A novel receive-only liquid nitrogen (LN2)-cooled RF coil for high-resolution in vivo imaging on a 3-Tesla whole-body scanner

The design and operation of a receive-only liquid nitrogen (LN2)-cooled coil and cryostat suitable for medical imaging on a 3-T whole-body magnetic resonance scanner is presented. The coil size, optimized for murine imaging, was determined by using electromagnetic (EM) simulations. This process is therefore easier and more cost effective than building a range of coils. A nonmagnetic cryostat suitable for small-animal imaging was developed having good vacuum and cryogenic temperature performance. The LN2-cooled probe had an active detuning circuit allowing the use with the scanner's built-in body coil. External tuning and matching was adopted to allow for changes to the coil due to temperature and loading. The performance of the probe was evaluated by comparison of signal-to-noise ratio (SNR) with the same radio-frequency RF) coil operating at room temperature (RT). The performance of the RF coil at RT was also benchmarked against a commercial surface coil with a similar dimension to ensure a fair SNR comparison. The cryogenic coil achieved a 1.6- to twofold SNR gain for several different medical imaging applications: For mouse-brain imaging, a 100-mu m resolution was achieved in an imaging time of 3.5 min with an SNR of 25-40, revealing fine anatomical details unseen at lower resolutions for the same time. For heavier loading conditions, such as imaging of the hind legs and liver, the SNR enhancement was slightly reduced to 1.6-fold. The observed SNR was in good agreement with the expected SNR gain correlated with the loaded-quality factor of RF coils from the EM simulations. With the aid of this end-user-friendly and economically attractive cryogenic RF coil, the enhanced SNR available can be used to improve resolution or reduce the duration of individual scans in a number of biomedical applications

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

Field Inhomogeneity Compensation in High Field Magnetic Resonance Imaging (MRI)

This thesis concentrates on the reduction of field (both main field B0 and RF field B1) inhomogeneity in MRI, especially at high B0 field. B0 and B1 field inhomogeneity are major hindrances in high B0 field MRI applications. B1 inhomogeneity will lead to spatially varying signal intensity in the MR images. B0 inhomogeneity produces blurring, distortion and signal loss at tissue interfaces. B0 artifacts are usually termed off-resonance or susceptibility artifacts. None of the existing methods can perfectly correct these inhomogeneity artifacts.This thesis aims at developing three-dimensional (3D) tailored RF (TRF) pulses to mitigate these artifacts. A current limitation in the use of 3D TRF techniques, however, is that pulses are often too long for practical clinical applications. Multiple transmission techniques are proposed to decrease pulse lengths and provide an inherent correction for B1 inhomogeneity. Shorter pulses are also more robust to profile distortions from susceptibility effects.Specifically, slice-selective 3D TRF pulses for multiple (or ¡°parallel¡±) transmitters were designed and validated in uniform phantom and human brain experiments at 3 Tesla. A pseudo-transmit sensitivity encoding (¡°transmit SENSE¡±) method was introduced using a body coil transmitter and multiple receivers to mimic the real parallel transmitter experiment. The kz-direction was controlled by fast switching of gradients in a fashion similar to Echo planar imaging (EPI). The transverse plane (kx-ky) was sampled sparsely with hexagonal trajectories, and accelerated with the transmit SENSE method. The transmit SENSE 3D TRF pulses reduced the B1 inhomogeneity compared to standard SINC pulses in human brain scans. The undersampled transmit SENSE pulses were only 4.3ms long and could excite a 5mm thick slice, which is very promising for clinical applications. Furthermore, these pulses are shown by numerical simulation to have promise in correcting through-plane susceptibility artifacts

Reduction of transmitter B 1 inhomogeneity with transmit SENSE slice-select pulses

Parallel transmitter techniques are a promising approach for reducing transmitter B 1 inhomogeneity due to the potential for adjusting the spatial excitation profile with independent RF pulses. These techniques may be further improved with transmit sensitivity encoding (SENSE) methods because the sensitivity information in pulse design provides an excitation that is inherently compensated for transmitter B 1 inhomogeneity. This paper presents a proof of this concept using transmit SENSE 3D tailored RF pulses designed for small flip angles. An eight-channel receiver coil was used to mimic parallel transmission for brain imaging at 3T. The transmit SENSE pulses were based on the fast- k z design and produced 5-mm-thick slices at a flip angle of 30° with only a 4.3-ms pulse length. It was found that the transmit SENSE pulses produced more homogeneous images than those obtained from the complex sum of images from all receivers excited with a standard RF pulse. Magn Reson Med 57:842–847, 2007. © 2007 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56010/1/21221_ftp.pd

Advanced methods for mapping the radiofrequency magnetic fields in MRI

As MRI systems have increased in static magnetic field strength, the radiofrequency (RF) fields that are used for magnetisation excitation and signal reception have become significantly less uniform. This can lead to image artifacts and errors when performing quantitative MRI. A further complication arises if the RF fields vary substantially in time. In the first part of this investigation temporal variations caused by respiration were explored on a 3T scanner. It was found that fractional changes in transmit field amplitude between inhalation and expiration ranged from 1% to 14% in the region of the liver in a small group of normal subjects. This observation motivated the development of a pulse sequence and reconstruction method to allow dynamic observation of the transmit field throughout the respiratory cycle. However, the proposed method was unsuccessful due to the inherently time-consuming nature of transmit field mapping sequences. This prompted the development of a novel data reconstruction method to allow the acceleration of transmit field mapping sequences. The proposed technique posed the RF field reconstruction as a nonlinear least-squares optimisation problem, exploiting the fact that the fields vary smoothly. It was shown that this approach was superior to standard reconstruction approaches. The final component of this thesis presents a unified approach to RF field calibration. The proposed method uses all measured data to estimate both transmit and receive sensitivities, whilst simultaneously insisting that they are smooth functions of space. The resulting maps are robust to both noise and imperfections in regions of low signal