Purpose: High permittivity dielectric pads are known to be effective for tailoring the RF field and improving image quality in high field MRI. Despite a number of studies reporting benign specific absorption rate (SAR) effects, their “universal” safety remains an open concern. In this work, we evaluate the impact of the insulation material in between the pad and the body, using both RF simulations as well as phantom experiments. Methods: A 3T configuration with high permittivity material was simulated and characterized experimentally in terms of B₁⁺ fields and RF power absorption, both with and without electrical insulation in between the high permittivity material and the sample. Different insulation conditions were compared, and electromagnetic analyses on the induced current density were performed to elucidate the effect. Results: Increases in RF heating of up to 49% were observed experimentally in a tissue-mimicking phantom after removing the material insulation. The B₁⁺ magnitude and RF transceive phase were not affected. Simulations indicated that an insulation thickness of 0.5–2 mm should be accounted for in numerical models in order to ensure reliable results. Conclusion: A reliable RF safety assessment of high permittivity dielectric pads requires accounting for the insulating properties of the plastic encasing. Ignoring the electrical insulation can lead to erroneous results with substantial increases in local SAR at the interface. Conversely, the material insulation does not need to be modeled to predict the B₁⁺ effects during the design of the pad geometry.

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Purpose: Parallel RF transmission (PTx) is one of the key technologies enabling high quality imaging at ultra-high fields (≥7T). Compliance with regulatory limits on the local specific absorption rate (SAR) typically involves over-conservative safety margins to account for intersubject variability, which negatively affect the utilization of ultra-high field MR. In this work, we present a method to generate a subject-specific body model from a single T1-weighted dataset for personalized local SAR prediction in PTx neuroimaging at 7T. Methods: Multi-contrast data were acquired at 7T (N = 10) to establish ground truth segmentations in eight tissue types. A 2.5D convolutional neural network was trained using the T1-weighted data as input in a leave-one-out cross-validation study. The segmentation accuracy was evaluated through local SAR simulations in a quadrature birdcage as well as a PTx coil model. Results: The network-generated segmentations reached Dice coefficients of 86.7% ± 6.7% (mean ± SD) and showed to successfully address the severe intensity bias and contrast variations typical to 7T. Errors in peak local SAR obtained were below 3.0% in the quadrature birdcage. Results obtained in the PTx configuration indicated that a safety margin of 6.3% ensures conservative local SAR estimates in 95% of the random RF shims, compared to an average overestimation of 34% in the generic “one-size-fits-all” approach. Conclusion: A subject-specific body model can be automatically generated from a single T1-weighted dataset by means of deep learning, providing the necessary inputs for accurate and personalized local SAR predictions in PTx neuroimaging at 7T.

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Background: Accuracy and precision assessment in radiomic features is important for the determination of their potential to characterize cancer lesions. In this regard, simulation of different imaging conditions using specialized phantoms is increasingly being investigated. In this study, the design and evaluation of a modular multimodality imaging phantom to simulate heterogeneous uptake and enhancement patterns for radiomics quantification in hybrid imaging is presented. Methods: A modular multimodality imaging phantom was constructed that could simulate different patterns of heterogeneous uptake and enhancement patterns in positron emission tomography (PET), single-photon emission computed tomography (SPECT), computed tomography (CT), and magnetic resonance (MR) imaging. The phantom was designed to be used as an insert in the standard NEMA-NU2 IEC body phantom casing. The entire phantom insert is composed of three segments, each containing three separately fillable compartments. The fillable compartments between segments had different sizes in order to simulate heterogeneous patterns at different spatial scales. The compartments were separately filled with different ratios of 99mTc-pertechnetate, 18F-fluorodeoxyglucose ([18F]FDG), iodine- and gadolinium-based contrast agents for SPECT, PET, CT, and T1-weighted MR imaging respectively. Image acquisition was performed using standard oncological protocols on all modalities and repeated five times for repeatability assessment. A total of 93 radiomic features were calculated. Variability was assessed by determining the coefficient of quartile variation (CQV) of the features. Comparison of feature repeatability at different modalities and spatial scales was performed using Kruskal-Wallis-, Mann-Whitney U-, one-way ANOVA- and independent t-tests. Results: Heterogeneous uptake and enhancement could be simulated on all four imaging modalities. Radiomic features in SPECT were significantly less stable than in all other modalities. Features in PET were significantly less stable than in MR and CT. A total of 20 features, particularly in the gray-level co-occurrence matrix (GLCM) and gray-level run-length matrix (GLRLM) class, were found to be relatively stable in all four modalities for all three spatial scales of heterogeneous patterns (with CQV < 10%). Conclusion: The phantom was suitable for simulating heterogeneous uptake and enhancement patterns in [18F]FDG-PET, 99mTc-SPECT, CT, and T1-weighted MR images. The results of this work indicate that the phantom might be useful for the further development and optimization of imaging protocols for radiomic quantification in hybrid imaging modalities.@en

Three-dimensional contrast source inversion-electrical properties tomography (3-D CSI-EPT) is an iterative reconstruction method that estimates the electrical properties of tissue from transmit field magnetic resonance data. However, in order to bring 3-D CSI-EPT into practice for complex tissue structures and to understand the origin and effect of errors, insight in the sensitivities of reconstruction accuracy to the major error-sources is necessary. In this paper, different strategies for implementing 3-D CSI-EPT, including their iterative structure, are presented, of which the regularized implementation shows the most potential to be used in practice. Moreover, the influence of initialization, noise, stopping criteria, incident fields, B1-maps, transceive phase and domain truncation are discussed. We show that of all these different error-sources, initialization, accurate coil models and domain truncation have the most dramatic effect on electrical properties reconstructions in practice.

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Purpose: High-permittivity materials in the form of flexible “dielectric pads” have proved very useful for addressing RF inhomogeneities in high field MRI systems. Finding the optimal design of such pads is, however, a tedious task, reducing the impact of this technique. We present an easy-to-use software tool which allows researchers and clinicians to design dielectric pads efficiently on standard computer systems, for 7T neuroimaging and 3T body imaging applications. Methods: The tool incorporates advanced computational methods based on field decomposition and model order reduction as a framework to efficiently evaluate the B₁ ⁺ fields resulting from dielectric pads. The tool further incorporates optimization routines which can either optimize the position of a given dielectric pad, or perform a full parametric design. The optimization procedure can target either a single target field, or perform a sweep to explore the trade-off between homogeneity and efficiency of the B₁ ⁺ field in a specific region of interest. The 3T version further allows for shifting of the imaging landmark to enable different imaging targets to be centered in the body coil. Results: Example design results are shown for imaging the inner ear at 7T and for cardiac imaging at 3T. Computation times for all cases are approximately a minute per target field. Conclusion: The developed tool can be easily used to design dielectric pads for any 7T neuroimaging and 3T body imaging application within minutes. This bridges the gap between the advanced design methods and the practical application by the MR community.

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Purpose: Patients who have medical metallic implants, e.g. orthopaedic implants and pacemakers, often cannot undergo an MRI exam. One of the largest risks is tissue heating due to the radio frequency (RF) fields. The RF safety assessment of implants is computationally demanding. This is due to the large dimensions of the transmit coil compared to the very detailed geometry of an implant. Methods: In this work, we explore a faster computational method for the RF safety assessment of implants that exploits the small geometry. The method requires the RF field without an implant as a basis and calculates the perturbation that the implant induces. The inputs for this method are the incident fields and a library matrix that contains the RF field response of every edge an implant can occupy. Through a low-rank inverse update, using the Sherman–Woodbury–Morrison matrix identity, the EM response of arbitrary implants can be computed within seconds. We compare the solution from full-wave simulations with the results from the presented method, for two implant geometries. Results: From the comparison, we found that the resulting electric and magnetic fields are numerically equivalent (maximum error of 1.35%). However, the computation was between 171 to 2478 times faster than the corresponding GPU accelerated full-wave simulation. Conclusions: The presented method enables for rapid and efficient evaluation of the RF fields near implants and might enable situation-specific scanning conditions.

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PURPOSE: One of the main concerns in fetal MRI is the radiofrequency power that is absorbed both by the mother and the fetus. Passive shimming using high permittivity materials in the form of "dielectric pads" has previously been shown to increase the formula presented efficiency and homogeneity in different applications, while reducing the specific absorption rate (SAR). In this work, we study the effect of optimized dielectric pads for 3 pregnant models. METHODS: Pregnant models in the 3rd, 7th, and 9th months of gestation were used for simulations in a birdcage coil at 3T. Dielectric pads were optimized regions of interest (ROI) using previously developed methods for formula presented efficiency and homogeneity and were designed for 2 ROIs: the entire fetus and the brain of the fetus. The SAR was evaluated in terms of the whole-body SAR, average SAR in the fetus and amniotic fluid, and maximum 10 g-averaged SAR in the mother, fetus, and amniotic fluid. RESULTS: The optimized dielectric pads increased the transmit efficiency up to 55% and increased the formula presented homogeneity in almost every tested configuration. The formula presented -normalized whole-body SAR was reduced by more than 31% for all body models. The formula presented -normalized local SAR was reduced in most scenarios by up to 62%. CONCLUSION: Simulations have shown that optimized high permittivity pads can reduce SAR in pregnant subjects at the 3rd, 7th, and 9th month of gestation, while improving the transmit field homogeneity in the fetus. However, significantly more work is required to demonstrate that fetal imaging is safe under standard operating conditions.

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Model-based electrical properties tomography (EPT; [1,2]) reconstruction with 3-D Contrast Source Inversion-EPT (CSI-EPT; [3,4]) has high potential, but is inherently sensitive to small errors in the model used. Here we assess its sensitivity to errors in the incident electromagnetic (EM) fields due to coupling of the coil to the sample (loading effect), errors in the total EM fields due to errors in mapping methods, and the effect of different object truncations.@en

Contrast source inversion &#x2013; electrical properties tomography (CSI-EPT) is an iterative reconstruction method to retrieve the electrical properties (EPs) of tissues from MR data. The method is based on integral representations of the electromagnetic (EM) field and has been shown to allow EP reconstructions of small structures as well as tissue boundaries with compelling accuracy. However, to date CSI-EPT has been implemented for two-dimensional (2D) configurations only which limits its applicability. In this paper, a full three-dimensional (3D) extension of the CSI-EPT method is presented, to enable CSI-EPT to be applied to realistic 3D scenarios. Here, we demonstrate a proof-of-principle of 3D CSI-EPT and present reconstructions of a 3D abdominal body section and a 3D head model using different settings of the transmit coil. Numerical results show that the full 3D approach yields accurate reconstructions of the EPs, even at tissue boundaries and is most accurate in regions where the absolute value of the electric field is highest.

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In this paper, we present an efficient dedicated electrical properties tomography (EPT) algorithm (called first-order current density EPT ) that exploits the particular radio frequency field structure, which is present in the midplane of a birdcage coil, to reconstruct conductivity and permittivity maps in this plane from B ^ + 1 data. The algorithm consists of a current density and an electrical properties step. In the current density reconstruction step, the induced currents in the midplane are determined by acting with a specific first-order differentiation operator on the B ^ + 1 data. In the electrical properties step, we first determine the electric field strength by solving a particular integral equation, and subsequently determine conductivity and permittivity maps from the constitutive relations. The performance of the algorithm is illustrated by presenting reconstructions of a human brain model based on simulated (noise corrupted) data and of a known phantom model based on experimental data. The method manages to reconstruct conductivity profiles without model related boundary artifacts and is also more robust to noise because only first-order differencing of the data is required as opposed to second-order data differencing in Helmholtz-based approaches. Moreover, reconstructions can be performed in less than a second, allowing for essentially real-time electrical properties mapping.@en

Inhomogeneities in the transmit radio frequency magnetic field ( {\text{B}}-{1}^{+} ) reduce the quality of magnetic resonance (MR) images. This quality can be improved by using high-permittivity pads that tailor the {\text{B}}-{1}^{+} fields. The design of an optimal pad is application-specific and not straightforward and would therefore benefit from a systematic optimization approach. In this paper, we propose such a method to efficiently design dielectric pads. To this end, a projection-based model order reduction technique is used that significantly decreases the dimension of the design problem. Subsequently, the resulting reduced-order model is incorporated in an optimization method in which a desired field in a region of interest can be set. The method is validated by designing a pad for imaging the cerebellum at 7 T. The optimal pad that is found is used in an MR measurement to demonstrate its effectiveness in improving the image quality.

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High-permittivity pads can be used to improve B High-permittivity pads can be used to improve B homogeneity and intensity in homogeneity and intensity inneuroimaging and body applications. Normally, neuroimaging and body applications. Normally, fifinding the “optimal” pad for a nding the “optimal” pad for aspeci specifific region of interest involves evaluating many di c region of interest involves evaluating many difffferent pad designs using erent pad designs usingelectromagnetic simulations, which is a very time-consuming approach taking electromagnetic simulations, which is a very time-consuming approach takinghours to days of computation time. We propose a nonlinear optimization method hours to days of computation time. We propose a nonlinear optimization methodbased on model order reduction that allows us to design high-permittivity pads based on model order reduction that allows us to design high-permittivity padsin less than 30 seconds. in less than 30 seconds.@en

In this work we present a systematic evaluation of the potential of combining dielectric materials with an array of electric dipoles for MRI. Design parameters include the permittivity and length of a dielectric sleeve, as well as the dipole length and position of the tuning inductors. Results show that the combined approach improves transmit efficiency and SNR by ~10 to 15 % compared to an optimized dipole array without dielectric sleeve. The resulting induced current densities reflect an improved correspondence with the ideal current pattern, which explains the gains in performance.@en

High-field MRI reduces the homogeneity of the B1+ transmit field, which in turn degrades the quality of MR images. High-permittivity pads are increasingly used to restore the homogeneity of this transmit field. Designing such a pad in terms of dimensions, position, and constitution is not trivial, however, and in this work we propose a design method that can be used to find an optimal pad for a certain imaging region of interest. By incorporating a projection based model order reduction technique in a Gauss-Newton optimization method, optimal dielectric pads can be found at significantly reduced computation times. We illustrate the performance of our optimization method by designing a pad for 7T cerebellum imaging and show its effectiveness in an actual MR imaging experiment.@en

Interference effects in the transmit $B_{1}^{+}$ field can severely degrade the image quality in high-field Magnetic Resonance Imaging (MRI). High-permittivity pads are increasingly used to counteract these effects, but designing such pads is not trivial. In this paper, we present an efficient solution methodology for this dielectric RF shimming problem. By exploiting the fact that dielectric pads form a low rank perturbation of a large-scale background model, we are able to efficiently compute $B_{1}^{+}$ fields that correspond to a wide range of different pad realizations. This allows us to efficiently design dielectric pads that eliminate the $B_{1}^{+}$ -interference effects of high-field MRI. We show that significant speed up factors can be achieved compared with traditional field simulation approaches and we validate our approach against measurements. Measured and simulated field responses are in good agreement with each other indicating that the proposed solution methodology enables us to efficiently analyze dielectric pads in realistic MRI measurement settings.@en

Purpose In this study, we analyzed dielectric shimming by formulating it as an electromagnetic scattering problem using integral equations. Methods Three-dimensional simulations of the radiofrequency field in two configurations using different materials were analyzed in terms of induced currents and secondary fields. A two-dimensional integral equation method with different backgrounds was used to identify the underlying physical mechanisms. This framework was then used to develop an inversion method for the design of dielectric pads. Results The effects of a dielectric pad can be attributed to the interference of a secondary field that is produced by the currents induced in the dielectric pad, radiating in an inhomogeneous background. The integral equation method with inhomogeneous background reduces the complexity of the forward and inverse problem significantly and can be used to optimize the permittivity distribution for a desired inline image field. Agreement with experimental inline image maps was obtained in a cylindrical phantom, demonstrating the validity of the method. Conclusions The integral equation method with inhomogeneous background yields an efficient numerical framework for the analysis and inverse design of dielectric shimming materials. Magn Reson Med 75:2185–2194, 2016. © 2015 Wiley Periodicals, Inc. @en