A Parametric Study of Radiative Dipole Body Array Coil for 7 Tesla MRI

In this contribution we present numerical and experimental results of a parametric quantitative study of radiative dipole antennas in a phased array configuration for efficient body magnetic resonance imaging at 7T via parallel transmission. For magnetic resonance imaging (MRI) at ultrahigh fields (7T and higher) dipole antennas are commonly used in phased arrays, particularly for body imaging targets. This study reveals the effects of dipole positioning in the array (elevation of dipoles above the subject and inter-dipole spacing) on their mutual coupling, $B_1^{+}$ per $P_{acc}$ and $B_1^{+}$ per maximum local SAR efficiencies as well as the RF-shimming capability. The numerical and experimental results are obtained and compared for a homogeneous phantom as well as for a real human models confirmed by in-vivo experiments

7 T renal MRI: challenges and promises

The progression to 7 Tesla (7 T) magnetic resonance imaging (MRI) yields promises of substantial increase in signal-to-noise (SNR) ratio. This increase can be traded off to increase image spatial resolution or to decrease acquisition time. However, renal 7 T MRI remains challenging due to inhomogeneity of the radiofrequency field and due to specific absorption rate (SAR) constraints. A number of studies has been published in the field of renal 7 T imaging. While the focus initially was on anatomic imaging and renal MR angiography, later studies have explored renal functional imaging. Although anatomic imaging remains somewhat limited by inhomogeneous excitation and SAR constraints, functional imaging results are promising. The increased SNR at 7 T has been particularly advantageous for blood oxygen level-dependent and arterial spin labelling MRI, as well as sodium MR imaging, thanks to changes in field-strength-dependent magnetic properties. Here, we provide an overview of the currently available literature on renal 7 T MRI. In addition, we provide a brief overview of challenges and opportunities in renal 7 T MR imaging

Simulation-based evaluation of SAR and flip angle homogeneity for five transmit head arrays at 14 T

INTRODUCTION: Various research sites are pursuing 14 T MRI systems. However, both local SAR and RF transmit field inhomogeneity will increase. The aim of this simulation study is to investigate the trade-offs between peak local SAR and flip angle uniformity for five transmit coil array designs at 14 T in comparison to 7 T. METHODS: Investigated coil array designs are: 8 dipole antennas (8D), 16 dipole antennas (16D), 8 loop coils (8D), 16 loop coils (16L), 8 dipoles/8 loop coils (8D8L) and for reference 8 dipoles at 7 T. Both RF shimming and k T-points were investigated by plotting L-curves of peak SAR levels vs flip angle homogeneity. RESULTS: For RF shimming, the 16L array performs best. For k T-points, superior flip angle homogeneity is achieved at the expense of more power deposition, and the dipole arrays outperform the loop coil arrays. DISCUSSION AND CONCLUSION: For most arrays and regular imaging, the constraint on head SAR is reached before constraints on peak local SAR are violated. Furthermore, the different drive vectors in k T-points alleviate strong peaks in local SAR. Flip angle inhomogeneity can be alleviated by k T-points at the expense of larger power deposition. For k T-points, the dipole arrays seem to outperform loop coil arrays

A perturbation approach for ultrafast calculation of RF field enhancements near medical implants in MRI

Patients with medical implants often are deprived of magnetic resonance imaging examination because of safety risks. One specific risk is the enhancement of the radiofrequency fields around the medical implant potentially resulting in significant tissue heating and damage. The assessment of this enhancement is a computationally demanding task, with simulations taking hours or days to converge. Conventionally the source of the radiofrequency fields, patient anatomy, and the medical implant are simulated concurrently. To alleviate the computational burden, we reformulate a fast simulation method that views the medical implant as a small perturbation of the simulation domain without the medical implant and calculates the radiofrequency fields associated with this perturbation. Previously, this method required an extensive offline stage where the result is intractable for large simulation domains. Currently, this offline stage is no longer required and the method is completely online. The proposed method results in comparable radiofrequency fields but is orders of magnitude faster compared to standard simulation technique; the finite-difference time-domain, the finite-sums, and the finite element methods. This acceleration could enable patient-specific and potentially online radiofrequency safety assessment

The role of the frontal cortex in memory: an investigation of the Von Restorff effect

Evidence from neuropsychology and neuroimaging indicate that the pre-frontal cortex (PFC) plays an important role in human memory. Although frontal patients are able to form new memories, these memories appear qualitatively different from those of controls by lacking distinctiveness. Neuroimaging studies of memory indicate activation in the PFC under deep encoding conditions, and under conditions of semantic elaboration. Based on these results, we hypothesize that the PFC enhances memory by extracting differences and commonalities in the studied material. To test this hypothesis, we carried out an experimental investigation to test the relationship between the PFC-dependent factors and semantic factors associated with common and specific features of words. These experiments were performed using Free-Recall of word lists with healthy adults, exploiting the correlation between PFC function and fluid intelligence. As predicted, a correlation was found between fluid intelligence and the Von-Restorff effect (better memory for semantic isolates, e.g., isolate “cat” within category members of “fruit”). Moreover, memory for the semantic isolate was found to depend on the isolate's serial position. The isolate item tends to be recalled first, in comparison to non-isolates, suggesting that the process interacts with short term memory. These results are captured within a computational model of free recall, which includes a PFC mechanism that is sensitive to both commonality and distinctiveness, sustaining a trade-off between the two

RF Coil Setup for P-31 MRSI in Tongue Cancer in vivo at 7 T

Surgery for tongue cancer often results in a major loss in quality of life. While MRI may be used to minimise the volume of excised tissue, often the full tumour extent is missed. This tumour extent may be detected with metabolic imaging. One of the main reasons for the lack of metabolic information on tongue cancer would be the absence of an x-nuclear coil with the tongue as a focus target. Metabolic MRI through 31P MRSI is known as a powerful tool to non-invasively study elevated cell proliferation and disturbed energy metabolism in tumours. Severe magnetic field non-uniformities are inherently caused by the substantial difference in magnetic susceptibilities of tissue and air in the mouth and its environs. Despite this, the wide chemical shift dispersion of 31P could still facilitate precise detection of the cell proliferation biomarkers, phospomonoesters and diesters, as well as energy metabolites ATP, inorganic phosphate, and phosphocreatine potentially mapped over the tongue or tumour in vivo. In this study, we present the first 31P MRSI data of the human tongue in vivo from healthy volunteers and a patient with a tongue tumour at 7 T MRI using a 1H 8-channel transceiver setup placed inside a body 31P transmitter, which is able to get a uniform excitation from the tongue while providing comfortable access to the patient. In addition, a user-friendly external 31P receiver array is used to provide high sensitivity (80%) comparable to an uncomfortable inner mouth loop coil positioned on the tongue. The primary aim is the demonstration of 31P metabolite profiles in the tongue and the differences between healthy and malignant tissue. Indeed, clear elevated cell proliferation expressed as enhanced phosphomonoesters is observed in the tumour vs. the healthy part of the tongue. This can be performed within a total scan duration of 30 min, comparable to clinical scans, with a spatial resolution of 1.5 cm for the 10-min 31P MRSI scan

Design of a forward view antenna for prostate imaging at 7T

Purpose: To design a forward view antenna for prostate imaging at 7T, which is placed between the legs of the subject in addition to a dipole array. Materials and methods: The forward view antenna is realized by placing a cross-dipole antenna at the end of a small rectangular waveguide. Quadrature drive of the cross-dipole can excite a circularly polarized wave propagating along the axial direction to and from the prostate region. Functioning of the forward view antenna is validated by comparing measurements and simulations. Antenna performance is evaluated by numerical simulations and measurements at 7T. Results: Simulations of B1 + on a phantom are in good correspondence with measurements. Simulations on a human model indicate that the signal-to-noise ratio (SNR), specific absorption rate (SAR) efficiency and SAR increase when adding the forward view antenna to a previously published dipole array. The SNR increases by up to 18% when adding the forward view antenna as a receive antenna to an eight-channel dipole array in vivo. Conclusions: A design for a forward view antenna is presented and evaluated. SNR improvements up to 18% are demonstrated when adding the forward view antenna to a dipole array

Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T

At ultrahigh field strengths images of the body are hampered by B 1 -field inhomogeneities. These present themselves as inhomogeneous signal intensity and contrast, which is regarded as a "bias field" to the ideal image. Current bias field correction methods, such as the N4 algorithm, assume a low frequency bias field, which is not sufficiently valid for T2w images at 7 T. In this work we propose a deep learning based bias field correction method to address this issue for T2w prostate images at 7 T. By combining simulated B 1 -field distributions of a multi-transmit setup at 7 T with T2w prostate images at 1.5 T, we generated artificial 7 T images for which the homogeneous counterpart was available. Using these paired data, we trained a neural network to correct the bias field. We predicted either a homogeneous image (t-Image neural network) or the bias field (t-Biasf neural network). In addition, we experimented with the single-channel images of the receive array and the corresponding sum of magnitudes of this array as the input image. Testing was carried out on four datasets: the test split of the synthetic training dataset, volunteer and patient images at 7 T, and patient images at 3 T. For the test split, the performance was evaluated using the structural similarity index measure, Wasserstein distance, and root mean squared error. For all other test data, the features Homogeneity and Energy derived from the gray level co-occurrence matrix (GLCM) were used to quantify the improvement. For each test dataset, the proposed method was compared with the current gold standard: the N4 algorithm. Additionally, a questionnaire was filled out by two clinical experts to assess the homogeneity and contrast preservation of the 7 T datasets. All four proposed neural networks were able to substantially reduce the B 1 -field induced inhomogeneities in T2w 7 T prostate images. By visual inspection, the images clearly look more homogeneous, which is confirmed by the increase in Homogeneity and Energy in the GLCM, and the questionnaire scores from two clinical experts. Occasionally, changes in contrast within the prostate were observed, although much less for the t-Biasf network than for the t-Image network. Further, results on the 3 T dataset demonstrate that the proposed learning based approach is on par with the N4 algorithm. The results demonstrate that the trained networks were capable of reducing the B 1 -field induced inhomogeneities for prostate imaging at 7 T. The quantitative evaluation showed that all proposed learning based correction techniques outperformed the N4 algorithm. Of the investigated methods, the single-channel t-Biasf neural network proves most reliable for bias field correction

The soil microbiome reduces Striga infection of sorghum by modulation of host-derived signaling molecules and root development

Sorghum bicolor is one of the most important cereals in the world and a staple crop for smallholder famers in sub-Saharan Africa. However approximately 20% of sorghum yield is annually lost on the African continent due to infestation with the root parasitic weed Striga hermonthica. Existing Striga management strategies often show an inconsistent to low efficacy. Hence, novel and integrated approaches are needed as an alternative strategy. Here, we demonstrate that the soil microbiome suppresses Striga infection in sorghum. We associate this suppression with microbiome-mediated induction of root endodermal suberization and aerenchyma formation, and depletion of haustorium inducing factors (HIFs), root exudate compounds that are critical for the initial stages of Striga infection. We further identify microbial taxa associated with reduced Striga infection with concomitant changes in root cellular anatomy and differentiation as well as HIF degradation. Our study describes novel microbiome-mediated mechanisms of Striga suppression, encompassing repression of haustorium formation and induction of physical barriers in the host root tissue. These findings open new avenues to broaden the effectiveness of Striga management practices

An Information Theoretic, Microfluidic-Based Single Cell Analysis Permits Identification of Subpopulations among Putatively Homogeneous Stem Cells

An incomplete understanding of the nature of heterogeneity within stem cell populations remains a major impediment to the development of clinically effective cell-based therapies. Transcriptional events within a single cell are inherently stochastic and can produce tremendous variability, even among genetically identical cells. It remains unclear how mammalian cellular systems overcome this intrinsic noisiness of gene expression to produce consequential variations in function, and what impact this has on the biologic and clinical relevance of highly ‘purified’ cell subgroups. To address these questions, we have developed a novel method combining microfluidic-based single cell analysis and information theory to characterize and predict transcriptional programs across hundreds of individual cells. Using this technique, we demonstrate that multiple subpopulations exist within a well-studied and putatively homogeneous stem cell population, murine long-term hematopoietic stem cells (LT-HSCs). These subgroups are defined by nonrandom patterns that are distinguishable from noise and are consistent with known functional properties of these cells. We anticipate that this analytic framework can also be applied to other cell types to elucidate the relationship between transcriptional and phenotypic variation