Faculty Bibliography

Theoretical arguments and experimental results are presented that characterize the impact of inductive coupling on the performance of parallel MRI reconstructions. A simple model of MR signal and noise reception suggests that the intrinsic amount of spatial information available from a given coil array is unchanged in the presence of inductive coupling, as long as the sample remains the dominant source of noise for the coupled array. Any loss of distinctness in the measured coil sensitivities is compensated by information stored in the measured noise correlations. Adjustments to the theory are described to account for preamplifier noise contributions. Results are presented from an experimental system in which preamplifier input impedances are systematically adjusted in order to vary the level of coupling between array elements. Parallel image reconstructions using an array with four different levels of coupling and an acceleration factor up to six show average SNR changes of -7.6% to +7.5%. The modest changes in overall SNR are accompanied by similarly small changes in g-factor. These initial results suggest that moderate amounts of inductive coupling should not have a prohibitive effect on the use of a given coil array for parallel MRI

A recently developed parallel magnetic resonance (MR) imaging technique, parallel imaging with an augmented radius in k space, was used to accelerate the volumetric interpolated breath-hold examination (VIBE) performed in 20 patients referred for clinical liver imaging. Nonaccelerated MR images were also acquired in these patients. A five-point scale was used to score the quality of the images. The acceleration resulted in reduced image quality: The nonaccelerated images had a significantly higher (P <.05) mean score--3.8 +/- 0.3 (SD), indicating good quality--than the accelerated images--3.0 +/- 0.3, indicating acceptable quality. However, for three patients who could not hold their breath for the duration necessary for nonaccelerated imaging, less severe breathing artifacts on the accelerated images resulted in improved quality compared with the quality of the nonaccelerated images. Parallel MR imaging-accelerated VIBE may be beneficial for patients who have difficulty sustaining a breath hold for the duration necessary to perform nonaccelerated imaging

The recently introduced planar strip array (PSA) can significantly reduce scan times in parallel MRI by enabling the utilization of a large number of RF strip detectors that are inherently decoupled, and are tuned by adjusting the strip length to integer multiples of a quarter-wavelength (lambda/4) in the presence of a ground plane and dielectric substrate. In addition, the more explicit spatial information embedded in the phase of the signals from the strip array is advantageous (compared to loop arrays) for limiting aliasing artifacts in parallel MRI. However, losses in the detector as its natural resonance frequency approaches the Larmor frequency (where the wavelength is long at 1.5 T) may limit the signal-to-noise ratio (SNR) of the PSA. Moreover, the PSA's inherent lambda/4 structure severely limits our ability to adjust detector geometry to optimize the performance for a specific organ system, as is done with loop coils. In this study we replaced the dielectric substrate with discrete capacitors, which resulted in both SNR improvement and a tunable lumped-element PSA (LPSA) whose dimensions can be optimized within broad constraints, for a given region of interest (ROI) and MRI frequency. A detailed theoretical analysis of the LPSA is presented, including its equivalent circuit, electromagnetic fields, SNR, and g-factor maps for parallel MRI. Two different decoupling schemes for the LPSA are described. A four-element LPSA prototype was built to test the theory with quantitative measurements on images obtained with parallel and conventional acquisition schemes. Magn Reson Med 51:172-183, 2004

A method is described for establishing an upper bound on the spatial encoding capabilities of coil arrays in parallel MRI. Ultimate intrinsic signal-to-noise ratio (SNR), independent of any particular conductor arrangement, is calculated by expressing arbitrary coil sensitivities in terms of a complete set of basis functions that satisfy Maxwell's equations within the sample and performing parallel imaging reconstructions using these basis functions. The dependence of the ultimate intrinsic SNR on a variety of experimental conditions is explored and a physically intuitive explanation for the observed behavior is provided based on a comparison between the electromagnetic wavelength and the distance between aliasing points. Imaging at high field strength, with correspondingly short wavelength, is shown to offer advantages for parallel imaging beyond those already expected due to the larger available spin polarization. One-dimensional undersampling of k-space yields a steep drop in attainable SNR for more than a 5-fold reduction of scan time, while 2D undersampling permits access to much higher degrees of acceleration. Increased tissue conductivity decreases baseline SNR, but improves parallel imaging performance. A procedure is also provided for generating the optimal coil sensitivity pattern for a given acceleration, which will serve as a useful guide for future coil designs

A new parallel MR imaging technique, which uses localized information from the elements of a multi-coil array to accelerate imaging, is described. The technique offers an alternative reconstruction approach to currently available techniques (e.g., SMASH and SENSE). Following a partial k-space data acquisition, image reconstruction in this approach proceeds in two steps: first, fitting the measured coil sensitivities to a set of partially localized target functions, a blurred intermediate image of the studied object is produced. Blurring is obtained in a systematic manner, forming images of the studied object convolved with a known convolution kernel. Full spatial resolution is then recovered by deconvolution of the blurred images with the known kernel function. The technique offers flexibility in the arrangement of the acquired signal data k-lines, and a mechanism for controlling reconstruction quality through the convolution the deconvolution procedure. The technique was validated in phantom and in vivo imaging experiments demonstrating high time reduction factors

The purposes of this article were to outline the current state of adrenal imaging, to highlight new developments, and to review the current radiologic advances that provide improved functional and structural information about adrenal disorders

Calibration of the spatial sensitivity functions of coil arrays is a crucial element in parallel magnetic resonance imaging (PMRI). The most common approach has been to measure coil sensitivities directly using one or more low-resolution images acquired before or after accelerated data acquisition. However, since it is difficult to ensure that the patient and coil array will be in exactly the same positions during both calibration scans and accelerated imaging, this approach can introduce sensitivity miscalibration errors into PMRI reconstructions. This work shows that it is possible to extract sensitivity calibration images directly from a fully sampled central region of a variable-density k-space acquisition. These images have all the features of traditional PMRI sensitivity calibrations and therefore may be used for any PMRI reconstruction technique without modification. Because these calibration data are acquired simultaneously with the data to be reconstructed, errors due to sensitivity miscalibration are eliminated. In vivo implementations of self-calibrating parallel imaging using a flexible coil array are demonstrated in abdominal imaging and in real-time cardiac imaging studies

Parallel magnetic resonance imaging (MRI) techniques use spatial information from arrays of radiofrequency (RF) detector coils to accelerate imaging. A number of parallel MRI techniques have been described in recent years, and numerous clinical applications are currently being explored. The advent of practical parallel imaging presents various challenges for image reconstruction and RF system design. Recent advances in tailored SiMultaneous Acquisition of Spatial Harmonics (SMASH) image reconstructions are summarized. These advances enable robust SMASH imaging in arbitrary image planes with a wide range of coil array geometries. A generalized formalism is described which may be used to understand the relations between SMASH and SENSE, to derive typical implementations of each as special cases, and to form hybrid techniques combining some of the advantages of both. Accurate knowledge of coil sensitivities is crucial for parallel MRI, and errors in calibration represent one of the most common and the most pernicious sources of error in parallel image reconstructions. As one example, motion of the patient and/or the coil array between the sensitivity reference scan and the accelerated acquisition can lead to calibration errors and reconstruction artifacts. Self-calibrating parallel MRI approaches that address this problem by eliminating the need for external sensitivity references are reviewed. The ultimate achievable signal-to-noise ratio (SNR) for parallel MRI studies is closely tied to the geometry and sensitivity patterns of the coil arrays used for spatial encoding. Several parallel imaging array designs that depart from the traditional model of overlapped adjacent loop elements are described

The fitting of coil sensitivity functions to spatial harmonics is central to image reconstructions using the simultaneous acquisition of spatial harmonics (SMASH) technique. It has previously been shown that the selection of the set of spatial harmonics used in a SMASH reconstruction can have a noticeable effect on the quality of the reconstructed image. However, a mechanism for automatic selection of the best set of harmonics in any particular situation has not been provided. In this work, a modification to the SMASH reconstruction procedure is introduced that allows the use of a weighted average of all possible harmonics in a reconstruction. The new reconstruction procedure is shown to allow automatic selection of the spatial harmonics and substantially improve SNR for both phantom and in vivo images

The SiMultaneous Acquisition of Spatial Harmonics (SMASH) technique uses linear combinations of undersampled datasets from the component coils of an RF coil array to reconstruct fully sampled composite datasets in reduced imaging times. In previously reported implementations, SMASH reconstructions were designed to reproduce the images that would otherwise be obtained by simple sums of fully gradient encoded component coil images. This strategy has left SMASH images vulnerable to phase cancellation artifacts when the sensitivities of RF coil array elements are not suitably phase-aligned. In fully gradient encoded imaging schemes these artifacts can be eliminated using a variety of methods for combining the individual coil images, including matched filter combinations as well as sum of squares combinations. Until now, these reconstruction schemes have been unavailable to SMASH reconstructions as SMASH produced a final composite image directly from the raw component coil k-space datasets. This article demonstrates a modification to SMASH that allows reconstruction of a full set of accelerated individual component coil images by fitting component coil sensitivity functions to a complete set of spatial harmonics tailored for each coil in the array. Standard component coil combinations applied to the individual reconstructed images produce final composite images free of phase cancellation artifacts