Parallel acquisition techniques in cardiac cine magnetic resonance imaging using TrueFISP sequences: comparison of image quality and artifacts

PURPOSE: To compare image quality, artifacts, and signal-to-noise ratio (SNR) in cardiac cine TrueFISP magnetic resonance imaging (MRI) with and without parallel acquisition techniques (PAT). MATERIALS AND METHODS: MRI was performed in 16 subjects with a TrueFISP sequence (1.5 T; Magnetom Sonata, Siemens): TR, 3.0 msec; TE, 1.5 msec; flip angle (FA), 60 degrees. Three axes were scanned without PAT (no PAT) and using the generalized autocalibrating partially parallel acquisition (GRAPPA) and modified sensitivity encoding (mSENSE) reconstruction algorithms with an autocalibration mode to reduce scan time. A conventional spine array and a body flex array were used. Artifacts, image noise, and overall image quality were classified on a 4-point scale by an observer blinded to the implemented technique; for quantitative comparison, SNR was measured. RESULTS: With a PAT factor of two, acquisition time could be reduced by 39%. No PAT did not show artifacts, and GRAPPA revealed fewer artifacts than mSENSE. PAT provided inferior-quality scores concerning image noise and overall image quality. In quantitative measurements, GRAPPA and mSENSE (20.1 +/- 6.2 and 15.6 +/- 6.2, respectively) yielded lower SNR than no PAT (30.6 +/- 20.1; P < 0.05) and P < 0.001). CONCLUSION: Time savings in PAT are accompanied by artifacts and an increase in image noise. The GRAPPA algorithm was superior to mSENSE concerning image quality, noise, and SNR.     

Independent phase modulation for efficient dual-band 3D imaging.

Certain applications of MRI, such as bilateral breast imaging, require simultaneous imaging of multiple volumes. Although image data can be acquired sequentially, the SNR is often improved if both slabs are excited and imaged together, typically with phase encoding across a volume including both slabs and the space between them. The use of independent phase modulation of multiple slabs eliminates the need to encode empty space between slabs, which can result in a significant time reduction. Each slab is excited with a phase proportional to phase-encode number such that the slab positions in the acquired data are shifted to reduce empty space. With careful consideration this technique is compatible with different pulse sequences (e.g., spin-echo, gradient-echo, RF spoiling, and balanced SSFP (bSSFP)) and acceleration strategies (e.g., partial k-space and parallel imaging). This technique was demonstrated in phantoms and applied to bilateral breast imaging, where scan times were reduced by 20-30%.     

Comparison of parallel acquisition techniques generalized autocalibrating partially parallel acquisitions (GRAPPA) and modified sensitivity encoding (mSENSE) in functional MRI (fMRI) at 3T

PURPOSE: To evaluate the parallel acquisition techniques, generalized autocalibrating partially parallel acquisitions (GRAPPA) and modified sensitivity encoding (mSENSE), and determine imaging parameters maximizing sensitivity toward functional activation at 3T. MATERIALS AND METHODS: A total of eight imaging protocols with different parallel imaging techniques (GRAPPA and mSENSE) and reduction factors (R = 1, 2, 3) were compared at different matrix sizes (64 and 128) with respect to temporal noise characteristics, artifact behavior, and sensitivity toward functional activation. RESULTS: Echo planar imaging (EPI) with GRAPPA and a reduction factor of 2 revealed similar image quality and sensitivity than full k-space EPI. A higher incidence of artifacts and a marked sensitivity loss occurred at R = 3. Even though the same eight-channel head coil was used for signal detection in all experiments, GRAPPA generally showed more benign patterns of spatially-varying noise amplification, and mSENSE was also more susceptible to residual unfolding artifacts than GRAPPA. CONCLUSION: At 3T and a reduction factor of 2, parallel imaging can be used with only little penalty with regard to sensitivity. With our implementation and coil setup the performance of GRAPPA was clearly superior to mSENSE. Thus, it seems advisable to pay special attention to the employed parallel imaging method and its implementation.     

Comparison of in vitro and in vivo MRI of the spine using parallel imaging

OBJECTIVE: The purpose of this study was to compare the image quality of two parallel-imaging methods applied to standard turbo spin-echo T2-weighted imaging of the lumbar spine. MATERIALS AND METHODS: Phantom imaging and lumbar spine studies of 15 healthy subjects were performed using T2-weighted turbo spin-echo sequences obtained with and without parallel imaging (generalized autocalibrating partially parallel acquisition [GRAPPA] and modified sensitive encoding [mSENSE]) on a 1.5-T magnet. The signal-to-noise ratio (SNR) and uniformity were measured in the phantom, and SNR and signal difference-noise ratio were evaluated in cerebrospinal fluid, vertebral bodies, and subcutaneous fat of the volunteers, using both techniques sequentially. Aliasing artifacts on GRAPPA and mSENSE images were visually evaluated. SNRs were compared using the Student's paired t test, with p values less than 0.05 considered significant. RESULTS: In the phantom study, when the same number of coil elements were used (n = 3), SNR and uniformity values obtained with standard T2-weighted turbo spin-echo sequences were higher than those obtained with parallel sequences. The GRAPPA SNR obtained with three coil elements was higher than the standard T2-weighted SNR obtained with one coil element. Similar findings were noted regarding uniformity. In the lumbar spine, GRAPPA SNR values for fat, cerebrospinal fluid, and vertebral bodies were significantly higher than mSENSE SNR values, with a p value less than 0.01, but were not significantly different from T2-weighted turbo spin-echo SNR values. GRAPPA signal difference-noise ratio values were significantly higher than mSENSE signal difference-noise ratio values, with a p value less than 0.01, but were not significantly different from T2-weighted turbo spin-echo signal difference-noise ratio values. GRAPPA produced fewer aliasing artifacts than mSENSE. CONCLUSION: In spine MRI, GRAPPA may be used to reduce scanning time and yields a higher SNR than mSENSE without any increase in aliasing artifacts and with an SNR similar to that obtained with standard T2-weighted turbo spin-echo.     

Parallel acquisition techniques for accelerated volumetric interpolated breath-hold examination magnetic resonance imaging of the upper abdomen: assessment of image quality and lesion conspicuity

PURPOSE: To evaluate the impact of parallel acquisition techniques (PATs) on image quality and detection of liver metastases using three-dimensional volumetric interpolated breath-hold examination (VIBE) for clinical liver imaging. MATERIALS AND METHODS: Forty-nine patients with various primary malignancies underwent abdominal dynamic contrast-enhanced three-dimensional VIBE magnetic resonance imaging (MRI) (1.5 T) using a standard phased array coil. Recently introduced Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA) and SENSitivity Encoding (mSENSE) PAT reconstruction algorithms were added to reduce scan time twofold. Overall image quality, motion, and aliasing artifacts were classified on a 5-point scale. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) measurements were performed for quantitative comparison. All sequences were evaluated concerning the number of detected lesions. RESULTS: PAT resulted in a reduction of data acquisition time from 23 to 13 seconds. Both GRAPPA and mSENSE data sets yielded 30% less SNR (34.8 +/- 14.1 and 33.1 +/- 13.3, P < 0.001) and 35% less CNR (21.2 +/- 15.0 and 20.9 +/- 12.7, P < 0.05) in comparison to unaccelerated VIBE (SNR = 50.8 +/- 20.3/CNR = 32.5 +/- 19.1). Similarly, PAT revealed lower-image-quality scores than unaccelerated VIBE. GRAPPA resulted in more fold-over artifacts than mSENSE. mSENSE revealed slightly fewer motion artifacts than no PAT. The unaccelerated late-venous-phase VIBE sequence revealed 146 lesions in the same patients. Accelerated images with mSENSE reconstruction detected 138 lesions. GRAPPA revealed 127 lesions, and thus performed inferior to mSENSE. CONCLUSION: At least for arrays with small numbers of elements, such as arrays used in this study, the PAT-induced reduction in scanning times must be weighed against compromises in image quality, which translate into poorer diagnostic performance regarding detection of small hepatic lesions. Thus, the PAT implementations tested in this study should probably be reserved for patients unable to hold their breaths for regular three-dimensional VIBE data sets.     

Breathheld autocalibrated phase‐contrast imaging

Purpose:

To compare generalized autocalibrating partially parallel acquisitions (GRAPPA), modified sensitivity encoding (mSENSE), and SENSE in phase‐contrast magnetic resonance imaging (PC‐MRI) applications.

Materials and Methods:

Aliasing of the torso can occur in PC‐MRI applications. If the data are further undersampled for parallel imaging, SENSE can be problematic in correctly unaliasing signals due to coil sensitivity maps that do not match that of the aliased volume. Here, a method for estimating coil sensitivities in flow applications is described. Normal volunteers (n = 5) were scanned on a 1.5 T MRI scanner and underwent PC‐MRI scans using GRAPPA, mSENSE, SENSE, and conventional PC‐MRI acquisitions. Peak velocity and flow through the aorta and pulmonary artery were evaluated.

Results:

Bland–Altman statistics for flow in the aorta and pulmonary artery acquired with mSENSE and GRAPPA methods (R = 2 and R = 3 cases) have comparable mean differences to flow acquired with conventional PC‐MRI. GRAPPA and mSENSE PC‐MRI have more robust measurements than SENSE when there is aliasing artifact caused by insufficient coil sensitivity maps. For peak velocity, there are no considerable differences among the mSENSE, GRAPPA, and SENSE reconstructions and are comparable to conventional PC‐MRI.

Conclusion:

Flow measurements of images reconstructed with autocalibration techniques have comparable agreement with conventional PC‐MRI and provide robust measurements in the presence of wraparound. J. Magn. Reson. Imaging 2010;31:1004–1014. ©2010 Wiley‐Liss, Inc.     

Quantitative myocardial perfusion imaging using different autocalibrated parallel acquisition techniques

PURPOSE: To compare three different autocalibrated parallel acquisition techniques (PAT) for quantitative and semiquantitative myocardial perfusion imaging. MATERIALS AND METHODS: Seven healthy volunteers underwent myocardial first-pass perfusion imaging at rest using an SR-TrueFISP pulse sequence without PAT and while using GRAPPA, mSENSE, and TSENSE. signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), normalized upslopes (NUS), and myocardial blood flow (MBF) were calculated. Artifacts, image noise, and overall image quality were qualitatively assessed. Furthermore, the relation between signal intensity (SI) and contrast medium (CM) concentration was determined in phantoms. RESULTS: Using PAT the linear range of the SR-TrueFISP sequence was increased about 40%. All three PAT methods introduced significant loss in SNR and CNR. GRAPPA yielded slightly better values then mSENSE and TSENSE. Both SENSE techniques introduced significantly residual aliasing artifacts. Image noise was increased with all three PAT methods. However, overall image quality was reduced only with mSENSE. Even though GRAPPA yielded smaller NUS values than non-PAT, mSENSE, and TSENSE, no differences were found in MBF between all applied techniques. CONCLUSION: Quantitative and semiquantitative myocardial perfusion imaging can benefit from PAT due to shorter acquisition times and increased linearity of the pulse sequence. GRAPPA and TSENSE turned out to be well suited for quantitative myocardial perfusion imaging.     

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.     

Comparison of generalized autocalibrating partially parallel acquisitions and modified sensitivity encoding for diffusion tensor imaging

BACKGROUND AND PURPOSE: Diffusion tensor magnetic resonance imaging (DTI) of the brain is usually acquired with single-shot echo-planar imaging, which is associated with localized signal loss, geometric distortions, and blurring. Parallel imaging can lessen these artifacts by shortening the length of the echo-train acquisition. The self-calibrating parallel acquisition techniques, image domain-based modified sensitivity encoding (mSENSE) and k-space-based generalized autocalibrating partially parallel acquisitions (GRAPPA), were evaluated with DTI of the brain in 5 healthy subjects. METHODS: GRAPPA and mSENSE with higher acceleration factors (R) up to 4 were compared with conventional DTI (with and without phase partial Fourier, another method of reducing the echo-train length) on a 1.5T Sonata scanner (Siemens, Erlangen, Germany). The resulting images and diffusion maps were evaluated qualitatively and quantitatively. Qualitative analysis was performed by 3 reviewers blinded to the technique using image sharpness and the level of artifacts as characteristics for scoring each set of images. Quantitative comparisons encompassed measuring signal-to-noise ratio, Trace/3 apparent diffusion coefficient (ADC), and fractional anisotropy (FA) in 6 white-matter (WM) and gray-matter (GM) regions. RESULTS: Reviewers scored the GRAPPA and mSENSE R = 2 images better than images acquired with conventional techniques. FA contrast was improved at the GM/WM junction in peripheral brain areas. Trace/3 ADC and FA measurements were consistent for all methods. However, R = 3,4 images suffered from reconstruction-related artifacts. CONCLUSIONS: GRAPPA and mSENSE (R = 2) minimized the susceptibility and off-resonance effects associated with conventional DTI methods, yielding high-quality images and reproducible quantitative diffusion measurements.     

Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla

OBJECTIVES: Single-shot echo-planar based diffusion tensor imaging is prone to geometric and intensity distortions. Parallel imaging is a means of reducing these distortions while preserving spatial resolution. A quantitative comparison at 3 T of parallel imaging for diffusion tensor images (DTI) using k-space (generalized auto-calibrating partially parallel acquisitions; GRAPPA) and image domain (sensitivity encoding; SENSE) reconstructions at different acceleration factors, R, is reported here. MATERIALS AND METHODS: Images were evaluated using 8 human subjects with repeated scans for 2 subjects to estimate reproducibility. Mutual information (MI) was used to assess the global changes in geometric distortions. The effects of parallel imaging techniques on random noise and reconstruction artifacts were evaluated by placing 26 regions of interest and computing the standard deviation of apparent diffusion coefficient and fractional anisotropy along with the error of fitting the data to the diffusion model (residual error). RESULTS: The larger positive values in mutual information index with increasing R values confirmed the anticipated decrease in distortions. Further, the MI index of GRAPPA sequences for a given R factor was larger than the corresponding mSENSE images. The residual error was lowest in the images acquired without parallel imaging and among the parallel reconstruction methods, the R = 2 acquisitions had the least error. The standard deviation, accuracy, and reproducibility of the apparent diffusion coefficient and fractional anisotropy in homogenous tissue regions showed that GRAPPA acquired with R = 2 had the least amount of systematic and random noise and of these, significant differences with mSENSE, R = 2 were found only for the fractional anisotropy index. CONCLUSION: Evaluation of the current implementation of parallel reconstruction algorithms identified GRAPPA acquired with R = 2 as optimal for diffusion tensor imaging.     

Adaptive bilateral breast MRI using projection reconstruction time-resolved imaging of contrast kinetics

PURPOSE: To introduce a bilateral implementation of an adaptive imaging technique in which both dynamic and high resolution breast MR images are acquired simultaneously. MATERIALS AND METHODS: Adaptive three-dimensional bilateral breast imaging in the sagittal plane was achieved by combining two elements: a projection reconstruction time-resolved imaging of contrast kinetics (PR-TRICKS) k-space trajectory and a slab interleaved sequence that imaged alternate breasts every TR. A pilot study was performed to evaluate image quality and contrast uptake behavior, using eight patients with previously identified benign lesions. RESULTS: Adaptive reconstruction demonstrated breast lesions in all eight women with similar image quality and signal-to-noise ratio (SNR) to Cartesian images with comparable imaging parameters. Contrast enhancement curves covering the entire postinjection time period were obtained from the dynamic images and in one case compared to previous enhancement profiles from a conventional Cartesian trajectory. CONCLUSION: Bilateral dynamic and high spatial resolution images with high SNR can be achieved in a clinically feasible manner, providing both kinetic and morphologic analysis with a single data set. This may obviate the need for multiple MRI examinations for a thorough breast MRI workup.     

Generalized autocalibrating partially parallel acquisitions (GRAPPA).

In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique.     

Parallel spectroscopic imaging reconstruction with arbitrary trajectories using k‐space sparse matrices

Parallel imaging reconstruction has been successfully applied to magnetic resonance spectroscopic imaging (MRSI) to reduce scan times. For undersampled k‐space data on a Cartesian grid, the reconstruction can be achieved in image domain using a sensitivity encoding (SENSE) algorithm for each spectral data point. Alternative methods for reconstruction with undersampled Cartesian k‐space data are the SMASH and GRAPPA algorithms that do the reconstruction in the k‐space domain. To reconstruct undersampled MRSI data with arbitrary k‐space trajectories, image‐domain‐based iterative SENSE algorithm has been applied at the cost of long computing times. In this paper, a new k‐space domain‐based parallel spectroscopic imaging reconstruction with arbitrary k‐space trajectories using k‐space sparse matrices is applied to MRSI with spiral k‐space trajectories. The algorithm achieves MRSI reconstruction with reduced memory requirements and computing times. The results are demonstrated in both phantom and in vivo studies. Spectroscopic images very similar to that reconstructed with fully sampled spiral k‐space data are obtained at different reduction factors. Magn Reson Med 61:267–272, 2009. © 2009 Wiley‐Liss, Inc.     

Optimized parallel imaging for dynamic PC‐MRI with multidirectional velocity encoding

Phase contrast MRI with multidirectional velocity encoding requires multiple acquisitions of the same k‐space lines to encode the underlying velocities, which can considerably lengthen the total scan time. To reduce scan time, parallel imaging is often applied. In dynamic phase contrast MRI using standard generalized autocalibrating partially parallel acquisitions (GRAPPA), several central k‐spaces for autocalibration of the reconstruction (autocalibrating signal lines (ACS)) are typically acquired, separately for each velocity direction and each cardiac timeframe, for calculating the reconstruction weights. To further accelerate data acquisition, we developed two methods, which calculated weights with a substantially reduced number of ACSl lines. The effects on image quality and flow quantification were compared to fully sampled data, standard GRAPPA, and time‐interleaved sampling scheme in combination with generalized autocalibrating partially parallel acquisitions (TGRAPPA). The results show that the two proposed methods can clearly improve scan efficiency while maintaining image quality and accuracy of measured flow or myocardial tissue velocities. Compared to TGRAPPA, the proposed methods were more accurate in evaluating flow velocity. In conclusion, the proposed reconstruction strategies are promising for dynamic multidirectionally encoded acquisitions and can easily be implemented using the standard GRAPPA reconstruction algorithm. Magn Reson Med, 2010. © 2010 Wiley‐Liss, Inc.     

Image reconstruction by regularized nonlinear inversion—Joint estimation of coil sensitivities and image content

The use of parallel imaging for scan time reduction in MRI faces problems with image degradation when using GRAPPA or SENSE for high acceleration factors. Although an inherent loss of SNR in parallel MRI is inevitable due to the reduced measurement time, the sensitivity to image artifacts that result from severe undersampling can be ameliorated by alternative reconstruction methods. While the introduction of GRAPPA and SENSE extended MRI reconstructions from a simple unitary transformation (Fourier transform) to the inversion of an ill‐conditioned linear system, the next logical step is the use of a nonlinear inversion. Here, a respective algorithm based on a Newton‐type method with appropriate regularization terms is demonstrated to improve the performance of autocalibrating parallel MRI—mainly due to a better estimation of the coil sensitivity profiles. The approach yields images with considerably reduced artifacts for high acceleration factors and/or a low number of reference lines. Magn Reson Med, 2008. © 2008 Wiley‐Liss, Inc.     

Improving quality of arterial spin labeling MR imaging at 3 Tesla with a 32-channel coil and parallel imaging

Purpose:

To compare 12‐channel and 32‐channel phased‐array coils and to determine the optimal parallel imaging (PI) technique and factor for brain perfusion imaging using Pulsed Arterial Spin labeling (PASL) at 3 Tesla (T).

Materials and Methods:

Twenty‐seven healthy volunteers underwent 10 different PASL perfusion PICORE Q2TIPS scans at 3T using 12‐channel and 32‐channel coils without PI and with GRAPPA or mSENSE using factor 2. PI with factor 3 and 4 were used only with the 32‐channel coil. Visual quality was assessed using four parameters. Quantitative analyses were performed using temporal noise, contrast‐to‐noise and signal‐to‐noise ratios (CNR, SNR).

Results:

Compared with 12‐channel acquisition, the scores for 32‐channel acquisition were significantly higher for overall visual quality, lower for noise and higher for SNR and CNR. With the 32‐channel coil, artifact compromise achieved the best score with PI factor 2. Noise increased, SNR and CNR decreased with PI factor. However mSENSE 2 scores were not always significantly different from acquisition without PI.

Conclusion:

For PASL at 3T, the 32‐channel coil at 3T provided better quality than the 12‐channel coil. With the 32‐channel coil, mSENSE 2 seemed to offer the best compromise for decreasing artifacts without significantly reducing SNR, CNR. J. Magn. Reson. Imaging 2012;35:1233‐1239. © 2012 Wiley Periodicals, Inc.     

Using the GRAPPA operator and the generalized sampling theorem to reconstruct undersampled non‐Cartesian data

As expected from the generalized sampling theorem of Papoulis, the use of a bunched sampling acquisition scheme in conjunction with a conjugate gradient (CG) reconstruction algorithm can decrease scan time by reducing the number of phase‐encoding lines needed to generate an unaliased image at a given resolution. However, the acquisition of such bunched data requires both modified pulse sequences and high gradient performance. A novel method of generating the “bunched” data using self‐calibrating GRAPPA operator gridding (GROG), a parallel imaging method that shifts data points by small distances in k‐space (with Δk usually less than 1.0, depending on the receiver coil) using the GRAPPA operator, is presented here. With the CG reconstruction method, these additional “bunched” points can then be used to reconstruct an image with reduced artifacts from undersampled data. This method is referred to as GROG‐facilitated bunched phase encoding (BPE), or GROG‐BPE. To better understand how the patterns of bunched points, maximal blip size, and number of bunched points affect the reconstruction quality, a number of simulations were performed using the GROG‐BPE approach. Finally, to demonstrate that this method can be combined with a variety of trajectories, examples of images with reduced artifacts reconstructed from undersampled in vivo radial, spiral, and rosette data are shown. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

Increasing efficiency of parallel imaging for 2D multislice acquisitions

Parallel imaging algorithms require precise knowledge about the spatial sensitivity variation of the receiver coils to reconstruct images with full field of view (FOV) from undersampled Fourier encoded data. Sensitivity information must either be given a priori, or estimated from calibration data acquired along with the actual image data. In this study, two approaches are presented, which require very little or no additional data at all for calibration in two‐dimensional multislice acquisitions. Instead of additional data, information from spatially adjacent slices is used to estimate coil sensitivity information, thereby increasing the efficiency of parallel imaging. The proposed approaches rely on the assumption that over a small range of slices, coil sensitivities vary smoothly in slice direction. Both methods are implemented as variants of the GRAPPA algorithm. For a given effective acceleration, superior image quality is achieved compared to the conventional GRAPPA method. For the latter calibration lines for coil weight computation must be acquired in addition to the undersampled k‐spaces for coil weight computation, thus requiring higher k‐space undersampling, that is, a higher reduction factor to achieve the same effective acceleration. The proposed methods are particularly suitable to speed up parallel imaging for clinical applications where the reduction factor is limited to two or three. Magn Reson Med 2009 © 2009 Wiley‐Liss, Inc.     

Highly k‐t‐space–accelerated phase‐contrast MRI

The purpose of this study was to combine a recently introduced spatiotemporal parallel imaging technique, PEAK‐GRAPPA (parallel MRI with extended and averaged generalized autocalibrating partially parallel acquisition), with two‐dimensional (2D) cine phase‐contrast velocity mapping. Phase‐contrast MRI was applied to measure the blood flow in the thoracic aorta and the myocardial motion of the left ventricle. To evaluate the performance of different reconstruction methods, fully acquired k‐space data sets were used to compare conventional parallel imaging using GRAPPA with reduction factors of R = 2–6 and PEAK‐GRAPPA as well as sliding window reconstruction with reduction factors R = 2–12 (net acceleration factors up to 5.2). PEAK‐GRAPPA reconstruction resulted in improved image quality with considerably reduced artifacts, which was also supported by error analysis. To analyze potential blurring or low‐pass filtering effects of spatiotemporal PEAK‐GRAPPA, the velocity time courses of aortic flow and myocardial tissue motion were evaluated and compared with conventional image reconstructions. Quantitative comparisons of blood flow velocities and pixel‐wise correlation analysis of velocities highlight the potential of PEAK‐GRAPPA for highly accelerated dynamic phase‐contrast velocity mapping. Magn Reson Med 60:1169–1177, 2008. © 2008 Wiley‐Liss, Inc.     

Online real‐time reconstruction of adaptive TSENSE with commodity CPU/GPU hardware

Adaptive temporal sensitivity encoding (TSENSE) has been suggested as a robust parallel imaging method suitable for MR guidance of interventional procedures. However, in practice, the reconstruction of adaptive TSENSE images obtained with large coil arrays leads to long reconstruction times and latencies and thus hampers its use for applications such as MR‐guided thermotherapy or cardiovascular catheterization. Here, we demonstrate a real‐time reconstruction pipeline for adaptive TSENSE with low image latencies and high frame rates on affordable commodity personal computer hardware. For typical image sizes used in interventional imaging (128 × 96, 16 channels, sensitivity encoding (SENSE) factor 2‐4), the pipeline is able to reconstruct adaptive TSENSE images with image latencies below 90 ms at frame rates of up to 40 images/s, rendering the MR performance in practice limited by the constraints of the MR acquisition. Its performance is demonstrated by the online reconstruction of in vivo MR images for rapid temperature mapping of the kidney and for cardiac catheterization. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.