Sensitivity profiles from an array of coils for encoding and reconstruction in parallel (SPACE RIP) (original) (raw)

Recent advances in image reconstruction, coil sensitivity calibration, and coil array design for SMASH and generalized parallel MRI

Magma: Magnetic Resonance Materials in Physics, Biology, and Medicine, 2001

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.

Parallel magnetic resonance imaging using coils with localized sensitivities

Magnetic Resonance Imaging, 2004

The purpose of this study was to present clinical examples and illustrate the inefficiencies of a conventional reconstruction using a commercially available phased array coil with localized sensitivities. Five patients were imaged at 1.5 T using a cardiac-synchronized gadolinium-enhanced acquisition and a commercially available four-element phased array coil. Four unique sets of images were reconstructed from the acquired k-space data: (a) sum-of-squares image using four elements of the coil; localized sum-of-squares images from the (b) anterior coils and (c) posterior coils and a (c) local reconstruction. Images were analyzed for artifacts and usable field-of-view. Conventional image reconstruction produced images with fold-over artifacts in all cases spanning a portion of the image (mean 90 mm; range 36 -126 mm). The local reconstruction removed fold-over artifacts and resulted in an effective increase in the field-of-view (mean 50%; range 20 -70%). Commercially available phased array coils do not always have overlapping sensitivities. Fold-over artifacts can be removed using an alternate reconstruction method. When assessing the advantages of parallel imaging techniques, gains achieved using techniques such as SENSE and SMASH should be gauged against the acquisition time of the locaized method rather than the conventional sum-of-squares method.

An introduction to coil array design for parallel MRI

Nmr in Biomedicine - NMR BIOMED, 2006

The basic principles of radiofrequency coil array design for parallel MRI are described from both theoretical and practical perspectives. Because parallel MRI techniques rely on coil array sensitivities to provide spatial information about the sample, a careful choice of array design is essential. The concepts of coil array spatial encoding are first discussed from four qualitative perspectives. These qualitative descriptions include using coil arrays to emulate spatial harmonics, choosing coils with selective sensitivities to aliased pixels, using coil sensitivities with broad k-space reception profiles, and relying on detector coils to provide a set of generalized projections of the sample. This qualitative discussion is followed by a quantitative analysis of coil arrays, which is discussed in terms of the baseline SNR of the received images as well as the noise amplifications (g-factor) in the reconstructed data. The complications encountered during the experimental evaluation of coil array SNR are discussed, and solutions are proposed. A series of specific array designs are reviewed, with an emphasis on the general design considerations that motivate each approach. Finally, a set of special topics is discussed, which reflect issues that have become important, especially as arrays are being designed for more high-performance applications of parallel MRI. These topics include concerns about the depth penetration of arrays composed of small elements, the use of adaptive arrays for systems with limited receiver channels, the management of inductive coupling between array elements, and special considerations required at high field strengths. The fundamental limits of spatial encoding using coil arrays are discussed, with a primary emphasis on how the determination of these limits impacts the design of optimized arrays. This review is intended to provide insight into how arrays are currently used for parallel MRI and to place into context the new innovations that are to come.

Regularization of parallel MRI reconstruction using in vivo coil sensitivities

2009

Parallel MRI can achieve increased spatiotemporal resolution in MRI by simultaneously sampling reduced k-space data with multiple receiver coils. One requirement that different parallel MRI techniques have in common is the need to determine spatial sensitivity information for the coil array. This is often done by smoothing the raw sensitivities obtained from low-resolution calibration images, for example via polynomial fitting. However, this sensitivity post-processing can be both time-consuming and error-prone. Another important factor in Parallel MRI is noise amplification in the reconstruction, which is due to non-unity transformations in the image reconstruction associated with spatially correlated coil sensitivity profiles. Generally, regularization approaches, such as Tikhonov and SVD-based methods, are applied to reduce SNR loss, at the price of introducing residual aliasing. In this work, we present a regularization approach using in vivo coil sensitivities in parallel MRI to overcome these potential errors into the reconstruction. The mathematical background of the proposed method is explained, and the technique is demonstrated with phantom images. The effectiveness of the proposed method is then illustrated clinically in a whole-heart 3D cardiac MR acquisition within a single breath-hold. The proposed method can not only overcome the sensitivity calibration problem, but also suppress a substantial portion of reconstruction-related noise without noticeable introduction of residual aliasing artifacts.

Parallel magnetic resonance imaging

Physics in Medicine and Biology, 2007

Parallel imaging has been the single biggest innovation in magnetic resonance imaging in the last decade. The use of multiple receiver coils to augment the time consuming Fourier encoding has reduced acquisition times significantly. This increase in speed comes at a time when other approaches to acquisition time reduction were reaching engineering and human limits. A brief summary of spatial encoding in MRI is followed by an introduction to the problem parallel imaging is designed to solve. There are a large number of parallel reconstruction algorithms; this article reviews a cross-section, SENSE, SMASH, g-SMASH and GRAPPA, selected to demonstrate the different approaches. Theoretical (the g-factor) and practical (coil design) limits to acquisition speed are reviewed. The practical implementation of parallel imaging is also discussed, in particular coil calibration. How to recognize potential failure modes and their associated artefacts are shown. Well-established applications including angiography, cardiac imaging and applications using echo planar imaging are reviewed and we discuss what makes a good application for parallel imaging. Finally, active research areas where parallel imaging is being used to improve data quality by repairing artefacted images are also reviewed.

A NEW METHOD FOR DATA ACQUISITION AND IMAGE RECONSTRUCTION IN PARALLEL MAGNETIC RESONANCE IMAGING

We propose a novel data acquisition and image reconstruction method for parallel magnetic resonance imaging (MRI). The proposed method improves the GRAPPA (Generalized Auto-calibrating Partially Parallel Acquisitions) method by simultaneously collecting data using the body coil in addition to localized surface coils. The body coil data is included in the GRAPPA reconstruction as an additional coil. The reconstructed body coil image shows greater uniformity over the field of view than the conventional sum-of-squares reconstruction that is conventionally used with GRAPPA. The body coil image can also be used to correct for spatial inhomogeneity in the sum-of-squares image. The proposed method is tested using numerical and real MRI phantom data.

Radiofrequency detector coil performance maps for parallel MRI applications

2006

Parallel MRI techniques allow acceleration of MR imaging beyond traditional speed limits. In parallel MRI, arrays of radiofrequency (RF) detector coil arrays are used to perform some degree of spatial encoding which complements traditional encoding using magnetic field gradients. As the acceleration factor increases, coil design becomes critical to the overall image quality. The quality of a design is commonly judged on how it compares with other coil configurations.

New approach for data acquisition and image reconstruction in parallel magnetic resonance imaging

2009

In this study, we propose a novel data acquisition and image reconstruction method for parallel magnetic resonance imaging (MRI). The proposed method improves the GRAPPA algorithm by simultaneously collecting data using the body coil in addition to localized surface coils. The body coil data is included in the GRAPPA reconstruction as an additional coil. The reconstructed body coil image shows greater uniformity over the field of view than the conventional sum-of-squares (SoS) reconstruction that is conventionally used with GRAPPA. The body coil image can also be used to correct for spatial inhomogeneity in the SoS image. The algorithm has been tested using numerical and real MRI phantom data.

Highly parallel volumetric imaging with a 32-element RF coil array

Magnetic Resonance in Medicine, 2004

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.

Rapid Volumetric MRI Using Parallel Imaging With Order-of-Magnitude Accelerations and a 32-Element RF Coil Array

Academic Radiology, 2005

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.