Faculty Bibliography

A generalized method for phase-constrained parallel MR image reconstruction is presented that combines and extends the concepts of partial-Fourier reconstruction and parallel imaging. It provides a framework for reconstructing images employing either or both techniques and for comparing image quality achieved by varying k-space sampling schemes. The method can be used as a parallel image reconstruction with a partial-Fourier reconstruction built in. It can also be used with trajectories not readily handled by straightforward combinations of partial-Fourier and SENSE-like parallel reconstructions, including variable-density, and non-Cartesian trajectories. The phase constraint specifies a better-conditioned inverse problem compared to unconstrained parallel MR reconstruction alone. This phase-constrained parallel MRI reconstruction offers a one-step alternative to the standard combination of homodyne and SENSE reconstructions with the added benefit of flexibility of sampling trajectory. The theory of the phase-constrained approach is outlined, and its calibration requirements and limitations are discussed. Simulations, phantom experiments, and in vivo experiments are presented

The use of self-calibrating techniques in parallel magnetic resonance imaging eliminates the need for coil sensitivity calibration scans and avoids potential mismatches between calibration scans and subsequent accelerated acquisitions (e.g., as a result of patient motion). Most examples of self-calibrating Cartesian parallel imaging techniques have required the use of modified k-space trajectories that are densely sampled at the center and more sparsely sampled in the periphery. However, spiral and radial trajectories offer inherent self-calibrating characteristics because of their densely sampled center. At no additional cost in acquisition time and with no modification in scanning protocols, in vivo coil sensitivity maps may be extracted from the densely sampled central region of k-space. This work demonstrates the feasibility of self-calibrated spiral and radial parallel imaging using a previously described iterative non-Cartesian sensitivity encoding algorithm

A parallel image reconstruction algorithm is presented that exploits the k-space locality in radiofrequency (RF) coil encoded data. In RF coil encoding, information relevant to reconstructing an omitted datum rapidly diminishes as a function of k-space separation between the omitted datum and the acquired signal data. The proposed method, parallel magnetic resonance imaging with adaptive radius in k-space (PARS), harnesses this physical property of RF coil encoding via a sliding-kernel approach. Unlike generalized parallel imaging approaches that might typically involve inverting a prohibitively large matrix for arbitrary sampling trajectories, the PARS sliding-kernel approach creates manageable and distributable independent matrices to be inverted, achieving both computational efficiency and numerical stability. An empirical method designed to measure total error power is described, and the total error power of PARS reconstructions is studied over a range of k-space radii and accelerations, revealing 'minimal-error' conditions at comparatively modest k-space radii. PARS reconstructions of undersampled in vivo Cartesian and non-Cartesian data sets are shown and are compared selectively with traditional SENSE reconstructions. Various characteristics of the PARS k-space locality constraint (such as the tradeoff between signal-to-noise ratio and artifact power and the relationship with iterative parallel conjugate gradient approaches or nonparallel gridding approaches) are discussed

RATIONALE AND OBJECTIVES: Many clinical applications of Magnetic Resonance Imaging are constrained by basic limits on imaging speed. Parallel MRI relaxes these limits by using the sensitivity patterns of arrays of radiofrequency receiver coils to encode spatial information in a manner complementary to traditional encoding with magnetic field gradients. Until now, parallel MRI has been used to achieve modest improvements in imaging speed; order-of-magnitude improvements have been elusive given fundamental losses in signal-to-noise ratio. The goal of this work was to demonstrate that, with appropriate hardware and careful SNR management, rapid volumetric imaging at high accelerations is in fact feasible. MATERIALS AND METHODS: Contrast-enhanced MRI with an axial 3D spoiled gradient echo imaging sequence was performed in healthy adult subjects using a 32-element RF coil array and a prototype 32-channel MR imaging system. Large imaging volumes were prescribed, in place of traditional limited slabs targeted only to suspect regions. RESULTS: As much as 16-fold net accelerations of imaging were achieved repeatably using this approach. The use of large 3D volumes allowed comprehensive anatomical coverage at clinically useful spatial and/or temporal resolution. The need for careful, time-consuming, and subject-specific scan prescription was also eliminated. CONCLUSION: The highly parallel imaging approach presented here allows previously inaccessible volumetric coverage for time-sensitive MRI examinations such as contrast-enhanced MRA, and simultaneously provides a substantially simplified imaging paradigm. The resulting capability for rapid volumetric imaging promises to combine the strengths of MRI with some of the advantages of alternative imaging modalities such as multidetector CT

The improvement of MRI speed with parallel acquisition is ultimately an SNR-limited process. To offset acquisition- and reconstruction-related SNR losses, practical parallel imaging at high accelerations should include the use of a many-element array with a high intrinsic signal-to-noise ratio (SNR) and spatial-encoding capability, and an advantageous imaging paradigm. We present a 32-element receive-coil array and a volumetric paradigm that address the SNR challenge at high accelerations by maximally exploiting multidimensional acceleration in conjunction with noise averaging. Geometric details beyond an initial design concept for the array were determined with the guidance of simulations. Imaging with the support of 32-channel data acquisition systems produced in vivo results with up to 16-fold acceleration, including images from rapid abdominal and MRA studies

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