Ultra-high Field Magnetic Resonance Imaging Research Articles

Characterization of pulsations in the brain and cerebrospinal fluid using ultra-high field magnetic resonance imaging

The development of innovative non-invasive neuroimaging methods and biomarkers is critical for studying brain disease. Imaging of cerebrospinal fluid (CSF) pulsatility may inform the brain fluid dynamics involved in clearance of cerebral metabolic waste. In this work, we developed a methodology to characterize the frequency and spatial localization of whole brain CSF pulsations in humans. Using 7 Tesla (T) human magnetic resonance imaging (MRI) and ultrafast echo-planar imaging (EPI), in-vivo images were obtained to capture pulsations of the CSF signal. Physiological data were simultaneously collected and compared with the 7 T MR data. The primary components of signal pulsations were identified using spectral analysis, with the most evident frequency bands identified around 0.3, 1.2, and 2.4 Hz. These pulsations were mapped spatially and temporally onto the MR image domain and temporally onto the physiological measures of electrocardiogram and respiration. We identified peaks in CSF pulsations that were distinct from peaks in grey matter and white matter regions. This methodology may provide novel in vivo biomarkers of disrupted brain fluid dynamics.

Signal-to-noise ratio versus field strength for small surface coils.

The increasing signal-to-noise ratio (SNR) is the main reason to use ultrahigh field MRI. Here, we investigate the dependence of the SNR on the magnetic field strength, especially for small animal applications, where small surface coils are used and coil noise cannot be ignored. Measurements were performed at five field strengths from 3 to 14.1 T, using 2.2-cm surface coils with an identical coil design for transmit and receive on two water samples with and without salt. SNR was measured in a series of spoiled gradient echo images with varying flip angle and corrected for saturation based on a series of flip angle and T1 measurements. Furthermore, the noise figure of the receive chain was determined and eliminated to remove instrument dependence. Finally, the coil sensitivity was determined based on the principle of reciprocity to obtain a measure for ultimate SNR. Before coil sensitivity correction, the SNR increase in nonconductive samples is highly supralinear with B0 1.6-2.7, depending on distance to the coil, while in the conductive sample, the growth is smaller, being around linear close to the surface coil and increasing up to a B0 2.0 dependence when moving away from the coil. After sensitivity correction, the SNR increase is independent of loading with B0 2.1. This study confirms the supralinear increase of SNR with increasing field strengths. Compared with most human measurements with larger coil sizes, smaller surface coils, as mainly used in animal studies, have a higher contribution of coil noise and thus a different behavior of SNR at high fields.

Anatomical and volumetric description of the guiana dolphin (Sotalia guianensis) brain from an ultra-high-field magnetic resonance imaging.

The Guiana dolphin (Sotalia guianensis) is a common species along Central and South American coastal waters. Although much effort has been made to understand its behavioral ecology and evolution, very little is known about its brain. The use of ultra-high field MRI in anatomical descriptions of cetacean brains is a very promising approach that is still uncommon. In this study, we present for the first time a full anatomical description of the Guiana dolphin's brain based on high-resolution ultra-high-field magnetic resonance imaging, providing an exceptional level of brain anatomical details, and enriching our understanding of the species. Brain structures were labeled and volumetric measurements were delineated for many distinguishable structures, including the gray matter and white matter of the cerebral cortex, amygdala, hippocampus, superior and inferior colliculi, thalamus, corpus callosum, ventricles, brainstem and cerebellum. Additionally, we provide the surface anatomy of the Guiana dolphin brain, including the labeling of main sulci and gyri as well as the calculation of its gyrification index. These neuroanatomical data, absent from the literature to date, will help disentangle the history behind cetacean brain evolution and consequently, mammalian evolution, representing a significant new source for future comparative studies.

A Metamaterial-like Structure Design Using Non-uniformly Distributed Dielectric and Conducting Strips to Boost the RF Field Distribution in 7 T MRI.

Metamaterial-based designs in ultra-high field (≥7 T) MRI have the promise of increasing the local magnetic resonance imaging (MRI) signal and potentially even the global efficiency of both the radiofrequency (RF) transmit and receive resonators. A recently proposed metamaterial-like structure-comprised of a high-permittivity dielectric material and a set of evenly distributed copper strips-indeed resulted in a local increase in RF transmission. Here, we demonstrate that non-uniform designs of this metamaterial-like structure can be used to boost the ultimate RF field distribution. A non-uniform dielectric distribution can yield longer electric dipoles, thus extending the RF transmit field coverage. A non-uniform distribution of conducting strips enables the tailoring of the local electric field hot spots, where a concave distribution resulted in lower power deposition. Simulations of the brain and calf regions using our new metamaterial-like design, which combines non-uniform distributions of both the dielectric and conducting strips, revealed a 1.4-fold increase in the RF field coverage compared to the uniform distribution, and a 1.5-2-fold increase in the transmit efficiency compared to the standard surface-coil.

In vivo enhancement of calf MRI at 7 T via optimized flexible metasurfaces.

Ultrahigh field (≥7 T) MRI is at the cutting edge of medical imaging, enabling enhanced spatial and spectral resolution as well as enhanced susceptibility contrast. However, transmit ( ) field inhomogeneity due to standing wave effects caused by the shortened RF wavelengths at 7 T is still a challenge to overcome. Novel hardware methods such as dielectric pads have been shown to improve the field inhomogeneity but are currently limited in their corrective effect by the range of high-permittivity materials available and have a fixed shelf life. In this work, an optimized metasurface design is presented that demonstrates in vivo enhancement of the field. A prototype metasurface was optimized by an empirical capacitor sweep and by varying the period size. Phantom temperature experiments were performed to evaluate potential metasurface heating effects during scanning. Lastly, in vivo gradient echo images and maps were acquired on five healthy subjects on a 7 T system. Dielectric pads were also used as a comparison throughout the work as a standard comparison. The metasurfaces presented here enhanced the average relative SNR of the gradient echo images by a factor of 2.26 compared to the dielectric pads factor of 1.61. Average values reflected a similar enhancement of 27.6% with the metasurfaces present versus 8.9% with the dielectric pads. The results demonstrate that metasurfaces provide superior performance to dielectric padding as shown by maps reflecting their direct effects and resulting enhancements in image SNR at 7 T.

Application of glutamate weighted CEST in brain imaging of nicotine dependent participants in vivo at 7T.

With nicotine dependence being a significant healthcare issue worldwide there is a growing interest in developing novel therapies and diagnostic aids to assist in treating nicotine addiction. Glutamate (Glu) plays an important role in cognitive function regulation in a wide range of conditions including traumatic brain injury, aging, and addiction. Chemical exchange saturation transfer (CEST) imaging via ultra-high field MRI can image the exchange of certain saturated labile protons with the surrounding bulk water pool, making the technique a novel tool to investigate glutamate in the context of addiction. The aim of this work was to apply glutamate weighted CEST (GluCEST) imaging to study the dorsal anterior cingulate cortex (dACC) in a small population of smokers and non-smokers to determine its effectiveness as a biomarker of nicotine use. 2D GluCEST images were acquired on 20 healthy participants: 10 smokers (ages 29-50) and 10 non-smokers (ages 25-69), using a 7T MRI system. T1-weighted images were used to segment the GluCEST images into white and gray matter tissue and further into seven gray matter regions. Wilcoxon rank-sum tests were performed, comparing mean GluCEST contrast between smokers and non-smokers across brain regions. GluCEST levels were similar between smokers and non-smokers; however, there was a moderate negative age dependence (R2 = 0.531) in smokers within the cingulate gyrus. Feasibility of GluCEST imaging was demonstrated for in vivo investigation of smokers and non-smokers to assess glutamate contrast differences as a potential biomarker with a moderate negative age correlation in the cingulate gyrus suggesting reward network involvement.

MP2RAGE vs. MPRAGE surface-based morphometry in focal epilepsy.

In drug-resistant focal epilepsy, detecting epileptogenic lesions using MRI poses a critical diagnostic challenge. Here, we assessed the utility of MP2RAGE-a T1-weighted sequence with self-bias correcting properties commonly utilized in ultra-high field MRI-for the detection of epileptogenic lesions using a surface-based morphometry pipeline based on FreeSurfer, and compared it to the common approach using T1w MPRAGE, both at 3T. We included data from 32 patients with focal epilepsy (5 MRI-positive, 27 MRI-negative with lobar seizure onset hypotheses) and 94 healthy controls from two epilepsy centres. Surface-based morphological measures and intensities were extracted and evaluated in univariate GLM analyses as well as multivariate unsupervised 'novelty detection' machine learning procedures. The resulting prediction maps were analyzed over a range of possible thresholds using alternative free-response receiver operating characteristic (AFROC) methodology with respect to the concordance with predefined lesion labels or hypotheses on epileptogenic zone location. We found that MP2RAGE performs at least comparable to MPRAGE and that especially analysis of MP2RAGE image intensities may provide additional diagnostic information. Secondly, we demonstrate that unsupervised novelty-detection machine learning approaches may be useful for the detection of epileptogenic lesions (maximum AFROC AUC 0.58) when there is only a limited lesional training set available. Third, we propose a statistical method of assessing lesion localization performance in MRI-negative patients with lobar hypotheses of the epileptogenic zone based on simulation of a random guessing process as null hypothesis. Based on our findings, it appears worthwhile to study similar surface-based morphometry approaches in ultra-high field MRI (≥ 7 T).

Cortical thickness of the posterior cingulate cortex is associated with the ketamine-induced altered sense of self: An ultra-high field MRI study

Subanesthetic doses of ketamine induce an antidepressant effect within hours in individuals with treatment-resistant depression while it furthermore induces immediate but transient psychotomimetic effects. Among these psychotomimetic effects, an altered sense of self has specifically been associated with the antidepressant response to ketamine as well as psychedelics. However, there is plenty of variation in the extent of the drug-induced altered sense of self experience that might be explained by differences in basal morphological characteristics, such as cortical thickness. Regions that have been previously associated with a psychedelics-induced sense of self and with ketamine's mechanism of action, are the posterior cingulate cortex (PCC) and the pregenual anterior cingulate cortex (pgACC).In this randomized, placebo-controlled, double-blind cross-over magnetic resonance imaging study, thirty-five healthy male participants (mean age ± standard deviation (SD) = 25.1 ± 4.2 years) were scanned at 7 T. We investigated whether the cortical thickness of two DMN regions, the PCC and the pgACC, are associated with disembodiment and experience of unity scores, which were used to index the ketamine-induced altered sense of self.We observed a negative correlation between the PCC cortical thickness and the disembodiment scores (R = −0.54, p < 0.001). In contrast, no significant association was found between the pgACC cortical thickness and the ketamine-induced altered sense of self. In the context of the existing literature, our findings highlight the importance of the PCC as a structure involved in the mechanism of ketamine-induced altered sense of self that seems to be shared with different antidepressant agents with psychotomimetic effects operating on different classes of transmitter systems.

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

Hippocampal subfields and thalamic nuclei associations with clinical outcomes in multiple sclerosis: An ultrahigh field MRI study

BackgroundPrevious studies have shown that thalamic and hippocampal neurodegeneration is associated with clinical decline in Multiple Sclerosis (MS). However, contributions of the specific thalamic nuclei and hippocampal subfields require further examination. ObjectiveUsing 7 Tesla (7T) magnetic resonance imaging (MRI), we investigated the cross-sectional associations between functionally grouped thalamic nuclei and hippocampal subfields volumes and T1 relaxation times (T1-RT) and subsequent clinical outcomes in MS. MethodsHigh-resolution T1-weighted and T2-weighted images were acquired at 7T (n=31), preprocessed, and segmented using the Thalamus Optimized Multi Atlas Segmentation (THOMAS, for thalamic nuclei) and the Automatic Segmentation of Hippocampal Subfields (ASHS, for hippocampal subfields) packages. We calculated Pearson correlations between hippocampal subfields and thalamic nuclei volumes and T1-RT and subsequent multi-modal rater-determined and patient-reported clinical outcomes (∼2.5 years after imaging acquisition), correcting for confounders and multiple tests. ResultsSmaller volume bilaterally in the anterior thalamus region correlated with worse performance in gait function, as measured by the Patient Determined Disease Steps (PDDS). Additionally, larger volume in most functional groups of thalamic nuclei correlated with better visual information processing and cognitive function, as measured by the Symbol Digit Modalities Test (SDMT). In bilateral medial and left posterior thalamic regions, there was an inverse association between volumes and T1-RT, potentially indicating higher tissue degeneration in these regions. We also observed marginal associations between the right hippocampal subfields (both volumes and T1-RT) and subsequent clinical outcomes, though they did not survive correction for multiple testing. ConclusionUltrahigh field MRI identified markers of structural damage in the thalamic nuclei associated with subsequently worse clinical outcomes in individuals with MS. Longitudinal studies will enable better understanding of the role of microstructural integrity in these brain regions in influencing MS outcomes.

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.

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

AbstractUltra‐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 (&gt;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.

Effect of 14.1T MRI on Mercury Amalgam: A Study by ICP-MS and XRD

Aim: The aim of this study was to evaluate the effect of electromagnetic effects of magnetic resonance imaging (MRI) on the release of mercury (Hg) and on the possible amalgam phase change in amalgam with 14.1T MRI. Material and methods: 60 amalgam discs with 4 mm diameter and 4 mm height were prepared. 30 were selected as the control and 30 as MRI group. They were placed in the Fusayama-Meyer solution. MRI group were exposed to 14.1T ultra-high-field magnetic resonance imaging (UHF-MRI) system (EPFL, Lausanne, Switzerland). 2, 12 and 24 hours after MRI, all discs were removed from the solutions. Inductively coupled plasma-mass spectroscopy (ICP-MS) analysis was performed to the solutions. X-ray diffractometry (XRD) was performed to amalgam discs. Differences and interactions between groups were evaluated by two-way ANOVA. Results: The concentration of Hg released from the amalgams to the solution in the MRI group was significantly higher than the control group (p=0,026; F=5,253). The peak intensity of the amalgam in the MRI group obtained by XRD was significantly lower than the control group (p = 0.000). Conclusion: UHF-MRI increases the release of Hg in the amalgam due to the strength of the magnetic field and appears to have a debilitating effect on the crystal structure of the amalgam within the period of exposure to the magnetic field.

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.

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.

Disparities in Research Participation within a Multi‐Racial SARS‐CoV‐2 Cohort for Evaluation of Ultrahigh Field (7T) MRI and Clinical Precursors of Alzheimer’s Disease and Related Dementias

AbstractBackgroundThe COVID‐19 pandemic has disproportionately affected ethno‐racial minority populations and people with greater social deprivation. It is unknown whether such disparities influence research participation for investigations of long‐term neuro‐cognitive effects of SARS‐CoV‐2 infection.MethodAcross 3 US and 1 UK sites, we are enrolling a multi‐racial cohort of SARS‐CoV‐2 infected individuals and age, sex, race‐matched non‐infected controls. Utilizing harmonized protocols for cognitive assessments and 7‐Tesla MRI, we aim to provide ultra‐high‐field data on natural history of COVID‐19 driven microstructural and microvascular cerebral changes and associated cognitive trajectories. We will also compare the imaging markers to those observed in an existing cohort of early onset Alzheimer’s Disease and Related Dementias (ADRD). We analyzed screening and enrollment data to determine potential age, sex, race, ethnicity, and social deprivation disparities in research participation. We derived address‐based Area Deprivation Index (ADI) (scale 1 ‐10), with higher ADI indicating greater deprivation. Logistic regression models were fit to evaluate associates of non‐response and refusal. Odds Ratios (OR) and 95% confidence intervals (CI) are reported.ResultOver a 11‐month period, at a single US site, a total of 1,046 SARS‐CoV‐2 infected people and their controls were contacted, and 379 (36.2%) responded. In univariable analyses, non‐response was associated with younger age, male sex, non‐White race, and higher ADI (Table 1). In the fully adjusted model, non‐White race was independently associated with higher likelihood of non‐response [OR (CI) for Black vs. White: 1.49 (1.04, 2.12) and for Asian vs. White: 1.88 (1.28, 2.76)]., Independent of race, higher ADI was also associated with likelihood of non‐response (Table 2 and Figure 1). Among the responders, 228 (60.2%) refused. Although, no socio‐demographic factors were significantly associated with likelihood of refusal, the point estimates in the fully adjusted model suggest potential racial disparities in providing consent (Tables 1 and 2). Aggregated data from all sites will be presented.ConclusionIt is imperative to recognize and mitigate persistent disparities in the COVID‐19 pandemic, particularly pertaining to participation in long‐COVID research. Mechanisms of such persistent disparities need to be studied in context of cultures, beliefs, access, and clinical factors.

Evaluation of coaxial dipole antennas as transceiver elements of human head array for ultra-high field MRI at 9.4T.

The aim of this work is to evaluate a new eight-channel transceiver (TxRx) coaxial dipole array for imaging of the human head at 9.4T developed to improve specific absorption rate (SAR) performance, and provide for a more compact and robust alternative to the state-of-the art dipole arrays. First, the geometry of a single coaxial element was optimized to minimize peak SAR and sensitivity to the load variation. Next, a multi-tissue voxel model was used to numerically simulate a TxRx array coil that consisted of eight coaxial dipoles with the optimal configuration. Finally, we compared the developed array to other human head dipole arrays. Results of numerical simulations were verified on a bench and in the scanner including in vivo measurements on a healthy volunteer. The developed eight-element coaxial dipole TxRx array coil showed up to 1.1times higher SAR-efficiency than a similar in geometry folded-end and fractionated dipole array while maintaining whole brain coverage and low sensitivity of the resonance frequency to variation in the head size. As a proof of concept, we developed and constructed a prototype of a 9.4T (400 MHz) human head array consisting of eight TxRx coaxial dipoles. The developed array improved SAR-efficiency and provided for a more compact and robust alternative to the folded-end dipole design. To the best of our knowledge, this is the first example of using coaxial dipoles for human head MRI at ultra-high field.

Brainstem anatomy with 7-T MRI: in vivo assessment and ex vivo comparison

Background The brainstem contains grey matter nuclei and white matter tracts to be identified in clinical practice. The small size and the low contrast among them make their in vivo visualisation challenging using conventional magnetic resonance imaging (MRI) sequences at high magnetic field strengths. Combining higher spatial resolution, signal- and contrast-to-noise ratio and sensitivity to magnetic susceptibility (χ), susceptibility-weighted 7-T imaging could improve the assessment of brainstem anatomy.MethodsWe acquired high-resolution 7-T MRI of the brainstem in a 46-year-old female healthy volunteer (using a three-dimensional multi-echo gradient-recalled-echo sequence; spatial resolution 0.3 × 0.3 × 1.2 mm3) and in a brainstem sample from a 48-year-old female body donor that was sectioned and stained. Images were visually assessed; nuclei and tracts were labelled and named according to the official nomenclature.ResultsThis in vivo imaging revealed structures usually evaluated through light microscopy, such as the accessory olivary nuclei, oculomotor nucleus and the medial longitudinal fasciculus. Some fibre tracts, such as the medial lemniscus, were visible for most of their course. Overall, in in vivo acquisitions, χ and frequency maps performed better than T2*-weighted imaging and allowed for the evaluation of a greater number of anatomical structures. All the structures identified in vivo were confirmed by the ex vivo imaging and histology.ConclusionsThe use of multi-echo GRE sequences at 7 T allowed the visualisation of brainstem structures that are not visible in detail at conventional magnetic field and opens new perspectives in the diagnostic and therapeutical approach to brain disorders.Relevance statementIn vivo MR imaging at UHF provides detailed anatomy of CNS substructures comparable to that obtained with histology. Anatomical details are fundamentals for diagnostic purposes but also to plan a direct targeting for a minimally invasive brain stimulation or ablation.Key points• The in vivo brainstem anatomy was explored with ultrahigh field MRI (7 T).• In vivo T2*-weighted magnitude, χ, and frequency images revealed many brainstem structures.• Ex vivo imaging and histology confirmed all the structures identified in vivo.• χ and frequency imaging revealed more brainstem structures than magnitude imaging.Graphical

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.

34 Verbal Memory as a Language Function: Phonological Processing Contributes to Word List Recall in Persons with Multiple Sclerosis

Objective:Verbal memory deficits are present in multiple sclerosis (MS), but neither inflammatory T2 lesion volume nor cerebral atrophy (generalized or localized hippocampal atrophy) fully explain disease-related verbal memory changes. Importantly, the hippocampus does not function in a vacuum; memory encoding and retrieval requires interactions between the hippocampus and cortical areas where information is processed and represented. Indeed, we have previously shown that lexical access speed (a language function assessed by rapid automatized naming) independently predicted delayed recall of verbal information (word list) for persons with MS, even when controlling for total learning. Informed by this work and recent ultra high field (7.0 Tesla) MRI research reporting high cortical lesion count in regions associated with phonological processing (e.g., plenum temporale, superior temporal gyrus), we assessed whether phonological processing independently explains verbal memory deficits in persons with MS.Participants and Methods:Analyses were performed on a clinical sample of persons with MS aged 18 to 59 years (n=60: 49 relapsing, 11 progressive). Word-list memory was assessed by the Hopkins Verbal Learning Test, Revised (HVLT-R), which yielded scores for Total Learning (TL) and Delayed Recall (DR). Phonological processing was assessed with WIAT-4 Phonemic Proficiency. WIAT-4 Sentence Repetition was utilized as a non-phonological language control task, and WIAT-4 Word Reading was administered to control for premorbid verbal ability. CANTAB Paired Associate Learning served as a nonverbal memory comparison. Performance on tasks was standardized using published age-adjusted norms. Primary analyses used partial correlations to assess relationships between Phonemic Proficiency and (a) HVLT-R TL and DR controlling for WIAT-4 Word Reading, and (b) HVLT-R DR controlling for WIAT-4 Word Reading and HVLT-R TL. To assess specificity to phonological processing, the same partial correlations assessed relationships between Sentence Repetition and HVLT-R variables, and between Phonemic Proficiency and nonverbal memory (CANTAB PAL).Results:When controlling for premorbid verbal ability, Phonemic Proficiency performance accounted for 7.8% of the variance in HVLT-R TL (rpartial=0.28, p=0.031) and 16% of the variance in HVLT-R DR (rpartial=0.40, p=0.002). Moreover, when additionally controlling for HVLT-R TL, Phonemic Proficiency still accounted for 10% of the variance in HVLT-R DR (r partial— 0.32, p=0.016). Showing specificity to phonological processing ability, performance on Sentence Repetition was not significantly related to HVLT-R DR when controlling for premorbid verbal ability (WIAT-4 Word Reading) and HVLT-R TL (rpartial=0.09, p=0.510). Showing specificity to verbal memory, neither Phonemic Proficiency nor Sentence Repetition performance were reliably related to CANTAB PAL for any variance in performance in nonverbal memory (Ps&gt;0.9).Conclusions:Results suggest that language ability, specifically phonological processing, contributes to delayed recall of word lists independent of premorbid verbal ability and initial total learning scores in persons with MS. These findings demonstrate contributions of language ability to verbal memory and highlight the need for further research into language ability changes in persons with MS. This may have implications for verbal memory rehabilitation in MS.