Improvements in magnetic resonance imaging excitation pulse design

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 241-253).This thesis focuses on the design of magnetic resonance imaging (MRI) radio-frequency (RF) excitation pulses, and its primary contributions are made through connections with the novel multiple-system single-output (MSSO) simultaneous sparse approximation problem. The contributions are both conceptual and algorithmic and are validated with simulations, as well as anthropogenic-object-based and in vivo trials on MRI scanners. Excitation pulses are essential to MRI: they excite nuclear spins within a subject that are detected by a resonant coil and then reconstructed into images. Pulses need to be as short as possible due to spin relaxation, tissue heating, and main field inhomogeneity limitations. When magnetic spins are tilted by only a small amount, pulse transmission may be interpreted as depositing energy in a continuous three-dimensional Fourier-like domain along a one-dimensional contour to form an excitation in the spatial domain. Pulse duration is proportional to the length of the contour and inversely proportional to the rate at which it is traversed, and the rate is limited by system gradient hardware restrictions. Joint design of the contour and a corresponding excitation pulse is a difficult and central problem, while determining near-optimal energy deposition once the contour is fixed is significantly easier. We first pose the NP-Hard MSSO problem and formulate greedy and convex relaxation-based algorithms with which to approximately solve it. We find that second-order-cone programming and iteratively-reweighted least squares approaches are practical techniques for solving the relaxed problem and prove that single-vector sparse approximation of a complex-valued vector is an MSSO problem.(cont.) We then focus on pulse design, first comparing three algorithms for solving linear systems of multi-channel excitation design equations, presenting experimental results from a 3 Tesla scanner with eight excitation channels. Our aim then turns toward the joint design of pulses and trajectories. We take joint design in a novel direction by utilizing MSSO theory and algorithms to design short-duration sparsity-enforced pulses. These pulses are used to mitigate transmit field inhomogeneity in the human brain at 7 Tesla, a significant step towards the clinical use of high-field imaging in the study of cancer, Alzheimer's disease, and Multiple Sclerosis. Pulses generated by the sparsity-enforced method outperform those created via conventional Fourier-based techniques, e.g., when attempting to produce a uniform magnetization in the presence of severe RF inhomogeneity, a 5.7-ms 15-spoke pulse generated by the sparsity-enforced method produces an excitation with 1.28 times lower root-mean-square error than conventionally-designed 15-spoke pulses. To achieve this same level of uniformity, conventional methods must use 29-spoke pulses that are 1.4 times longer. We then confront a subset selection problem that arises when a parallel excitation system has more transmit modes available than hardware transmit channels with which to drive them. MSSO theory and algorithms are again applicable and determine surprising targetspecific mixtures of light and dark modes that yield high-quality excitations. Finally, we study the critical patient safety issue of specific absorption rate (SAR) of multi-channel excitation pulses at high field. We develop a fast SAR calculation algorithm and propose optimizing an individual pulse and time-multiplexing a set of pulses as ways to reduce SAR; the latter is capable of reducing maximum local SAR by 11% with no impact on pulse duration.by Adam Charles Zelinski.Ph.D

Fast joint design method for parallel excitation radiofrequency pulse and gradient waveforms considering off‐resonance

A fast parallel excitation pulse design algorithm to select and to order phase‐encoding (PE) locations (also known as “spokes”) of an Echo‐Volumar excitation k ‐space trajectory considering B 0 field inhomogeneity is presented. Recently, other groups have conducted research to choose optimal PE locations, but the potential benefit of considering B 0 field inhomogeneity during PE location selection or their ordering has not been fully investigated. This article introduces a novel fast greedy algorithm to determine PE locations and their order that takes into account the off‐resonance effects. Computer simulations of the proposed algorithm for B 1 field inhomogeneity correction demonstrate that it not only improves excitation accuracy but also provides an effective ordering of the PE locations. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/91341/1/24311_ftp.pd

Simultaneously Sparse Solutions to Linear Inverse Problems with Multiple System Matrices and a Single Observation Vector

A linear inverse problem is proposed that requires the determination of multiple unknown signal vectors. Each unknown vector passes through a different system matrix and the results are added to yield a single observation vector. Given the matrices and lone observation, the objective is to find a simultaneously sparse set of unknown vectors that solves the system. We will refer to this as the multiple-system single-output (MSSO) simultaneous sparsity problem. This manuscript contrasts the MSSO problem with other simultaneous sparsity problems and conducts a thorough initial exploration of algorithms with which to solve it. Seven algorithms are formulated that approximately solve this NP-Hard problem. Three greedy techniques are developed (matching pursuit, orthogonal matching pursuit, and least squares matching pursuit) along with four methods based on a convex relaxation (iteratively reweighted least squares, two forms of iterative shrinkage, and formulation as a second-order cone program). The algorithms are evaluated across three experiments: the first and second involve sparsity profile recovery in noiseless and noisy scenarios, respectively, while the third deals with magnetic resonance imaging radio-frequency excitation pulse design.Comment: 36 pages; manuscript unchanged from July 21, 2008, except for updated references; content appears in September 2008 PhD thesi

Numerical field simulation for parallel transmission in MRI at 7 tesla

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 41-42).Parallel transmission (pTx) is a promising improvement to coil design that has been demonstrated to mitigate B1* inhomogeneity, manifest as center brightening, for high-field magnetic resonance imaging (MRI). Parallel transmission achieves spatially-tailored pulses through multiple radiofrequency (RF) excitation coils that can be activated independently. In this work, simulations of magnetic fields in numerical phantoms using an FDTD solver are used to estimate the excitation profiles for an 8-channel RF head coil. Each channel is driven individually in the presence of a dielectric load, and the excitation profiles for all channels are combined post-processing into a B1+ profile of the birdcage (BC) mode. The B1 profile is calculated for a dielectric sphere phantom with material properties of white matter at main magnetic field strengths of 3T and 7T to demonstrate center brightening associated with head imaging at high magnetic field strengths. Measurements of a circular ROI centered in the image show more B1+ inhomogeneity at 7T than at 3T. The B1* profile is then simulated for a numerical head phantom with spatially segmented tissue compartments at 7T. Comparison of the simulated and in vivo B1* profiles at 7T shows agreement in the B1 inhomogeneity. The results provide confidence in numerical simulation as a means to estimate magnetic fields for human imaging. This work will allow further numerical simulations to model the propagation of electric fields within the body, ultimately to provide an estimate of heat deposition in tissue, quantified by the specific absorption rate (SAR), which is a limiting factor of the use of high-field MRI in the clinical setting.by Jessica A. Bernier.S.M

Specific Absorption Rate Reduction Using Nonlinear Gradient Fields

Cataloged from PDF version of article.The specific absorption rate is used as one of the main safety parameters in magnetic resonance imaging. The performance of imaging sequences is frequently hampered by the limitations imposed on the specific absorption rate that increase in severity at higher field strengths. The most well-known approach to reducing the specific absorption rate is presumably the variable rate selective excitation technique, which modifies the gradient waveforms in time. In this article, an alternative approach is introduced that uses gradient fields with nonlinear variations in space to reduce the specific absorption rate. The effect of such gradient fields on the relationship between the desired excitation profile and the corresponding radiofrequency pulse is shown. The feasibility of the method is demonstrated using three examples of radiofrequency pulse design. Finally, the proposed method is compared with and combined with the variable rate selective excitation technique. Magn Reson Med 70:537–546, 2013. © 2012 Wiley Periodicals, In

Simultaneous use of Individual and Joint Regularization Terms in Compressive Sensing: Joint Reconstruction of Multi-Channel Multi-Contrast MRI Acquisitions

Purpose: A time-efficient strategy to acquire high-quality multi-contrast images is to reconstruct undersampled data with joint regularization terms that leverage common information across contrasts. However, these terms can cause leakage of uncommon features among contrasts, compromising diagnostic utility. The goal of this study is to develop a compressive sensing method for multi-channel multi-contrast magnetic resonance imaging (MRI) that optimally utilizes shared information while preventing feature leakage. Theory: Joint regularization terms group sparsity and colour total variation are used to exploit common features across images while individual sparsity and total variation are also used to prevent leakage of distinct features across contrasts. The multi-channel multi-contrast reconstruction problem is solved via a fast algorithm based on Alternating Direction Method of Multipliers. Methods: The proposed method is compared against using only individual and only joint regularization terms in reconstruction. Comparisons were performed on single-channel simulated and multi-channel in-vivo datasets in terms of reconstruction quality and neuroradiologist reader scores. Results: The proposed method demonstrates rapid convergence and improved image quality for both simulated and in-vivo datasets. Furthermore, while reconstructions that solely use joint regularization terms are prone to leakage-of-features, the proposed method reliably avoids leakage via simultaneous use of joint and individual terms. Conclusion: The proposed compressive sensing method performs fast reconstruction of multi-channel multi-contrast MRI data with improved image quality. It offers reliability against feature leakage in joint reconstructions, thereby holding great promise for clinical use.Comment: 13 pages, 13 figures. Submitted for possible publicatio

Simultaneous use of linear and nonlinear gradients for B1 + inhomogeneity correction

The simultaneous use of linear spatial encoding magnetic fields (L-SEMs) and nonlinear spatial encoding magnetic fields (N-SEMs) in B1 + inhomogeneity problems is formulated and demonstrated with both simulations and experiments. Independent excitation k-space variables for N-SEMs are formulated for the simultaneous use of L-SEMs and N-SEMs by assuming a small tip angle. The formulation shows that, when N-SEMs are considered as an independent excitation k-space variable, numerous different k-space trajectories and frequency weightings differing in dimension, length, and energy can be designed for a given target transverse magnetization distribution. The advantage of simultaneous use of L-SEMs and N-SEMs is demonstrated by B1 + inhomogeneity correction with spoke excitation. To fully utilize the independent k-space formulations, global optimizations are performed for 1D, 2D RF power limited, and 2D RF power unlimited simulations and experiments. Three different cases are compared: L-SEMs alone, N-SEMs alone, and both used simultaneously. In all cases, the simultaneous use of L-SEMs and N-SEMs leads to a decreased standard deviation in the ROI compared with using only L-SEMs or N-SEMs. The simultaneous use of L-SEMs and N-SEMs results in better B1 + inhomogeneity correction than using only L-SEMs or N-SEMs due to the increased number of degrees of freedom. Copyright © 2017 John Wiley & Sons, Ltd

Topics in Steady-state MRI Sequences and RF Pulse Optimization.

Small-tip fast recovery (STFR) is a recently proposed rapid steady-state magnetic resonance imaging (MRI) sequence that has the potential to be an alternative to the popular balanced steady-state free precession (bSSFP) imaging sequence, since they have similar signal level and tissue contrast, but STFR has reduced banding artifacts. In this dissertation, an analytic equation of the steady-state signal for the unspoiled version of STFR is first derived. It is shown that unspoiled-STFR is less sensitive to the inaccuracy in excitation than the previous proposed spoiled-STFR. By combining unspoiled-STFR with jointly designed tip-down and tip-up pulses, a 3D STFR acquisition over 3-4 cm thick 3D ROI with single coil and short RF pulses (1.7 ms) is demonstrated. Then, it is demonstrated that STFR can reliably detect functional MRI signal and the contrast is driven mainly from intra-voxel dephasing, not diffusion, using Monte Carlo simulation, human experiments and test-retest reliability. Following that another version of STFR using a spectral pre-winding pulse instead of the spatially tailored pulse is investigated, leading to less T2* weighting, easier implementation. Multidimensional selective RF pulse is a key part for STFR and many other MRI applications. Two novel RF pulse optimization methods are proposed. First, a minimax formulation that directly controls the maximum excitation error, and an effective optimization algorithm using variable splitting and alternating direction method of multipliers (ADMM). The proposed method reduced the maximum excitation by more than half in all the testing cases. Second, a method that jointly optimizes the excitation k-space trajectory and RF pulse is proposed. The k-space trajectory is parametrized using 2nd-order B-splines, and an interior point algorithm is used to explicitly solve the constrained optimization. An effective initialization method is also suggested. The joint design reduced the NRMSE by more than 30 percent compared to existing methods in inner volume excitation and pre-phasing problem. Using the proposed joint design, rapid inner volume STFR imaging with a 4 ms excitation pulse with single transmit coil is demonstrated. Finally, a regularized Bloch-Siegert B1 map reconstruction method is presented that significantly reduces the noise in estimated B1 maps.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111514/1/sunhao_1.pd

Four dimensional spectral‐spatial fat saturation pulse design

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/109603/1/mrm25076.pd