectable differences in thalamic vasculature and PVS. These findings suggests that increases in the number of thalamic PVS and vessels may be a potential neuroimaging biomarker in epilepsy. This tool may be useful in the detection of subtle vascular changes in other regions of the brain related to epilepsy or can be employed in other neurological conditions.

Increased cortical inhibition following brief motor memory reactivation supports reconsolidation and overnight offline learning gains.

Practicing motor skills stabilizes and strengthens motor memories by repeatedly reactivating and reconsolidating them. The conventional view, by which a repetitive practice is required for substantially improving skill performance, has been recently challenged by behavioral experiments, in which even brief reactivations of the motor memory have led to significant improvements in skill performance. However, the mechanisms which facilitate brief reactivation-induced skill improvements remain elusive. While initial memory consolidation has been repeatedly associated with increased neural excitation and disinhibition, reconsolidation has been shown to involve a poorly understood mixture of both excitatory and inhibitory alterations. Here, we followed a 3-d reactivation-reconsolidation framework to examine whether the excitatory/inhibitory mechanisms which underlie brief reactivation and repetitive practice differ. Healthy volunteers practiced a motor sequence learning task using either brief reactivation or repetitive practice and were assessed using ultrahigh field (7T) magnetic resonance spectroscopy at the primary motor cortex (M1). We found that increased inhibition (GABA concentrations) and decreased excitation/inhibition (glutamate/GABA ratios) immediately following the brief reactivation were associated with overnight offline performance gains. These gains were on par with those exhibited following repetitive practice, where no correlations with inhibitory or excitatory changes were observed. Our findings suggest that brief reactivation and repetitive practice depend on fundamentally different neural mechanisms and that early inhibition-and not excitation-is particularly important in supporting the learning gains exhibited by brief reactivation.

Toward hippocampal volume measures on ultra-high field magnetic resonance imaging: a comprehensive comparison study between deep learning and conventional approaches.

The hippocampus is a complex brain structure that plays an important role in various cognitive aspects such as memory, intelligence, executive function, and path integration. The volume of this highly plastic structure is identified as one of the most important biomarkers of specific neuropsychiatric and neurodegenerative diseases. It has also been extensively investigated in numerous aging studies. However, recent studies on aging show that the performance of conventional approaches in measuring the hippocampal volume is still far from satisfactory, especially in terms of delivering longitudinal measures from ultra-high field magnetic resonance images (MRIs), which can visualize more boundary details. The advancement of deep learning provides an alternative solution to measuring the hippocampal volume. In this work, we comprehensively compared a deep learning pipeline based on nnU-Net with several conventional approaches including Freesurfer, FSL and DARTEL, for automatically delivering hippocampal volumes: (1) Firstly, we evaluated the segmentation accuracy and precision on a public dataset through cross-validation. Results showed that the deep learning pipeline had the lowest mean (L = 1.5%, R = 1.7%) and the lowest standard deviation (L = 5.2%, R = 6.2%) in terms of volume percentage error. (2) Secondly, sub-millimeter MRIs of a group of healthy adults with test-retest 3T and 7T sessions were used to extensively assess the test-retest reliability. Results showed that the deep learning pipeline achieved very high intraclass correlation coefficients (L = 0.990, R = 0.986 for 7T; L = 0.985, R = 0.983 for 3T) and very small volume percentage differences (L = 1.2%, R = 0.9% for 7T; L = 1.3%, R = 1.3% for 3T). (3) Thirdly, a Bayesian linear mixed effect model was constructed with respect to the hippocampal volumes of two healthy adult datasets with longitudinal 7T scans and one disease-related longitudinal dataset. It was found that the deep learning pipeline detected both the subtle and disease-related changes over time with high sensitivity as well as the mild differences across subjects. Comparison results from the aforementioned three aspects showed that the deep learning pipeline significantly outperformed the conventional approaches by large margins. Results also showed that the deep learning pipeline can better accommodate longitudinal analysis purposes.

A hybrid 2D-FDTD/3D-MoM method used for the analysis of MRI RF coils

The design of radiofrequency (RF) coils is crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) systems. To analyze RF coils, various numerical methods, such as finite-difference time-domain (FDTD) and method of moments (MoM), are usually adopted. In this paper, we present a novel hybrid approach that combines a two-dimensional (2D) FDTD with a three-dimensional (3D) MoM to analyze MRI RF problems. In our algorithm, the MoM is utilized for calculating the coil current, and FDTD is assigned for solving the electromagnetic (EM) fields in the imaging region. The hybrid method achieves superior efficiency and acceptable accuracy than using either method individually. To validate the hybrid method, we analyze an ellipse coil loaded with a uniform phantom and a realistic human head model, with the objective of tailoring the magnetic field intensity by adding a multilayer dielectric pad (DP). The results show an improvement in the magnetic field after optimizing the DP configuration. These simulation studies indicate the potential of the new numerical method for the design and analysis of RF systems for ultra-high field applications.

Enhancing the brain MRI at ultra-high field systems using a meta-array structure.

The main advantage of ultra-high field (UHF) magnetic resonance neuroimaging is theincreased signal-to-noise ratio (SNR) compared with lower field strength imaging. However, the wavelength effect associated with UHF MRI results in radiofrequency (RF) inhomogeneity, compromising whole brain coverage for many commercial coils. Approaches to resolving this issue of transmit field inhomogeneity include the design of parallel transmit systems (PTx), RF pulse design, and applying passive RF shimming such as high dielectric materials. However, these methods have some drawbacks such as unstable material parameters of dielectric pads, high-cost, and complexity of PTx systems. Metasurfaces are artificial structures with a unique platform that can control the propagation of the electromagnetic (EM) waves, and they are very promising for engineering EM device. Implementation of meta-arrays enhancing MRI has been explored previously in several studies. The aim of this study was to assess the effect of new meta-array technology on enhancing the brain MRI at 7T. A meta-array based on a hybrid structure consisting of an array of broadside-coupled split-ring resonators and high-permittivity materials was designed to work at the Larmor frequency of a 7 Tesla (7T) MRI scanner. When placed behind the head and neck, this construct improves the SNR in the region of the cerebellum,brainstem and the inferior aspect of the temporal lobes. Numerical electromagnetic simulations were performed to optimize the meta-array design parameters and determine the RF circuit configuration. The resultant transmit-efficiency and signal sensitivity improvements were experimentally analyzed in phantoms followed by healthy volunteers using a 7T whole-body MRI scanner equipped with a standard one-channel transmit, 32-channel receive head coil. Efficacy was evaluated through acquisition with and without the meta-array using two basic sequences: gradient-recalled-echo (GRE) and turbo-spin-echo (TSE). Experimental phantom analysis confirmed two-fold improvement in the transmit efficiency and 1.4-fold improvement in the signal sensitivity in the target region. In vivo GRE and TSE images with the meta-array in place showed enhanced visualization in inferior regions of the brain, especially of the cerebellum, brainstem, and cervical spinal cord. Addition of the meta-array to commonly used MRI coils can enhance SNR to extend the anatomical coverage of the coil and improve overall MRI coil performance. This enhancement in SNR can be leveraged to obtain a higher resolution image over the same time slot or faster acquisition can be achieved with same resolution. Using this technique could improve the performance of existing commercial coils at 7T for whole brain and other applications.

Design optimization of a stepped HTS magnet for electrodynamic suspension train

High-temperature superconducting (HTS) magnets are promising candidates for transportation and power systems, such as the electrodynamic suspension (EDS) train, ultra-high field magnet and magnetic resonance imaging, because of their large current-carrying capacity and low power loss. The critical current depending on magnetic flux density is an essential factor in assessing the application performance of HTS magnets. As usual, the existing HTS magnet is wound with rectangular cross-section, which results in magnetic field concentration inside winding. In this paper, we propose a novel HTS magnet structure with stepped cross-section to alleviate the magnetic field concentration, and resultantly improve the critical current. From this point, this paper aims to design and optimize a stepped HTS magnet with the critical current maximized. Firstly, the structure design of the stepped HTS magnet is performed with a consideration of the application scenario of EDS train. Then, the critical current of the HTS magnet is estimated with a homogenized self-consistent model. Afterwards, an HTS magnet with stepped cross-section is optimized, fabricated and finally tested. The critical current was experimentally measured to verify the simulation results, followed by the electromagnetic investigations of the stepped HTS magnet in the EDS train.

Psilocybin induces acute and persisting alterations in immune status in healthy volunteers: An experimental, placebo-controlled study

Patients characterized by stress-related disorders such as depression display elevated circulating concentrations of pro-inflammatory cytokines and a hyperactive HPA axis. Psychedelics are demonstrating promising results in treatment of such disorders, however the mechanisms of their therapeutic effects are still unknown. To date the evidence of acute and persisting effects of psychedelics on immune functioning, HPA axis activity in response to stress, and associated psychological outcomes is preliminary. To address this, we conducted a placebo-controlled, parallel group design comprising of 60 healthy participants who received either placebo (n = 30) or 0.17 mg/kg psilocybin (n = 30). Blood samples were taken to assess acute and persisting (7 day) changes in immune status. Seven days’ post-administration, participants in each treatment group were further subdivided: 15 underwent a stress induction protocol, and 15 underwent a control protocol. Ultra-high field (7-Tesla) magnetic resonance spectroscopy was used to assess whether acute changes in glutamate or glial activity were associated with changes in immune functioning. Finally, questionnaires assessed persisting self-report changes in mood and social behavior. Psilocybin immediately reduced concentrations of the pro-inflammatory cytokine tumor necrosis factor-α (TNF-α), while other inflammatory markers (interleukin (IL)- 1β, IL-6, and C-reactive protein (CRP)) remained unchanged. Seven days later, TNF-α concentrations returned to baseline, while IL-6 and CRP concentrations were persistently reduced in the psilocybin group. Changes in the immune profile were related to acute neurometabolic activity as acute reductions in TNF-α were linked to lower concentrations of glutamate in the hippocampus. Additionally, the more of a reduction in IL-6 and CRP seven days after psilocybin, the more persisting positive mood and social effects participants reported. Regarding the stress response, after a psychosocial stressor, psilocybin did not significantly alter the stress response. Results are discussed in regards to the psychological and therapeutic effects of psilocybin demonstrated in ongoing patient trials.

Individual Differences in Decision Strategy Relate to Neurochemical Excitability and Cortical Thickness.

The speed-accuracy trade-off (SAT), whereby faster decisions increase the likelihood of an error, reflects a cognitive strategy humans must engage in during the performance of almost all daily tasks. To date, computational modeling has implicated the latent decision variable of response caution (thresholds), the amount of evidence required for a decision to be made, in the SAT. Previous imaging has associated frontal regions, notably the left prefrontal cortex and the presupplementary motor area (pre-SMA), with the setting of such caution levels. In addition, causal brain stimulation studies, using transcranial direct current stimulation (tDCS), have indicated that while both of these regions are involved in the SAT, their role appears to be dissociable. tDCS efficacy to impact decision-making processes has previously been linked with neurochemical concentrations and cortical thickness of stimulated regions. However, to date, it is unknown whether these neurophysiological measures predict individual differences in the SAT, and brain stimulation effects on the SAT. Using ultra-high field (7T) imaging, here we report that instruction-based adjustments in caution are associated with both neurochemical excitability (the balance between GABA+ and glutamate) and cortical thickness across a range of frontal regions in both sexes. In addition, cortical thickness, but not neurochemical concentrations, was associated with the efficacy of left prefrontal and superior medial frontal cortex (SMFC) stimulation to modulate performance. Overall, our findings elucidate key neurophysiological predictors, frontal neural excitation, of individual differences in latent psychological processes and the efficacy of stimulation to modulate these.SIGNIFICANCE STATEMENT The speed-accuracy trade-off (SAT), faster decisions increase the likelihood of an error, reflects a cognitive strategy humans must engage in during most daily tasks. The SAT is often investigated by explicitly instructing participants to prioritize speed or accuracy when responding to stimuli. Using ultra-high field (7T) magnetic resonance imaging (MRI), we found that individual differences in the extent to which participants adjust their decision strategies with instruction related to neurochemical excitability (ratio of GABA+ to glutamate) and cortical thickness in the frontal cortex. Moreover, brain stimulation to the left prefrontal cortex and the superior medial frontal cortex (SMFC) modulated performance, with the efficacy specifically related to cortical thickness. This work sheds new light on the neurophysiological basis of decision strategies and brain stimulation.

Thermal measurements of a muscle-mimicking phantom during ultra-high field magnetic resonance imaging

Abstract At ultra-high field MRI (Bo&gt;7T) it is crucial to predict and control the patient safety. Commonly patient safety is controlled by the power deposited in the tissue (specific absorption rate - SAR). However, temperature distributions do not always correlate directly with SAR distributions, which makes temperature control also a crucial parameter to guarantee patient safety. In this work, temperature changes were accessed by MR thermometry, specifically by the proton resonance frequency shift technique (PRF). A phantom mimicking muscle tissue was used to evaluate the temperature rise caused by the radiofrequency (RF) absorption during 7T MRI, applied through a commercial birdcage head coil. A pulse-sequence protocol was implemented for both, the generation of temperature increase and the MR thermometry. To control the temperature, a digital thermometer was used, and oil tubes were utilized to dismiss the drift effects for PRF. Measurements of the phantom’s dielectric characteristics, i.e. conductivity and permittivity, were in good agreement with the literature values for muscle. Spatio-temporal evaluations showed a temperature increase in time via RF exposure and the feasibility of measuring temperature maps using the PRF shift method. The accuracy of the PRF shift method increased when the drift effects were quantified and dismissed, indicating a PRF reading accuracy differing less than 0.5 °C from the thermometer. Results also validate our heating and temperature imaging protocol. This study is a valuable contribution to the evaluation of heating effects caused by RF absorption and demonstrates potential impact on future thermal investigations, which may use different heating sources, as well validate thermal simulations.

Micron-resolution Imaging of Cortical Bone under 14 T Ultrahigh Magnetic Field.

Compact, mineralized cortical bone tissues are often concealed on magnetic resonance (MR) images. Recent development of MR instruments and pulse techniques has yielded significant advances in acquiring anatomical and physiological information from cortical bone despite its poor 1 H signals. This work demonstrates the first MR research on cortical bones under an ultrahigh magnetic field of 14 T. The 1 H signals of different mammalian species exhibit multi-exponential decays of three characteristic T2 or T2 * values: 0.1-0.5ms, 1-4ms, and 4-8ms. Systematic sample comparisons attribute these T2 /T2 * value ranges to collagen-bound water, pore water, and lipids, respectively. Ultrashort echo time (UTE) imaging under 14 T yielded spatial resolutions of 20-80 microns, which resolves the 3D anatomy of the Haversian canals. The T2 * relaxation characteristics further allow spatial classifications of collagen, pore water and lipids in human specimens. The study achieves a record of the spatial resolution for MR imaging in bone and shows that ultrahigh-field MR has the unique ability to differentiate the soft and organic compartments in bone tissues.

Ultra-high field magnetic resonance imaging of the quadriceps tendon enthesis in healthy subjects.

Although enthesitis is a hallmark of several rheumatologic conditions, current imaging methods are still unable to characterize entheses changes because of the corresponding short transverse relaxation times (T2). A growing number of MR studies have used Ultra-High Field (UHF) MRI in order to assess low-T2 tissues e.g., tendon but never in humans. The purpose of the present study was to assess in vivo the enthesis of the quadriceps tendon in healthy subjects using UHF MRI. Eleven healthy subjects volunteered in an osteoarthritis imaging study. The inclusion criteria were: no knee trauma, Lequesne index = 0, less than 3h of sport activities per week, and Kellgren and Lawrence grade = 0. 3D MR images were acquired at 7T using GRE sequences and a T2* mapping. Regions of interest i.e., trabecular bone, subchondral bone, enthesis, and tendon body were identified, and T2* values were quantified and compared. Quadriceps tendon enthesis was visible as a hyper-intense signal. The largest and the lowest T2* values were quantified in the subchondral bone region and the tendon body respectively. T2* value within subchondral bone was significantly higher than T2* value within the enthesis. T2* in subchondral bone region was significantly higher than the whole tendon body T2*. A T2* gradient was observed along the axis from the enthesis toward the tendon body. It illustrates different water biophysical properties. These results provide normative values which could be used in the field of inflammatory rheumatologic diseases and mechanical disorders affecting the tendon.

Neurochemistry-enriched dynamic causal models of magnetoencephalography, using magnetic resonance spectroscopy

We present a hierarchical empirical Bayesian framework for testing hypotheses about neurotransmitters’ concertation as empirical prior for synaptic physiology using ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography data (MEG). A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of individuals’ neurophysiological observations. At the second level, individuals’ 7T-MRS estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the group-wise evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction (BMR), parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare alternative model evidence of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the subset of synaptic connections that are influenced by individual differences in neurotransmitter levels, as measured by 7T-MRS. We demonstrate the method using resting-state MEG (i.e., task-free recording) and 7T-MRS data from healthy adults. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. Using within-subject split-sampling of the MEG dataset (i.e., validation by means of a held-out dataset), we show that model comparison for hypothesis testing can be highly reliable. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to reveal the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

Convolutional neural network to predict IDH mutation status in glioma from chemical exchange saturation transfer imaging at 7 Tesla.

Noninvasive prediction of isocitrate dehydrogenase (IDH) mutation status in glioma guides surgical strategies and individualized management. We explored the capability on preoperatively identifying IDH status of combining a convolutional neural network (CNN) and a novel imaging modality, ultra-high field 7.0 Tesla (T) chemical exchange saturation transfer (CEST) imaging. We enrolled 84 glioma patients of different tumor grades in this retrospective study. Amide proton transfer CEST and structural Magnetic Resonance (MR) imaging at 7T were performed preoperatively, and the tumor regions are manually segmented, leading to the "annotation" maps that offers the location and shape information of the tumors. The tumor region slices in CEST and T1 images were further cropped out as samples and combined with the annotation maps, which were inputted to a 2D CNN model for generating IDH predictions. Further comparison analysis to radiomics-based prediction methods was performed to demonstrate the crucial role of CNN for predicting IDH based on CEST and T1 images. A fivefold cross-validation was performed on the 84 patients and 4090 slices. We observed a model based on only CEST achieved accuracy of 74.01% ± 1.15%, and the area under the curve (AUC) of 0.8022 ± 0.0147. When using T1 image only, the prediction performances dropped to accuracy of 72.52% ± 1.12% and AUC of 0.7904 ± 0.0214, which indicates no superiority of CEST over T1. However, when we combined CEST and T1 together with the annotation maps, the performances of the CNN model were further boosted to accuracy of 82.94% ± 1.23% and AUC of 0.8868 ± 0.0055, suggesting the importance of a joint analysis of CEST and T1. Finally, using the same inputs, the CNN-based predictions achieved significantly improved performances above those from radiomics-based predictions (logistic regression and support vector machine) by 10% to 20% in all metrics. 7T CEST and structural MRI jointly offer improved sensitivity and specificity of preoperative non-invasive imaging for the diagnosis of IDH mutation status. As the first study of CNN model on imaging acquired at ultra-high field MR, our results could demonstrate the potential of combining ultra-high-field CEST and CNN for facilitating decision-making in clinical practice. However, due to the limited cases and B1 inhomogeneities, the accuracy of this model will be improved in our further study.

BigBrain-MR: a new digital phantom with anatomically-realistic magnetic resonance properties at 100-µm resolution for magnetic resonance methods development

The benefits, opportunities and growing availability of ultra-high field magnetic resonance imaging (MRI) for humans have prompted an expansion in research and development efforts towards increasingly more advanced high-resolution imaging techniques. To maximize their effectiveness, these efforts need to be supported by powerful computational simulation platforms that can adequately reproduce the biophysical characteristics of MRI, with high spatial resolution. In this work, we have sought to address this need by developing a novel digital phantom with realistic anatomical detail up to 100-µm resolution, including multiple MRI properties that affect image generation. This phantom, termed BigBrain-MR, was generated from the publicly available BigBrain histological dataset and lower-resolution in-vivo 7T-MRI data, using a newly-developed image processing framework that allows mapping the general properties of the latter into the fine anatomical scale of the former. Overall, the mapping framework was found to be effective and robust, yielding a diverse range of realistic “in-vivo-like” MRI contrasts and maps at 100-µm resolution. BigBrain-MR was then tested in three imaging applications (motion effects and interpolation, super-resolution imaging, and parallel imaging reconstruction) to investigate its properties, value and validity as a simulation platform. The results consistently showed that BigBrain-MR can closely approximate the behavior of real in-vivo data, more realistically and with more extensive features than a more classic option such as the Shepp-Logan phantom. Its flexibility in simulating different contrast mechanisms and artifacts may also prove valuable for educational applications. BigBrain-MR is therefore deemed a favorable choice to support methodological development and demonstration in brain MRI, and has been made freely available to the community.

A hybrid FDTD/MoM algorithm with a conformal Huygens' equivalent surface for MRI RF coil design and analysis

Accurate design and analysis of radiofrequency (RF) coils are crucial for ultra-high field (UHF) magnetic resonance imaging (MRI) applications. To improve the numerical accuracy of electromagnetic (EM) simulations, we propose a hybrid finite difference time domain (FDTD)/method of moments (MoM) method. Unlike conventional cuboid-like Huygens' equivalent surfaces (HES), we proposed to use a conformal HES to interface the EM data of the FDTD and MoM zone. The shape and size of the conformal surface can be adjusted to fit different RF coil models, thus broadening the application range of the hybrid FDTD/MoM method. Two numerical models: an 8-channel ellipse array, and an 8-channel bent dipole array, are simulated and compared with the conventional HES counterpart. Numerical results demonstrate the capability of the conformal HES method in the analysis of RF coils.

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.

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. 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. 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. 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.

Detailed organisation of the human midbrain periaqueductal grey revealed using ultra-high field magnetic resonance imaging

The midbrain periaqueductal grey (PAG) is a critical region for the mediation of pain-related behavioural responses. Neuronal tract tracing techniques in experimental animal studies have demonstrated that the lateral column of the PAG (lPAG) displays a crude somatotopy, which is thought to be critical for the selection of contextually appropriate behavioural responses, without the need for higher brain input. In addition to the different behavioural responses to cutaneous and muscle pain – active withdrawal versus passive coping – there is evidence that cutaneous pain is processed in the region of the lPAG and muscle pain in the adjacent ventrolateral PAG (vlPAG). Given the fundamental nature of these behavioural responses to cutaneous and muscle pain, these PAG circuits are assumed to have been preserved, though yet to be definitively documented in humans. Using ultra-high field (7-Tesla) functional magnetic resonance imaging we determined the locations of signal intensity changes in the PAG during noxious cutaneous heat stimuli and muscle pain in healthy control participants. Images were processed and blood oxygen level dependant (BOLD) signal changes within the PAG determined. It was observed that noxious cutaneous stimulation of the lip, cheek, and ear evoked maximal increases in BOLD activation in the rostral contralateral PAG, whereas noxious cutaneous stimulation of the thumb and toe evoked increases in the caudal contralateral PAG. Analysis of individual participants demonstrated that these activations were located in the lPAG. Furthermore, we found that deep muscular pain evoked the greatest increases in signal intensity in the vlPAG. These data suggest that the crude somatotopic organization of the PAG may be phyletically preserved between experimental animals and humans, with a body-face delineation capable of producing an appropriate behavioural response based on the location and tissue origin of a noxious stimulus.