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

Cardiac stress MR imaging with dobutamine

Stress testing for detection of ischemia-induced wall-motion abnormalities has become a mainstay for noninvasive diagnosis and risk stratification of patients with suspected coronary artery disease (CAD). Recent technical developments in magnetic resonance imaging (MRI), including the adoption of balanced steady-state free precession (b-SSFP) sequences-preferentially in combination with parallel imaging techniques-have led to a significant reduction of imaging time and improved patient safety. The stress protocol includes application of high-dose dobutamine (up to 40 microg/kg/min) combined with fractionated atropine (up to a maximal dose of 1.0 mg). High-dose dobutamine stress MRI revealed good sensitivity (83-96%) and specificity (80-100%) for detection of significant CAD. Myocardial tagging methods have been shown to further increase sensitivity for CAD detection. Severe complications (sustained tachycardia, ventricular fibrillation, myocardial infarction, cardiogenic shock) are rare but may be expected in 0.1-0.3% of patients. Dobutamine stress MRI has emerged as a reliable and safe clinical alternative for noninvasive assessment of CAD. New pulse sequences, such as real-time imaging, might obviate the need for breath holding and electrocardiogram (ECG) triggering in patients with severe dyspnoea and cardiac arrhythmias, which may further improve the clinical impact and acceptance of stress MRI in the future.

Advances in locally constrained k-space-based parallel MRI

In this article, several theoretical and methodological developments regarding k-space-based, locally constrained parallel MRI (pMRI) reconstruction are presented. A connection between Parallel MRI with Adaptive Radius in k-Space (PARS) and GRAPPA methods is demonstrated. The analysis provides a basis for unified treatment of both methods. Additionally, a weighted PARS reconstruction is proposed, which may absorb different weighting strategies for improved image reconstruction. Next, a fast and efficient method for pMRI reconstruction of data sampled on non-Cartesian trajectories is described. In the new technique, the computational burden associated with the numerous matrix inversions in the original PARS method is drastically reduced by limiting direct calculation of reconstruction coefficients to only a few reference points. The rest of the coefficients are found by interpolating between the reference sets, which is possible due to the similar configuration of points participating in reconstruction for highly symmetric trajectories, such as radial and spirals. As a result, the time requirements are drastically reduced, which makes it practical to use pMRI with non-Cartesian trajectories in many applications. The new technique was demonstrated with simulated and actual data sampled on radial trajectories.

Parallel imaging in cardiovascular MRI: methods and applications

Cardiovascular MR imaging (CVMR) has become a valuable modality for the non-invasive detection and characterization of cardiovascular diseases. CVMR requires high imaging speed and efficiency, which is fundamentally limited in conventional cardiovascular MRI studies. With the introduction of parallel imaging, alternative means for increasing acquisition speed beyond these limits have become available. In parallel imaging some image data are acquired simultaneously, using RF detector coil sensitivities to encode simultaneous spatial information that complements the information gleaned from sequential application of magnetic field gradients. The resulting improvements in imaging speed can be used in various ways, including shortening long examinations, improving spatial resolution and/or anatomic coverage, improving temporal resolution, enhancing image quality, overcoming physiological constraints, detecting and correcting for physiologic motion, and streamlining work flow. Examples of each of these strategies will be provided in this review. First, basic principles and key concepts of parallel MR are described. Second, practical considerations such as coil array design, coil sensitivity calibrations, customized pulse sequences and tailored imaging parameters are outlined. Next, cardiovascular applications of parallel MR are reviewed, ranging from cardiac anatomical and functional assessment to myocardial perfusion and viability to MR angiography of the coronary arteries and the large vessels. Finally, current trends and future directions in parallel CVMR are considered.

Generalized encoding through the use of selective excitation in accelerated parallel MRI

Selective RF excitation is employed in magnetic resonance imaging (MRI) to achieve a variety of effects, such as slice selection. More elaborate transverse magnetization patterns can be realized via tailored RF excitation pulses, useful for example to image any specific region geometry within the field of view, or, to acquire non-Fourier encoded samples of the underlying magnetization distribution. In this manuscript, we review prior work on the combination of selective RF excitation with parallel MRI acquisition techniques. This combination can be used both to advantageously manipulate the numerical conditioning of the reconstruction problem, as well as to compact the information content of the acquired data so as to improve the achievable acceleration rate. With the latter application it is possible to also consider the acceleration provided by parallel imaging alone as a compaction of information content, which in certain cases can be used to reduce the length of the selective excitations. The main contribution of this review is to show how the combination of selective excitation with parallel imaging provides the latter an added flexibility that can be used to either enhance image quality, increase imaging speed, or both.

Potential and feasibility of parallel MRI at high field

This survey focuses on the fusion of two major lines of recent progress in MRI methodology: parallel imaging with receiver coil arrays and the transition to high and ultra-high field strength for human applications. As discussed in this paper, combining the two developments has vast potential due to multiple specific synergies. First, parallel acquisition and high field are highly complementary in terms of their individual advantages and downsides. As a consequence, the joint approach generally offers enhanced flexibility in the design of scanning strategies. Second, increasing resonance frequency changes the electrodynamics of the MR signal in such a way that parallel imaging becomes more effective in large objects. The underlying conceptual and theoretical considerations are reviewed in detail. In further sections, technical challenges and practical aspects are discussed. The feasibility of parallel MRI at ultra-high field is illustrated by current results of parallel human MRI at 7 T.

Autocalibrated coil sensitivity estimation for parallel imaging

Parallel imaging has proven to be a robust solution to the problem of acquisition speed in MRI. These methods are based on extracting spatial information from an array of multiple surface coils in order to speed up image acquisition. One of the most essential elements of any parallel imaging method is the information describing the coil sensitivity distribution throughout the sample. This paper covers some of the advanced methods to obtain coil sensitivity-related information, focusing particularly on the class of methods referred to as autocalibrating. These methods all acquire the data for coil sensitivity estimation directly before, during or directly after the reduced data acquisition. After a review of standard methods for coil sensitivity estimation, some of the basic and advanced autocalibrating methods are reviewed, and some example applications shown.

Encoding and reconstruction in parallel MRI

The advent of parallel MRI over recent years has prompted a variety of concepts and techniques for performing parallel imaging. A main distinguishing feature among these is the specific way of posing and solving the problem of image reconstruction from undersampled multiple-coil data. The clearest distinction in this respect is that between k-space and image-domain methods. The present paper reviews the basic reconstruction approaches, aiming to emphasize common principles along with actual differences. To this end the treatment starts with an elaboration of the encoding mechanisms and sampling strategies that define the reconstruction task. Based on these considerations a formal framework is developed that permits the various methods to be viewed as different solutions of one common problem. Besides the distinction between k-space and image-domain approaches, special attention is given to the implications of general vs lattice sampling patterns. The paper closes with remarks concerning noise propagation and control in parallel imaging and an outlook upon key issues to be addressed in the future.

k-space inherited parallel acquisition (KIPA): application on dynamic magnetic resonance imaging thermometry

In this study, a novel method for dynamic parallel image acquisition and reconstruction is presented. In this method, called k-space inherited parallel acquisition (KIPA), localized reconstruction coefficients are used to achieve higher reduction factors, and lower noise and artifact levels compared to that of generalized autocalibrating partially parallel acquisition (GRAPPA) reconstruction. In KIPA, the full k-space for the first frame and the partial k-space for later frames are required to reconstruct a whole series of images. Reconstruction coefficients calculated for different segments of k-space from the first frame data set are used to estimate missing k-space lines in corresponding k-space segments of other frames. The local determination of KIPA reconstruction coefficients is essential to adjusting them according to the local signal-to-noise ratio characteristics of k-space data. The proposed algorithm is applicable to dynamic imaging with arbitrary k-space sampling trajectories. Simulations of magnetic resonance thermometry using the KIPA method with a reduction factor of 6 and using dynamic imaging studies of human subjects with reduction factors of 4 and 6 have been performed to prove the feasibility of our method and to show apparent improvement in image quality in comparison with GRAPPA for dynamic imaging.

Analytically exact correction scheme for signal extraction from noisy magnitude MR signals

An analytically exact method is proposed to extract the signal intensity and the noise variance simultaneously from noisy magnitude MR signals. This method relies on a fixed point formula of signal-to-noise ratio (SNR) and a correction factor. The correction factor, which is a function of SNR, establishes a fundamental link between the variance of the magnitude MR signal and the variance of the underlying Gaussian noise in the two quadrature channels. A more general but very similar method is developed for parallel signal acquisitions with multiple receiver coils. In the context of MR imaging, the proposed method can be carried out on a pixel-by-pixel basis if the mean and the standard deviation of the magnitude signal are available.

Parallel magnetic resonance imaging using the GRAPPA operator formalism

In this article it is shown that GRAPPA reconstruction can be reformulated as a matrix operator, similar to ladder or propagator operators used in quantum mechanics, that shifts data in k-space. Using this formalism, it is shown that there exists an infinitesimal GRAPPA operator that shifts data in k-space by arbitrarily small amounts. Other desired k-space shifts can then be accomplished through repeated applications of this infinitesimal GRAPPA operator. Implications of these ideas are described.

Minimum-norm reconstruction for sensitivity-encoded magnetic resonance spectroscopic imaging

In this work we propose minimum-norm reconstruction as a means to enhance the spatial response behavior in parallel spectroscopic MRI. By directly optimizing the shape of the spatial response function (SRF), the new method accounts for coil sensitivity variation across individual voxels and their side lobes. In this fashion, it mitigates the signal contamination and side-lobe aliasing, to which previous techniques are susceptible at low resolution. Although the computational burden is higher, minimum-norm reconstruction is shown to be feasible using an iterative algorithm. Benefits in terms of SRF shape and artifact suppression are demonstrated.

Controlled aliasing in volumetric parallel imaging (2D CAIPIRINHA)

The CAIPIRINHA (Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration) concept in parallel imaging has recently been introduced, which modifies the appearance of aliasing artifacts during data acquisition in order to improve the subsequent parallel imaging reconstruction procedure. This concept has been successfully applied to simultaneous multi-slice imaging (MS CAIPIRINHA). In this work, we demonstrate that the concept of CAIPIRINHA can also be transferred to 3D imaging, where data reduction can be performed in two spatial dimensions simultaneously. In MS CAIPIRINHA, aliasing is controlled by providing individual slices with different phase cycles by means of alternating multi-band radio frequency (RF) pulses. In contrast to MS CAIPIRINHA, 2D CAIPIRINHA does not require special RF pulses. Instead, aliasing in 2D parallel imaging can be controlled by modifying the phase encoding sampling strategy. This is done by shifting sampling positions from their normal positions in the under-sampled 2D phase encoding scheme. Using this modified sampling strategy, coil sensitivity variations can be exploited more efficiently in multiple dimensions, resulting in a more robust parallel imaging reconstruction.

Discrepancy-based adaptive regularization for GRAPPA reconstruction

PURPOSE

To develop a novel regularization method for GRAPPA by which the regularization parameters can be optimally and adaptively chosen.

MATERIALS AND METHODS

In the fit procedures in GRAPPA, the discrepancy principle, which chooses the regularization parameter based on a priori information about the noise level in the autocalibrating signals (ACS), is used with the truncated singular value decomposition (TSVD) regularization and the Tikhonov regularization, and its performance is compared with the singular value (SV) threshold method and the L-curve method, respectively by axial and sagittal head imaging experiments.

RESULTS

In both axial and sagittal reconstructions, normal GRAPPA reconstruction results exhibit a relatively high level of noise. With discrepancy-based choices of parameters, regularization can improve the signal-to-noise ratio (SNR) with only a very modest increase in aliasing artifacts. The L-curve method in all of the reconstructions leads to overregularization, which causes severe residual aliasing artifacts. The 10% SV threshold method yields good overall image quality in the axial case, but in the sagittal case it also leads to an obvious increase in aliasing artifacts.

CONCLUSION

Neither a fixed SV threshold nor the L-curve are robust means of choosing the appropriate parameters in GRAPPA reconstruction. However, with the discrepancy-based parameter-choice strategy, adaptively regularized GRAPPA can be used to automatically choose nearly optimal parameters for reconstruction and achieve an excellent compromise between SNR and artifacts.

Common SENSE (sensitivity encoding using hardware common to all MR scanners): a new method for single-shot segmented echo planar imaging

A new method is presented that enables image acquisition to be segmented into two readouts. This is achieved using a new pulse sequence that creates two components of magnetization with different spatial profiles. Each component of the magnetization is measured in one of the readouts. This produces two images with complimentary "sensitivity profiles" and near identical contrast. The images can be acquired with a reduced data matrix that corresponds to shorter periods of data acquisition. The reduced matrix images are then combined to produce a full matrix image using reconstruction methods previously applied to images from multiple RF coils in the sensitivity encoding (SENSE) technique. The most promising application for this technique is in improving the performance of echo planar imaging (EPI) at high field. In this application, common SENSE obtains two segments of data in a single excitation of the magnetization (i.e., two readouts are performed per shot). The combination of these segments in image space avoids the difficulties normally associated with segmented EPI methods, namely, increased ghosting from discontinuities in the k-space data. The main advantages are a reduction in distortion and blurring. Common SENSE is compatible with parallel imaging and partial Fourier methods.

Phase-constrained parallel MR image reconstruction

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.

Focused, eight-element transceive phased array coil for parallel magnetic resonance imaging of the chest--theoretical considerations

A new transceive system for chest imaging for MRI applications is presented. A focused, eight-element transceive torso phased array coil is designed to investigate transmitting a focused radiofrequency field deep within the torso and to enhance signal homogeneity in the heart region. The system is used in conjunction with the SENSE reconstruction technique to enable focused parallel imaging. A hybrid finite-difference-time-domain/method-of-moments method is used to accurately predict the radiofrequency behavior inside the human torso. The simulation results reported herein demonstrate the feasibility of the design concept, which shows that radiofrequency field focusing with SENSE reconstruction is theoretically achievable.

A review of technical advances in interventional magnetic resonance imaging

Initial research in the development of interventional magnetic resonance (MR) imaging in the late 1980s and early to mid-1990s focused on pulse sequences, devices, and clinical applications. This focus was largely a result of the limited number of areas in which the academic research community leading the development could provide innovation on the MR systems of the time. However, during the past decade, computational power, higher bandwidth graphical displays, faster computer networks, improved pulse sequence architectures, and improved technical specifications have accelerated the pace of development on modern MR systems. Today, it is the combination of multiple system factors that are enabling the future of interventional MR. These developments, their impact on the field, and newly emerging applications are described.

Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA)

Current parallel imaging techniques for accelerated imaging require a fully encoded reference data set to estimate the spatial coil sensitivity information needed for reconstruction. In dynamic parallel imaging a time-interleaved acquisition scheme can be used, which eliminates the need for separately acquiring additional reference data, since the signal from directly adjacent time frames can be merged to build a set of fully encoded full-resolution reference data for coil calibration. In this work, we demonstrate that a time-interleaved sampling scheme, in combination with autocalibrated GRAPPA (referred to as TGRAPPA), allows one to easily update the coil weights for the GRAPPA algorithm dynamically, thereby improving the acquisition efficiency. This method may update coil sensitivity estimates frame by frame, thereby tracking changes in relative coil sensitivities that may occur during the data acquisition.

Comparison of different methods for combining phase-contrast images obtained with multiple coils

The ability to determine coil sensitivities implies that a method optimized in terms of maximized signal-to-noise ratio (SNR) can be applied to the combination of multiple coil images. An optimization of SNR subsequently results in a minimized variance in quantitative velocity measurements using phase-contrast imaging. When coil sensitivities are unknown, the weighted mean method, utilizing the square of the signal magnitude as weights, is suitable for combination of multiple phase images. In this study, the optimized method using estimated coil sensitivities was compared to the weighted mean method both theoretically and experimentally. It is shown that absence of noise correlation between the different coil images implies no difference between the methods regarding the variance of the phase. In the practical situation, noise correlation does exist, implying an opportunity for further reduction of phase variance using the optimized method. In vitro and in vivo studies showed, however, no significant difference between the two methods studied.

Partially parallel imaging with phase-sensitive data: Increased temporal resolution for magnetic resonance temperature imaging

Magnetic resonance temperature imaging can be used to monitor the progress of thermal ablation therapies, increasing treatment efficacy and improving patient safety. High temporal resolution is important when therapies rapidly heat tissue, but many approaches to faster image acquisition compromise image resolution, slice coverage, or phase sensitivity. Partially parallel imaging techniques offer the potential for improved temporal resolution without forcing such concessions. Although these techniques perturb image phase, relative phase changes between dynamically acquired phase-sensitive images, such as those acquired for MR temperature imaging, can be reliably measured through partially parallel imaging techniques using reconstruction filters that remain constant across the series. Partially parallel and non-accelerated phase-difference-sensitive data can be obtained through arrays of surface coils using this method. Average phase differences measured through partially parallel and fully Fourier encoded images are virtually identical, while phase noise increases with g(sqrt)L as in standard partially parallel image acquisitions..

Tailored utilization of acquired k-space points for GRAPPA reconstruction

The generalized auto-calibrating partially parallel acquisition (GRAPPA) is an auto-calibrating parallel imaging technique which incorporates multiple blocks of data to derive the missing signals. In the original GRAPPA reconstruction algorithm only the data points in phase encoding direction are incorporated to reconstruct missing points in k-space. It has been recognized that this scheme can be extended so that data points in readout direction are also utilized and the points are selected based on a k-space locality criterion. In this study, an automatic subset selection strategy is proposed which can provide a tailored selection of source points for reconstruction. This novel approach extracts a subset of signal points corresponding to the most linearly independent base vectors in the coefficient matrix of fit, effectively preventing incorporating redundant signals which only bring noise into reconstruction with little contribution to the exactness of fit. Also, subset selection in this way has a regularization effect since the vectors corresponding to the smallest singular values are eliminated and consequently the condition of the reconstruction is improved. Phantom and in vivo MRI experiments demonstrate that this subset selection strategy can effectively improve SNR and reduce residual artifacts for GRAPPA reconstruction.

Field-of-view limitations in parallel imaging

Parallel imaging is one of the most promising developments in recent years for the acceleration of MR acquisitions. One area of practical importance where different parallel imaging methods perform differently is the manner in which they deal with aliasing in the full-FOV reconstructed image. It has been reported that sensitivity encoding (SENSE) reconstruction fails whenever the reconstructed FOV is smaller than the object being imaged. On the other hand, generalized autocalibrating partially parallel acquisition (GRAPPA) has been used successfully to reconstruct images with aliasing in the reconstructed FOV, as in conventional imaging. The disparate behavior of these methods can be easily demonstrated by a few simple illustrative examples. Additional in vivo examples using GRAPPA and modified SENSE (mSENSE) make this distinction clear. These experiments demonstrate that SENSE fails to reconstruct correct images when coil sensitivity maps are used that do not automatically account for the object size and therefore the aliasing in the reconstructed images. However, with the use of aliased high-resolution coil sensitivity maps, accurate SENSE reconstructions can be generated. On the other hand, GRAPPA produces images with an aliasing appearance that is exactly as would be expected from normal nonaccelerated acquisitions. An understanding of these effects could potentially lead to fewer operator-dependent errors, as well as a better understanding of the differences between the underlying reconstruction processes.

Parallel imaging performance as a function of field strength--an experimental investigation using electrodynamic scaling

In this work, the dependence of parallel MRI performance on main magnetic field strength is experimentally investigated. Using the general framework of electrodynamic scaling, the B0-dependent behavior of the relevant radiofrequency fields at a single physical field strength of 7 T is studied. In the chosen implementation this is accomplished by adjusting the permittivity and conductivity of a homogeneous spherical phantom. With different mixing ratios of decane, ethanol, purified water, N-methylformamide, and sodium chloride, field strengths in the range of 1.5 to 11.5 T are mimicked. Based on sensitivity maps of an eight-coil receiver array, the field-dependent performance of parallel imaging is assessed in terms of the geometry factor g, which reflects noise enhancement in parallel imaging reconstruction. At low field strengths the SNR penalty was nearly independent of B0 and favorably low for 1D reduction factors up to between 3 and 4. At higher field strengths the transition between favorable and prohibitive parallel imaging conditions was found to shift toward higher feasible reduction factors. These findings are in good agreement with previous theoretical predictions. From this agreement it is concluded that parallel MRI at high B0 benefits specifically from onsetting far-field behavior of the involved radiofrequency fields.

Large field-of-view real-time MRI with a 32-channel system

The emergence of parallel MRI techniques and new applications for real-time interactive MRI underscores the need to evaluate performance gained by increasing the capability of MRI phased-array systems beyond the standard four to eight high-bandwidth channels. Therefore, to explore the advantages of highly parallel MRI a 32-channel 1.5 T MRI system and 32-element torso phased arrays were designed and constructed for real-time interactive MRI. The system was assembled from multiple synchronized scanner-receiver subsystems. Software was developed to coordinate across subsystems the real-time acquisition, reconstruction, and display of 32-channel images. Real-time, large field-of-view (FOV) body-survey imaging was performed using interleaved echo-planar and single-shot fast-spin-echo pulse sequences. A new method is demonstrated for augmenting parallel image acquisition by independently offsetting the frequency of different array elements (FASSET) to variably shift their FOV. When combined with conventional parallel imaging techniques, image acceleration factors of up to 4 were investigated. The use of a large number of coils allowed the FOV to be doubled in two dimensions during rapid imaging, with no degradation of imaging time or spatial resolution. The system provides a platform for evaluating the applications of many-channel real-time MRI, and for understanding the factors that optimize the choice of array size.

64-channel array coil for single echo acquisition magnetic resonance imaging

A 64-channel array coil for magnetic resonance imaging (MRI) has been designed and constructed. The coil was built to enable the testing of a new imaging method, single echo acquisition (SEA) MRI, in which an independent full image is acquired with every echo. This is accomplished by entirely eliminating phase encoding and instead using the spatial information obtained from an array of very narrow, long, parallel coils. The planar pair element design proved to be key in achieving well-localized field sensitivity patterns and isolated elements, the crucial requirements for performing SEA. The matching and tuning of the array elements were accomplished on the coil array printed circuit board using varactor diodes biased over the RF lines. The array was successfully used to obtain SEA images as well as conventional partially parallel images at unprecedented acceleration factors.

Accelerating MRI by skipped phase encoding and edge deghosting (SPEED)

A fast imaging method called skipped phase encoding and edge deghosting (SPEED) is introduced. The k-space is sparsely sampled into three interleaved datasets, each with a skip-size N and a relative shift in phase encoding (PE). These datasets are separately reconstructed by 2DFT and edge-enhanced by a differential filter in the PE direction, resulting in edge maps with phase-shifted aliasing ghosts. The sparseness of edges reduces the chance of ghost overlapping. Typical ghosted-edge maps can be adequately modeled with only two dominating ghost layers that are resolved from a set of three equations using least-square error minimization, yielding N ghost maps of different orders that can be registered and averaged into a single deghosted-edge map for noise and artifact reduction. Finally, the deghosted-edge map is transformed into a deghosted image by an inverse filter. A few central k-space lines are collected without PE skip to aid the inverse filtering. SPEED has been demonstrated by in vivo data to reduce scan time considerably without noticeable artifacts. It has various potential applications, such as MR angiography (MRA), where the signal itself is sparse. As an independent method, SPEED can be combined with other fast imaging methods for further acceleration.

Partial fourier partially parallel imaging

The techniques of partial Fourier (PF) and partially parallel imaging have been combined using a constrained reconstruction technique. The benefits compared with the individual techniques are reduced imaging time and/or an increase in signal-to-noise ratio. Low-resolution phase maps and coil sensitivities may be obtained using autocalibration or from a prescan followed by additional processing. Minor phase artifacts that are introduced by relying on conjugate symmetry can be reduced using a novel regularization scheme to vary the degree to which PF is used in the reconstruction. A nonrectilinear reconstruction algorithm is presented and the potential for motion artifact reduction is investigated using robust reconstruction.

Controlled aliasing in parallel imaging results in higher acceleration (CAIPIRINHA) for multi-slice imaging

In all current parallel imaging techniques, aliasing artifacts resulting from an undersampled acquisition are removed by means of a specialized image reconstruction algorithm. In this study a new approach termed "controlled aliasing in parallel imaging results in higher acceleration" (CAIPIRINHA) is presented. This technique modifies the appearance of aliasing artifacts during the acquisition to improve the subsequent parallel image reconstruction procedure. This new parallel multi-slice technique is more efficient compared to other multi-slice parallel imaging concepts that use only a pure postprocessing approach. In this new approach, multiple slices of arbitrary thickness and distance are excited simultaneously with the use of multi-band radiofrequency (RF) pulses similar to Hadamard pulses. These data are then undersampled, yielding superimposed slices that appear shifted with respect to each other. The shift of the aliased slices is controlled by modulating the phase of the individual slices in the multi-band excitation pulse from echo to echo. We show that the reconstruction quality of the aliased slices is better using this shift. This may potentially allow one to use higher acceleration factors than are used in techniques without this excitation scheme. Additionally, slices that have essentially the same coil sensitivity profiles can be separated with this technique.

Parallel imaging for NMR microscopy at 14.1 Tesla

Parallel imaging techniques using arrays of mutually decoupled coils have become standard on almost all clinical imaging systems. Such techniques also have great potential for high-field magnetic resonance (MR) microscopy, where measurement times are usually long and susceptibility artifacts can be severe. However, it is technically very challenging to design efficient high-frequency phased arrays for small-diameter, vertical-bore magnets, especially since standard decoupling methods, such as impedance mismatched preamplifiers, cannot be easily integrated. A four-coil phased array was constructed for microimaging at 600 MHz, and sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstructions of spin-echo and echo-planar images of the mouse brain were performed to reduce imaging time and susceptibility artifacts, respectively.

3Parallel magnetic resonance imaging with adaptive radius ink-space (PARS): Constrained image reconstruction usingk-space locality in radiofrequency coil encoded data

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.

SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method

Fast imaging methods and the availability of required hardware for magnetic resonance tomography (MRT) have significantly reduced acquisition times from about an hour down to several minutes or seconds. With this development over the last 20 years, magnetic resonance imaging (MRI) has become one of the most important instruments in clinical diagnosis. In recent years, the greatest progress in further increasing imaging speed has been the development of parallel MRI (pMRI). Within the last 3 years, parallel imaging methods have become commercially available, and therefore are now available for a broad clinical use. The basic feature of pMRI is a scan time reduction, applicable to nearly any available MRI method, while maintaining the contrast behavior without requiring higher gradient system performance. Because of its faster image acquisition, pMRI can in some cases even significantly improve image quality. In the last 10 years of pMRI development, several different pMRI reconstruction methods have been set up which partially differ in their philosophy, in the mode of reconstruction as well in their advantages and drawbacks with regard to a successful image reconstruction. In this review, a brief overview is given on the advantages and disadvantages of present pMRI methods in clinical applications, and examples from different daily clinical applications are shown.

Method for spatially interleaving two images to halve EPI readout times: two reduced acquisitions interleaved (TRAIL)

A new MRI method is presented that can generate images using half the normal readout time or, more usefully, half the number of phase-encode steps, combining two readouts per excitation. However, the corresponding data are interleaved in image space-not in k-space, as in many other fast techniques. This gives a resilience to the phase-related artifacts that can occur in many other techniques due to subject motion. A modified stimulated-echo experiment is used to create two low-resolution images from a single sequence. The magnetization that contributes to these images is nonuniformly distributed within each pixel, forming two sinusoidal waves in quadrature, with an oscillation period of exactly two pixels. Since only half of each pixel contributes significant signal, the two images can be interleaved to create a full image with twice as many pixels and double the resolution. When the technique is used in the phase-encode direction, the effective imaging time is halved, though with two readouts per TR period. When two half-length echo-planar readouts are used, the method can also reduce blurring and distortion by halving the effective readout time for echo-planar imaging (EPI). For even further improvements, the technique can be combined with partial Fourier or parallel imaging.

New partially parallel acquisition technique in cerebral imaging: preliminary findings

In MRI applications where short acquisition time is necessary, the increase of acquisition speed is often at the expense of image resolution and SNR. In such cases, the newly developed parallel acquisition techniques could provide images without mentioned limitations and in reasonably shortened measurement time. A newly designed eight-channel head coil array (i-PAT coil) allowing for parallel acquisition of independently reconstructed images (GRAPPA mode) has been tested for its applicability in neuroradiology. Image homogeneity was tested in standard phantom and healthy volunteers. BOLD signal changes were studied in a group of six volunteers using finger tapping stimulation. Phantom studies revealed an important drop of signal even after the use of a normalization filter in the center of the image and an important increase of artifact power with reduction of measurement time strongly depending on the combination of acceleration parameters. The additional application of a parallel acquisition technique such as GRAPPA decreases measurement time in the range of about 30%, but further reduction is often possible only at the expense of SNR. This technique performs best in conditions in which imaging speed is important, such as CE MRA, but time resolution still does not allow the acquisition of angiograms separating the arterial and venous phase. Significantly larger areas of BOLD activation were found using the i-PAT coil compared to the standard head coil. Being an eight-channel surface coil array, peripheral cortical structures profit from high SNR as high-resolution imaging of small cortical dysplasias and functional activation of cortical areas imaged by BOLD contrast. In BOLD contrast imaging, susceptibility artifacts are reduced, but only if an appropriate combination of acceleration parameters is used.

Parallel imaging at high field strength: synergies and joint potential

MRI faces fundamental limitations in terms of sensitivity and speed. These limitations can be effectively tackled by the transition to higher field strengths and parallel imaging technology. Owing to largely independent physics, the two approaches can be readily combined. Considering the specific advantages and disadvantages of high field strength and parallel imaging, it is found that the combination is particularly synergistic. In the joint approach, the two concepts play different roles. Higher field strength acts as a source of higher baseline signal-to-noise ratio (SNR), while parallelization acts as a means of converting added SNR into a variety of alternative benefits. This interplay holds promise for a broad range of clinical applications, as recently illustrated by several imaging studies at 3 T. As a consequence, clinical MRI at 3 T and higher is expected to rely more on parallel acquisition than at lower field strength. The specific synergy with parallel imaging may even make 3 T the field strength of choice for a range of exams that conventionally work best at 1.5 T or less.

Reduced data acquisition methods in cardiac imaging

In cardiac imaging, acquisition speed is of primary importance. While improved performance has mainly been achieved through improvements in gradient hardware in the past, further developments along this direction are limited due to physiological constraints such as the risk of peripheral nerve stimulation. With the introduction of parallel imaging, alternative means for increasing acquisition speed have become available. Using information from multiple receiver coils, images can be reconstructed from a sparsely sampled set of data. In practice, parallel imaging allows for 2- to 3-fold acceleration of the imaging process in typical cardiac applications. Further increases in acquisition speed are, however, difficult to achieve for current clinical field strengths and typical field of views. To address the limited gain in acquisition speed achievable with parallel imaging, a new set of methods has been proposed to take into account the similarity of image information at different time points during a dynamic series. Using these methods, 5- to 8-fold acceleration can be achieved in cardiac imaging. It is the purpose of this paper to review cardiac applications of reduced data acquisition methods with focus on parallel imaging and the recently developed k-t BLAST and k-t SENSE techniques.

Parallel Imaging in MR Angiography

The recently developed techniques of parallel imaging with phased array coils are rapidly becoming accepted for magnetic resonance angiography (MRA) applications. This article reviews the various current parallel imaging techniques and their application to MRA. The increased scan efficiency provided by parallel imaging allows increased temporal or spatial resolution, and reduction of artifacts in contrast-enhanced MRA (CE-MRA). Increased temporal resolution in CE-MRA can be used to reduce the need for bolus timing and to provide hemodynamic information helpful for diagnosis. In addition, increased spatial resolution (or volume coverage) can be acquired in a breathhold (eg, in renal CE-MRA), or in otherwise limited clinically acceptable scan durations. The increased scan efficiency provided by parallel imaging has been successfully applied to CE-MRA as well as other MRA techniques such as inflow and phase contrast imaging. The large signal-to-noise ratio available in many MRA techniques lends these acquisitions to increased scan efficiency through parallel imaging.

Auto-SENSE perfusion imaging of the whole human heart

PURPOSE

To show the application of auto-sensitivity encoding (SENSE)-a self-calibrating parallel imaging technique-to first pass perfusion imaging of the whole human heart.

MATERIALS AND METHODS

The self-calibrating parallel imaging method auto-SENSE was implemented for a saturation recovery turbo-fast low-angle shot (FLASH) sequence on a 1.5-T scanner using a standard four-element body phased array coil. By reducing the acquisition time per slice by a factor of two compared to conventional turbo FLASH imaging, the number of imaged slices could be doubled to six to ten with an unchanged temporal resolution of one image per heartbeat. This technique has been tested in eight healthy volunteers for contrast-enhanced heart perfusion imaging.

RESULTS

Auto-SENSE heart perfusion imaging with improved coverage of the human heart could be performed successfully in all volunteers. A first quantitative comparison of perfusion values between the auto-SENSE and the non-SENSE techniques shows good agreement.

CONCLUSION

Auto-SENSE allows perfusion imaging of the whole human heart without gaps.

Electrodynamics and ultimate SNR in parallel MR imaging

The purpose of this article is to elucidate inherent limitations to the performance of parallel MRI. The study focuses on the ultimate signal-to-noise ratio (SNR), which refers to the maximum SNR permitted by the electrodynamics of the signal detection process. Using a spherical model object, it is shown that the behavior of the ultimate SNR imposes distinct limits on the acceleration rate in parallel imaging. For low and moderate acceleration, the ultimate SNR performance is nearly optimal, with geometry factors close to 1. However, for high reduction factors beyond a critical value, the ultimate performance deteriorates rapidly, corresponding to exponential growth of the geometry factor. The transition from optimal to deteriorating performance depends on the electrodynamic characteristics of the detected RF fields. In the near-field regime, i.e., for low B0 and small object size, the critical reduction factor is constant and approximately equal to four for 1D acceleration in the sphere. In the far-field wave regime the critical reduction factor is larger and increases both with B0 and object size. Therefore, it is concluded that parallel techniques hold particular promise for human MR imaging at very high field.

Noise-adaptive nonlinear diffusion filtering of MR images with spatially varying noise levels

Anisotropic diffusion filtering is widely used for MR image enhancement. However, the anisotropic filter is nonoptimal for MR images with spatially varying noise levels, such as images reconstructed from sensitivity-encoded data and intensity inhomogeneity-corrected images. In this work, a new method for filtering MR images with spatially varying noise levels is presented. In the new method, a priori information regarding the image noise level spatial distribution is utilized for the local adjustment of the anisotropic diffusion filter. Our new method was validated and compared with the standard filter on simulated and real MRI data. The noise-adaptive method was demonstrated to outperform the standard anisotropic diffusion filter in both image error reduction and image signal-to-noise ratio (SNR) improvement. The method was also applied to inhomogeneity-corrected and sensitivity encoding (SENSE) images. The new filter was shown to improve segmentation of MR brain images with spatially varying noise levels.

Non-Fourier-encoded parallel MRI using multiple receiver coils

This paper describes a general theoretical framework that combines non-Fourier (NF) spatially-encoded MRI with multichannel acquisition parallel MRI. The two spatial-encoding mechanisms are physically and analytically separable, which allows NF encoding to be expressed as complementary to the inherent encoding imposed by RF receiver coil sensitivities. Consequently, the number of NF spatial-encoding steps necessary to fully encode an FOV is reduced. Furthermore, by casting the FOV reduction of parallel imaging techniques as a dimensionality reduction of the k-space that is NF-encoded, one can obtain a speed-up of each digital NF spatial excitation in addition to accelerated imaging. Images acquired at speed-up factors of 2x to 8x with a four-element RF receiver coil array demonstrate the utility of this framework and the efficiency afforded by it.

Stroke patients' evolving symptoms assessed by tractography

PURPOSE

To test the hypothesis that an interval evolution in the location of the depicted sensorimotor tract relative to the infarct (the "tract-infarct relationship") may be related to stroke victims' symptom progression.

MATERIALS AND METHODS

Patients (N = 7) who underwent multiple diffusion-tensor imaging (DTI) studies during symptomatic progression were included in this study. DTI was performed using a single-shot echo-planar imaging (EPI) technique with a motion-probing gradient in six orientations, a b-value of 800 seconds/mm2, and six image averages. The total scan time was four minutes and 24 seconds. Fiber-tracking of the sensorimotor pathways was performed, and the locations of these tracts were retrospectively assessed in relation to the evolution of the symptoms.

RESULTS

Five of the seven patients showed an interval enlargement of the infarct on diffusion-weighted (DW) images. In two of these cases the lesion enlarged to involve the sensorimotor tracts, while in three cases the lesion enlarged only so far to come into close proximity to the sensorimotor tract. In the remaining two cases there was no interval enlargement of the infarct, and therefore the tract-infarct relationship could not account for the evolution of the symptoms in these cases.

CONCLUSION

A tract-infarct relationship can be observed with the use of a fiber-tracking technique, and the results may improve our understanding of the symptom progression seen in stroke victims.

UNFOLD-SENSE: A parallel MRI method with self-calibration and artifact suppression

This work aims at improving the performance of parallel imaging by using it with our "unaliasing by Fourier-encoding the overlaps in the temporal dimension" (UNFOLD) temporal strategy. A self-calibration method called "self, hybrid referencing with UNFOLD and GRAPPA" (SHRUG) is presented. SHRUG combines the UNFOLD-based sensitivity mapping strategy introduced in the TSENSE method by Kellman et al. (5), with the strategy introduced in the GRAPPA method by Griswold et al. (10). SHRUG merges the two approaches to alleviate their respective limitations, and provides fast self-calibration at any given acceleration factor. UNFOLD-SENSE further includes an UNFOLD artifact suppression scheme to significantly suppress artifacts and amplified noise produced by parallel imaging. This suppression scheme, which was published previously (4), is related to another method that was presented independently as part of TSENSE. While the two are equivalent at accelerations < or = 2.0, the present approach is shown here to be significantly superior at accelerations > 2.0, with up to double the artifact suppression at high accelerations. Furthermore, a slight modification of Cartesian SENSE is introduced, which allows departures from purely Cartesian sampling grids. This technique, termed variable-density SENSE (vdSENSE), allows the variable-density data required by SHRUG to be reconstructed with the simplicity and fast processing of Cartesian SENSE. UNFOLD-SENSE is given by the combination of SHRUG for sensitivity mapping, vdSENSE for reconstruction, and UNFOLD for artifact/amplified noise suppression. The method was implemented, with online reconstruction, on both an SSFP and a myocardium-perfusion sequence. The results from six patients scanned with UNFOLD-SENSE are presented.

POCSENSE: POCS-based reconstruction for sensitivity encoded magnetic resonance imaging

A novel method for iterative reconstruction of images from undersampled MRI data acquired by multiple receiver coil systems is presented. Based on Projection onto Convex Sets (POCS) formalism, the method for SENSitivity Encoded data reconstruction (POCSENSE) can be readily modified to include various linear and nonlinear reconstruction constraints. Such constraints may be beneficial for reconstructing highly and overcritically undersampled data sets to improve image quality. POCSENSE is conceptually simple and numerically efficient and can reconstruct images from data sampled on arbitrary k-space trajectories. The applicability of POCSENSE for image reconstruction with nonlinear constraining was demonstrated using a wide range of simulated and real MRI data.

A brief review of parallel magnetic resonance imaging

Since the 1980s, the implementation of fast imaging methods and dedicated hardware for MRI scanners has reduced the image acquisition time from nearly an hour down to several seconds and has therefore enabled a widespread use of MRI in clinical diagnosis. Since this development, the greatest incremental gain in imaging speed has been provided by the development of parallel MRI (pMRI) techniques in late 1990s. Within the past 2 years, parallel imaging methods have become commercially available, which means that pMRI is now available for broad clinical use. In the clinical routine, virtually any MRI method can be enhanced by pMRI, allowing faster image acquisitions without any increased gradient system performance. In some cases pMRI can even result in a significant gain in image quality due to this faster acquisition. In this review article, the advantages and the disadvantages of pMRI in clinical applications are discussed and examples from many different daily applications are given.

Fiber-tracking method reveals sensorimotor pathway involvement in stroke patients

BACKGROUND AND PURPOSE

We tested the feasibility of a new MRI technique that provides visualization of the sensorimotor tracts in vivo in a group of stroke victims.

SUMMARY OF REPORT

Fourteen patients with small infarctions involving the white matter of the supratentorial brain were evaluated. Sensorimotor tracts on the lesional and contralesional sides were successfully depicted in all cases. The position of the sensorimotor tracts relative to the infarct was in good agreement with clinical symptoms. The overall sensitivity and specificity for sensorimotor tract involvement were 100% and 77%, respectively.

CONCLUSIONS

Our proposed fiber-tracking method was shown to be a clinically feasible technique that correlates well with clinical symptoms.

Rapid MR imaging by sensitivity profile indexing and deconvolution reconstruction (SPID)

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.

[Assessment of axonal degeneration on Alzheimer's disease with diffusion tensor MRI]

PURPOSE

Alzheimer disease (AD) causes cortical degeneration with subsequent degenerative changes of the white matter. The aim of this study was to investigate the extent of white matter tissue damage of patients with Alzheimer's disease in comparison with healthy subjects using diffusion tensor MRI (DTI). The value of integrated parallel imaging techniques (iPAT) for reduction of image distortion was assessed.

MATERIAL AND METHODS

We studied 9 patients with mild AD and 10 age and gender matched healthy controls. DTI brain scans were obtained on a 1.5 tesla system (Siemens Magnetom Sonata) using parallel imaging (iPAT) and an EPI diffusion sequence with TE/TR 71 ms/6000 ms. We used an 8-element head coil and a GRAPPA reconstruction algorithm with an acceleration factor of 2. From the tensor, the mean diffusivity (D), the fractional anisotropy (FA), and the relative anisotropy (RA) of several white matter regions were determined.

RESULTS

FA was significantly lower (p <0,05) in the white matter of the genu of corpus callosum from patients with AD than in the corresponding regions from healthy controls. There was a trend observed for slightly higher ADC values in the AD group (p=0,06). No significant changes were observed in the regions of the splenium, internal capsule, pericallosal areas, frontal, temporal, parietal, and occipital lobe. The images obtained with iPAT contained substantially less susceptibility artefacts and were less distorted than images acquired with non-parallel imaging technique.

CONCLUSIONS

DTI is a method with potential to assess early stages of white matter damage in vivo. The altered FA and ADC values in the genu of corpus callosum of patients with AD presumably reflect the microscopic white matter degeneration. Acquisition time can be reduced by iPAT methods with less image distortion from susceptibility artefacts resulting in a more accurate calculation of the diffusion tensor.

CT versus MR in neonatal brain imaging at term

BACKGROUND

Recent reports have highlighted the lifetime risk of malignancy from using ionizing radiation in pediatric imaging. Computed tomography (CT), which uses ionizing radiation, is employed extensively for neonatal brain imaging of term infants. Magnetic resonance (MR) provides an alternative that does not use ionizing radiation.

OBJECTIVE

The purpose of this study was to assess the cross-modality agreement and interobserver agreement of CT and MR brain imaging of the term or near-term neonate.

MATERIALS AND METHODS

Brain CT and MR images of 48 neonates were retrospectively reviewed by two pediatric neuroradiologists. CT and MR examinations had been obtained within 72 h of one another in all patients. CT was obtained with 5 mm collimation (KV=120, mAs=340). MR consisted of T1-weighted imaging (TR/TE=300/14; 4-mm slice thickness/1-mm gap), T2-weighted imaging (TR/TE/etl= 3000/126/16; 4-mm slice thickness/1-mm gap), and line scan diffusion imaging (LSDI) (TR/TE/b factor=1258/63/750; nominal 4-mm slice thickness/3-mm gap). The brain was categorized as normal or abnormal on both CT and MR.

RESULTS

Ischemic injury was the most common brain abnormality demonstrated. McNemar's test indicated no significant difference between CT and MR test results for reader 1 (P=0.22) or reader 2 (P=0.45). The readers agreed on the presence or absence of abnormality on CT in 40 patients (83.3%) and on MR in 45 patients (93.8%). For CT, the kappa coefficient indicated excellent interobserver agreement (kappa=0.68), although the lower limit of the 95% confidence interval extends to kappa=0.55, which indicates only good-to-moderate agreement. For MR, the kappa coefficient indicated almost perfect interobserver agreement (kappa=0.88) with the 95% confidence interval extending to a lower limit of kappa=0.76, which represents excellent agreement. CONCLUSION. Because MR demonstrates findings similar to CT and has greater interobserver agreement, it appears that MR is a superior test to CT in determining brain abnormalities in the term neonate. Furthermore, since MR eliminates the use of ionizing radiation, a putative cause of malignancy, it should be the standard in neonatal brain imaging. Future efforts should be directed to improving neonatal access to MR to avoid the routine use of CT in infants.

Brain fiber tracking with clinically feasible diffusion-tensor MR imaging: initial experience

Two technical challenges must be overcome before brain fiber tracking with diffusion-tensor magnetic resonance (MR) imaging can be applied to clinical practice: Imaging time must be shortened, and image distortion must be minimized. Single-shot echo-planar MR imaging with parallel imaging technique enabled both objectives to be accomplished. Twenty-three consecutive patients with brain tumors underwent MR imaging with a 1.5-T whole-body MR system. Fiber tracts on the lesion side in the brain had varying degrees of displacement or disruption as a result of the tumor. Tract disruption resulted from direct tumor involvement, compression on the tract, and vasogenic edema surrounding the tumor. This diffusion-tensor MR imaging method with the parallel imaging technique allows clinically feasible brain fiber tracking.