k-t-Space accelerated myocardial perfusion

Purpose

To investigate the performance of the recently introduced spatiotemporal parallel imaging technique called parallel MRI with extended and averaged generalized autocalibrating partially parallel acquisitions (GRAPPA) kernels (PEAK‐GRAPPA) for myocardial perfusion measurements.

Materials and Methods

A study with 11 patients with myocardial infarction was performed to compare nonaccelerated perfusion imaging, i.e., fully acquired k‐space data, with the results of conventional GRAPPA and PEAK‐GRAPPA with a net acceleration factor of 2.4 to 3.4. Signal time courses reflecting the passage of the contrast agent bolus in different regions of the heart were evaluated for these different reconstruction methods.

Results

Reconstruction with PEAK‐GRAPPA demonstrated considerably improved image quality compared to conventional GRAPPA. In addition, signal time courses for PEAK‐GRAPPA demonstrated an excellent agreement compared to full k‐space data, which is necessary for an accurate qualitative and quantitative assessment of myocardial perfusion.

Conclusion

Qualitative and quantitative results of patient measurements illustrate that the temporal fidelity of nonperiodic processes such as myocardial perfusion are preserved with PEAK‐GRAPPA up to net acceleration factors of more than 3 while showing a superior image quality compared to conventional GRAPPA and a sliding‐window reconstruction. J. Magn. Reson. Imaging 2008;28:1080–1085. © 2008 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.     

Using GRAPPA to improve autocalibrated coil sensitivity estimation for the SENSE family of parallel imaging reconstruction algorithms

Two strategies are widely used in parallel MRI to reconstruct subsampled multicoil image data. SENSE and related methods employ explicit receiver coil spatial response estimates to reconstruct an image. In contrast, coil‐by‐coil methods such as GRAPPA leverage correlations among the acquired multicoil data to reconstruct missing k‐space lines. In self‐referenced scenarios, both methods employ Nyquist‐rate low‐frequency k‐space data to identify the reconstruction parameters. Because GRAPPA does not require explicit coil sensitivities estimates, it needs considerably fewer autocalibration signals than SENSE. However, SENSE methods allow greater opportunity to control reconstruction quality though regularization and thus may outperform GRAPPA in some imaging scenarios. Here, we employ GRAPPA to improve self‐referenced coil sensitivity estimation in SENSE and related methods using very few auto‐calibration signals. This enables one to leverage each methods' inherent strength and produce high quality self‐referenced SENSE reconstructions. Magn Reson Med 60:462–467, 2008. © 2008 Wiley‐Liss, Inc.     

On the undersampling strategies to accelerate time‐resolved 3D imaging using k‐t‐GRAPPA

The purpose of this study was to explore how to optimally undersample and reconstruct time‐resolved 3D data using a k‐t‐space‐based GRAPPA technique. The performance of different reconstruction strategies was evaluated using data sets with different ratios of phase (N_y) and partition (N_z) encoding lines (N_y × N_z = 64–128 × 40–64) acquired in a moving phantom. Image reconstruction was performed for different kernel configurations and different reduction factors (R = 5, 6, 8, and 10) and was evaluated using regional error quantification and SNR analysis. To analyze the temporal fidelity of the different kernel configurations in vivo, time‐resolved 3D phase contrast data were acquired in the thoracic aorta of two healthy volunteers. Results demonstrated that kernel configurations with a small kernel extension yielded superior results especially for more asymmetric data matrices as typically used in clinical applications. The application of k‐t‐GRAPPA to in vivo data demonstrated the feasibility of undersampling of time‐resolved 3D phase contrast data set with a nominal reduction factors of up to R_net = 8, while maintaining the temporal fidelity of the measured velocity field. Extended GRAPPA‐based parallel imaging with optimized multidimensional reconstruction kernels has the potential to substantially accelerate data acquisitions in time‐resolved 3D MRI. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

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.     

Variation of noise in multi-run functional MRI using generalized autocalibrating partially parallel acquisition (GRAPPA)

Purpose:

To investigate the noise variation in multi‐run functional MRI (fMRI) scans using generalized autocalibrating partially parallel acquisition (GRAPPA), with a focus on the cause of this variation.

Materials and Methods:

A phantom was continuously scanned for 10 runs using echo‐planar imaging (EPI) combined with GRAPPA to simulate a multi‐run fMRI exam. The variation of noise between runs was examined for different GRAPPA acceleration factors. The noise variation was also evaluated in a real fMRI experiment with human subjects at an acceleration factor of two. The cause of noise variation was explored by offline reconstruction using different GRAPPA weights and numerical simulation of GRAPPA reference scans.

Results:

It was found that the noise distribution in the image is stable within a run but may vary randomly from run to run. The variation of noise was also observed in fMRI experiments with human subjects. The variation can be significantly reduced if all the images from individual runs are reconstructed using the same reference scan data.

Conclusion:

Both phantom experiments and human data showed that the noise pattern may change in different fMRI runs. The variation is mainly caused by the random noise in separate reference scans for GRAPPA in each run. J. Magn. Reson. Imaging 2012;462‐470. © 2011 Wiley Periodicals, Inc.     

HTGRAPPA: Real‐time B1‐weighted image domain TGRAPPA reconstruction

The temporal generalized autocalibrating partially parallel acquisitions (TGRAPPA) algorithm for parallel MRI was modified for real‐time low latency imaging in interventional procedures using image domain, B₁‐weighted reconstruction. GRAPPA coefficients were calculated in k‐space, but applied in the image domain after appropriate transformation. Convolution‐like operations in k‐space were thus avoided, resulting in improved reconstruction speed. Image domain GRAPPA weights were combined into composite unmixing coefficients using adaptive B₁‐map estimates and optimal noise weighting. Images were reconstructed by pixel‐by‐pixel multiplication in the image domain, rather than time‐consuming convolution operations in k‐space. Reconstruction and weight‐set calculation computations were parallelized and implemented on a general‐purpose multicore architecture. The weight calculation was performed asynchronously to the real‐time image reconstruction using a dedicated parallel processing thread. The weight‐set coefficients were computed in an adaptive manner with updates linked to changes in the imaging scan plane. In this implementation, reconstruction speed is not dependent on acceleration rate or GRAPPA kernel size. Magn Reson Med, 2009. © 2009 Wiley‐Liss, Inc.     

Half‐fourier‐acquisition single‐shot turbo spin‐echo (HASTE) MRI of the lung at 3 Tesla using parallel imaging with 32‐receiver channel technology

Purpose

To assess the feasibility of half‐Fourier‐acquisition single‐shot turbo spin‐echo (HASTE) of the lung at 3 Tesla (T) using parallel imaging with a prototype of a 32‐channel torso array coil, and to determine the optimum acceleration factor for the delineation of intrapulmonary anatomy.

Materials and Methods

Nine volunteers were examined on a 32‐channel 3T MRI system using a prototype 32‐channel‐torso‐array‐coil. HASTE‐MRI of the lung was acquired at both, end‐inspiratory and end‐expiratory breathhold with parallel imaging (Generalized autocalibrating partially parallel acquisitions = GRAPPA) using acceleration factors ranging between R = 1 (TE = 42 ms) and R = 6 (TE = 16 ms). The image quality of intrapulmonary anatomy and subjectively perceived noise level was analyzed by two radiologists in consensus. In addition quantitative measurements of the signal‐to‐noise ratio (SNR) of HASTE with different acceleration factors were assessed in phantom measurements.

Results

Using an acceleration factor of R = 4 image blurring was substantially reduced compared with lower acceleration factors resulting in sharp delineation of intrapulmonary structures in expiratory scans. For inspiratory scans an acceleration factor of 2 provided the best image quality. Expiratory scans had a higher subjectively perceived SNR than inspiratory scans.

Conclusion

Using optimized multi‐element coil geometry HASTE‐MRI of the lung is feasible at 3T with acceleration factors up to 4. Compared with nonaccelerated acquisitions, shorter echo times and reduced image blurring are achieved. Expiratory scanning may be favorable to compensate for susceptibility associated signal loss at 3T. J. Magn. Reson. Imaging 2009;30:541–546. © 2009 Wiley‐Liss, Inc.     

Virtual coil concept for improved parallel MRI employing conjugate symmetric signals

A new approach for utilizing conjugate k‐space symmetry for improved parallel MRI performance is presented. By generating virtual coils containing conjugate symmetric k‐space signals from actual coils, additional image‐ and coil‐phase information can be incorporated into the reconstruction process for parallel acquisition techniques. In that way the reconstruction conditions are improved, resulting in less noise enhancement. In particular in combination with generalized autocalibrating partially parallel acquisitions (GRAPPA), the virtual coil concept represents a practical approach since no explicit spatial phase information is required. In addition, the influence of phase variations originating from the complex receiver coils as well as from the background is investigated. It is shown that there exist background phase distributions yielding an optimized pMRI reconstruction. Magn Reson Med 61:93–102, 2009. © 2008 Wiley‐Liss, Inc.     

Diffusion tensor imaging (DTI) with retrospective motion correction for large-scale pediatric imaging

Purpose:

To develop and implement a clinical DTI technique suitable for the pediatric setting that retrospectively corrects for large motion without the need for rescanning and/or reacquisition strategies, and to deliver high‐quality DTI images (both in the presence and absence of large motion) using procedures that reduce image noise and artifacts.

Materials and Methods:

We implemented an in‐house built generalized autocalibrating partially parallel acquisitions (GRAPPA)‐accelerated diffusion tensor (DT) echo‐planar imaging (EPI) sequence at 1.5T and 3T on 1600 patients between 1 month and 18 years old. To reconstruct the data, we developed a fully automated tailored reconstruction software that selects the best GRAPPA and ghost calibration weights; does 3D rigid‐body realignment with importance weighting; and employs phase correction and complex averaging to lower Rician noise and reduce phase artifacts. For select cases we investigated the use of an additional volume rejection criterion and b‐matrix correction for large motion.

Results:

The DTI image reconstruction procedures developed here were extremely robust in correcting for motion, failing on only three subjects, while providing the radiologists high‐quality data for routine evaluation.

Conclusion:

This work suggests that, apart from the rare instance of continuous motion throughout the scan, high‐quality DTI brain data can be acquired using our proposed integrated sequence and reconstruction that uses a retrospective approach to motion correction. In addition, we demonstrate a substantial improvement in overall image quality by combining phase correction with complex averaging, which reduces the Rician noise that biases noisy data. J. Magn. Reson. Imaging 2012;36:961–971. © 2012 Wiley Periodicals, Inc.     

Combination of compressed sensing and parallel imaging for highly accelerated first‐pass cardiac perfusion MRI

First‐pass cardiac perfusion MRI is a natural candidate for compressed sensing acceleration since its representation in the combined temporal Fourier and spatial domain is sparse and the required incoherence can be effectively accomplished by k‐t random undersampling. However, the required number of samples in practice (three to five times the number of sparse coefficients) limits the acceleration for compressed sensing alone. Parallel imaging may also be used to accelerate cardiac perfusion MRI, with acceleration factors ultimately limited by noise amplification. In this work, compressed sensing and parallel imaging are combined by merging the k‐t SPARSE technique with sensitivity encoding (SENSE) reconstruction to substantially increase the acceleration rate for perfusion imaging. We also present a new theoretical framework for understanding the combination of k‐t SPARSE with SENSE based on distributed compressed sensing theory. This framework, which identifies parallel imaging as a distributed multisensor implementation of compressed sensing, enables an estimate of feasible acceleration for the combined approach. We demonstrate feasibility of 8‐fold acceleration in vivo with whole‐heart coverage and high spatial and temporal resolution using standard coil arrays. The method is relatively insensitive to respiratory motion artifacts and presents similar temporal fidelity and image quality when compared to Generalized autocalibrating partially parallel acquisitions (GRAPPA) with 2‐fold acceleration. Magn Reson Med, 2010. © 2010 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.     

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.     

Cross-validation-based kernel support selection for improved GRAPPA reconstruction.

The extended version of the generalized autocalibrating partially parallel acquisition (GRAPPA) technique incorporates multiple lines and multiple columns of measured k-space data to estimate missing data. For a given accelerated dataset, the selection of the measured data points for fitting a missing datum (i.e., the kernel support) that provides optimal reconstruction depends on coil array configuration, noise level in the acquired data, imaging configuration, and number and position of autocalibrating signal lines. In this work, cross-validation is used to select the kernel support that best balances the conflicting demands of fit accuracy and stability in GRAPPA reconstruction. The result is an optimized tradeoff between artifacts and noise. As demonstrated with experimental data, the method improves image reconstruction with GRAPPA. Because the method is simple and applied in postprocessing, it can be used with GRAPPA routinely.     

Artifact and noise suppression in GRAPPA imaging using improved k-space coil calibration and variable density sampling.

A parallel imaging technique, GRAPPA (GeneRalized Auto-calibrating Partially Parallel Acquisitions), has been used to improve temporal or spatial resolution. Coil calibration in GRAPPA is performed in central k-space by fitting a target signal using its adjacent signals. Missing signals in outer k-space are reconstructed. However, coil calibration operates with signals that exhibit large amplitude variation while reconstruction is performed using signals with small amplitude variation. Different signal variations in coil calibration and reconstruction may result in residual image artifact and noise. The purpose of this work was to improve GRAPPA coil calibration and variable density (VD) sampling for suppressing residual artifact and noise. The proposed coil calibration was performed in local k-space along both the phase and frequency encoding directions. Outer k-space was acquired with two different reduction factors. Phantom data were reconstructed by both the conventional GRAPPA and the improved technique for comparison at an acceleration of two. Under the same acceleration, optimal sampling and calibration parameters were determined. An in vivo image was reconstructed in the same way using the predetermined optimal parameters. The performance of GRAPPA was improved by the localized coil calibration and VD sampling scheme.     

Model-based nonlinear inverse reconstruction for T2 mapping using highly undersampled spin-echo MRI

Purpose:

To develop a model‐based reconstruction technique for T2 mapping based on multi‐echo spin‐echo MRI sequences with highly undersampled Cartesian data encoding.

Materials and Methods:

The proposed technique relies on a nonlinear inverse reconstruction algorithm which directly estimates a T2 and spin‐density map from a train of undersampled spin echoes. The method is applicable to acquisitions with single receiver coils but benefits from multi‐element coil arrays. The algorithm is validated for trains of 16 spin echoes with a spacing of 10 to 12 ms using numerical simulations as well as human brain MRI at 3 Tesla (T).

Results:

When compared with a standard T2 fitting procedure using fully sampled T2‐weighted images, and depending on the available signal‐to‐noise ratio and number of coil elements, model‐based nonlinear inverse reconstructions for both simulated and in vivo MRI data yield accurate T2 estimates for undersampling factors of 5 to 10.

Conclusion:

This work describes a promising strategy for T2‐weighted MRI that simultaneously offers accurate T2 relaxation times and properly T2‐weighted images at arbitrary echo times. For a standard spin‐echo MRI sequence with Cartesian encoding, the method allows for a much higher degree of undersampling than obtainable by conventional parallel imaging. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.     

Generalized GRAPPA operators for wider spiral bands: Rapid self‐calibrated parallel reconstruction for variable density spiral MRI

A rapid and self‐calibrated parallel imaging reconstruction method is proposed for undersampled variable density spiral datasets. A set of generalized GRAPPA for wider readout line operators are used to expand each acquired spiral line into a wider spiral band, therefore fulfilling Nyquist sampling criterion throughout the k‐space. The calibration of generalized GRAPPA for wider readout line operators is performed using the fully sampled central k‐space region. The resulting generalized GRAPPA for wider readout line operator weights are adaptively regularized to minimize the error in the newly‐generated data at different k‐space locations. Simulation and experimental results demonstrate that the technique can be used either to achieve a significant acceleration and/or to reduce off‐resonance artifacts due to a shorten readout duration. Magn Reson Med, 2011. © 2011 Wiley‐Liss, Inc.     

Iterative decomposition of water and fat with echo asymmetry and least‐squares estimation (IDEAL) of the wrist and finger at 3T: Comparison with chemical shift selective fat suppression images

Purpose:

To compare fat‐suppressed magnetic resonance imaging (MRI) quality using iterative decomposition of water and fat with echo asymmetry and least‐squares estimation (IDEAL) with that using chemical shift selective fat‐suppressed T1‐weighted spin‐echo (CHESS) images for evaluating rheumatoid arthritis (RA) lesions of the hand and finger at 3T.

Materials and Methods:

MRI was performed in eight healthy volunteers and eight RA patients with a 3.0T MR system (Signa HDxt GE healthcare) using an eight‐channel knee coil. FS‐CHESS‐T1‐SE and IDEAL imaging were acquired in the coronal planes covering the entire structure of the bilateral hands with a slice thickness of 2 mm. In the RA patients both images were obtained after intravenous gadolinium administration. Image quality was evaluated on a five‐point scale (1 = excellent to 5 = very poor). Synovitis and bone marrow contrast uptake on MR images were reviewed by two musculoskeletal radiologists using the Rheumatoid Arthritis MRI Scoring System (RAMRIS) of the Outcome Measures in Rheumatoid Arthritis Clinical Trials (OMERACT) group.

Results:

IDEAL showed uniform FS unaffected by magnetic field inhomogeneity and challenging geometry of hand and fingers, while CHESS‐T1‐SE often showed FS failure within the first metacarpal joint, tip of the finger, and ulnar aspect of the wrist joint. Overall image quality was significantly better with IDEAL than CHESS‐T1‐SE images (4.43 vs. 3.43, P < 0.01). Interobserver agreement (κ value) for synovitis and bone marrow contrast uptake was good to excellent with IDEAL (0.74–0.91, 0.62–0.89, respectively).

Conclusion:

IDEAL could compensate for the effects of field inhomogeneities, providing uniform FS of the hand and finger than did the CHESS‐T1‐SE sequence. J. Magn. Reson. Imaging 2013;37:733–738. © 2012 Wiley Periodicals, Inc.     

Denoising sparse images from GRAPPA using the nullspace method

To accelerate magnetic resonance imaging using uniformly undersampled (nonrandom) parallel imaging beyond what is achievable with generalized autocalibrating partially parallel acquisitions (GRAPPA) alone, the DEnoising of Sparse Images from GRAPPA using the Nullspace method is developed. The trade‐off between denoising and smoothing the GRAPPA solution is studied for different levels of acceleration. Several brain images reconstructed from uniformly undersampled k‐space data using DEnoising of Sparse Images from GRAPPA using the Nullspace method are compared against reconstructions using existing methods in terms of difference images (a qualitative measure), peak‐signal‐to‐noise ratio, and noise amplification (g‐factors) as measured using the pseudo‐multiple replica method. Effects of smoothing, including contrast loss, are studied in synthetic phantom data. In the experiments presented, the contrast loss and spatial resolution are competitive with existing methods. Results for several brain images demonstrate significant improvements over GRAPPA at high acceleration factors in denoising performance with limited blurring or smoothing artifacts. In addition, the measured g‐factors suggest that DEnoising of Sparse Images from GRAPPA using the Nullspace method mitigates noise amplification better than both GRAPPA and L₁ iterative self‐consistent parallel imaging reconstruction (the latter limited here by uniform undersampling). Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.     

k-t GRAPPA: a k-space implementation for dynamic MRI with high reduction factor.

A novel technique called "k-t GRAPPA" is introduced for the acceleration of dynamic magnetic resonance imaging. Dynamic magnetic resonance images have significant signal correlations in k-space and time dimension. Hence, it is feasible to acquire only a reduced amount of data and recover the missing portion afterward. Generalized autocalibrating partially parallel acquisitions (GRAPPA), as an important parallel imaging technique, linearly interpolates the missing data in k-space. In this work, it is shown that the idea of GRAPPA can also be applied in k-t space to take advantage of the correlations and interpolate the missing data in k-t space. For this method, no training data, filters, additional parameters, or sensitivity maps are necessary, and it is applicable for either single or multiple receiver coils. The signal correlation is locally derived from the acquired data. In this work, the k-t GRAPPA technique is compared with our implementation of GRAPPA, TGRAPPA, and sliding window reconstructions, as described in Methods. The experimental results manifest that k-t GRAPPA generates high spatial resolution reconstruction without significant loss of temporal resolution when the reduction factor is as high as 4. When the reduction factor becomes higher, there might be a noticeable loss of temporal resolution since k-t GRAPPA uses temporal interpolation. Images reconstructed using k-t GRAPPA have less residue/folding artifacts than those reconstructed by sliding window, much less noise than those reconstructed by GRAPPA, and wider temporal bandwidth than those reconstructed by GRAPPA with residual k-space. k-t GRAPPA is applicable to a wide range of dynamic imaging applications and is not limited to imaging parts with quasi-periodic motion. Since only local information is used for reconstruction, k-t GRAPPA is also preferred for applications requiring real time reconstruction, such as monitoring interventional MRI.