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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This dissertation describes how to design dielectric pads that can be used to increase image quality in Magnetic Resonance Imaging, and how to accelerate image reconstruction times using a preconditioner. Image quality is limited by the signal to noise ratio of a scan. This ratio is increased for higher static magnetic field strengths and therefore there is great interest in high-field MRI. The wavelength of the transmitted magnetic RF field decreases for higher field strengths, and it becomes comparable to the dimensions of the human body. Consequently, RF interference patterns are encountered which can severely degrade image quality because of a low transmit efficiency or because of inhomogeneities in the field distribution. Dielectric pads can be used to improve this distribution as the pads tailor the field by inducing a secondary magnetic field due to its high permittivity. Typically, the pads are placed tangential to the body and in the vicinity of the region of interest. The exact location, dimensions, and constitution of the pad need to be carefully determined, however, and depend on the application and the MR configuration. Normally, parametric design studies are carried out using electromagnetic field solvers to find a suitable pad, but this is a very time consuming process which can last hours to days. In contrast with these design studies, we present methods to efficiently model and design the dielectric pads using reduced order modeling and optimization techniques. Subsequently, we have created a design tool to bridge the gap between the advanced design methods and the practical application by the MR community. Now, pads can be designed for any 7T neuroimaging and 3T body imaging application within minutes. In the second part of the thesis a preconditioner is designed for parallel imaging (PI) and compressed sensing (CS) reconstructions. MRI acquisition times can be strongly reduced by using PI and CS techniques by acquiring less data than prescribed by the Nyquist criterion to fully reconstruct the anatomic image; this is beneficial for patient's comfort and for minimizing the risk of patient's movement. Although acquisition times are reduced, the reconstruction times are increased significantly. The reconstruction times can be reduced when a preconditioner is used. In this thesis, we construct such a preconditioner for the frequently used iterative Split Bregman framework. We have tested the performance in a conjugate gradient framework, and show that for different coil configurations, undersampling patterns, and anatomies, a five-fold acceleration can be obtained for solving the linear system part of Split Bregman.@en

Purpose: Design of a preconditioner for fast and efficient parallel imaging (PI) and compressed sensing (CS) reconstructions for Cartesian trajectories. Theory: PI and CS reconstructions become time consuming when the problem size or the number of coils is large, due to the large linear system of equations that has to be solved in l₁ and l₂-norm based reconstruction algorithms. Such linear systems can be solved efficiently using effective preconditioning techniques. Methods: In this article we construct such a preconditioner by approximating the system matrix of the linear system, which comprises the data fidelity and includes total variation and wavelet regularization, by a matrix that is block circulant with circulant blocks. Due to this structure, the preconditioner can be constructed quickly and its inverse can be evaluated fast using only two fast Fourier transformations. We test the performance of the preconditioner for the conjugate gradient method as the linear solver, integrated into the well-established Split Bregman algorithm. Results: The designed circulant preconditioner reduces the number of iterations required in the conjugate gradient method by almost a factor of 5. The speed up results in a total acceleration factor of approximately 2.5 for the entire reconstruction algorithm when implemented in MATLAB, while the initialization time of the preconditioner is negligible. Conclusion: The proposed preconditioner reduces the reconstruction time for PI and CS in a Split Bregman implementation without compromising reconstruction stability and can easily handle large systems since it is Fourier-based, allowing for efficient computations.

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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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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.@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-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

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

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

MRI at high fields requires new approaches to RF coil design to maximize RF performance. Over the past years, various technologies have been developed, ranging fromactive control via parallel RF transmission (pTx), to passive approaches using dielectric materials. Previous work also indicates that the combination of both can yield furtherimprovements.1,2 However, the analysis of a dielectric shim in resonant coil structures such as surface arrays can involve long simulation times due to mutual coupling. Thisimpedes a constructive analysis on the design of the dielectric in such scenarios.A domain decomposition method has previously been presented which reduces the computational domain to that of the dielectric shim, allowing for much faster evaluation of itseffect.3 This approach is especially powerful in a decoupled scenario in which the coil’s current distribution is minimally affected by the dielectric. In this work, we extend thedomain decomposition method using circuit co-simulation techniques to account for tuned coil models as well as array configurations. Examples are shown for a tuned 7T birdcageanalysis and a four-channel dipole array design study.@en

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

High permittivity materials, in the form of “dielectric pads” are used in neuroimaging and body applications to improve B1+ homogeneity and intensity or to reduce corresponding SAR measures. In 3D, systematic pad design is computationally intensive with very long associated simulation times. We propose a hybrid solution to this problem by combining the flexibility of FDTD to model complex background configurations (coil/shield/subject) with an integral equation approach that takes the presence of a dielectric pad into account. This solution leads to speed up factors of 30 – 40 compared with conventional FDTD approaches and enables effective 3D dielectric pad design.@en

High permittivity materials, in the form of “dielectric pads” are used in neuroimaging and body applications to improve B1+ homogeneity and intensity or to reduce corresponding SAR measures. In 3D, systematic pad design is computationally intensive with very long associated simulation times. We propose a hybrid solution to this problem by combining the flexibility of FDTD to model complex background configurations (coil/shield/subject) with an integral equation approach that takes the presence of a dielectric pad into account. This solution leads to speed up factors of 30 – 40 compared with conventional FDTD approaches and enables effective 3D dielectric pad design.@en