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.     

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.     

Parallel MRI with extended and averaged GRAPPA kernels (PEAK-GRAPPA): optimized spatiotemporal dynamic imaging

Purpose

To evaluate an optimized k‐t‐space related reconstruction method for dynamic magnetic resonance imaging (MRI), a method called PEAK‐GRAPPA (Parallel MRI with Extended and Averaged GRAPPA Kernels) is presented which is based on an extended spatiotemporal GRAPPA kernel in combination with temporal averaging of coil weights.

Materials and Methods

The PEAK‐GRAPPA kernel consists of a uniform geometry with several spatial and temporal source points from acquired k‐space lines and several target points from missing k‐space lines. In order to improve the quality of coil weight estimation sets of coil weights are averaged over the temporal dimension.

Results

The kernel geometry leads to strongly decreased reconstruction times compared to the recently introduced k‐t‐GRAPPA using different kernel geometries with only one target point per kernel to fit. Improved results were obtained in terms of the root mean square error and the signal‐to‐noise ratio as demonstrated by in vivo cardiac imaging.

Conclusion

Using a uniform kernel geometry for weight estimation with the properties of uncorrelated noise of different acquired timeframes, optimized results were achieved in terms of error level, signal‐to‐noise ratio, and reconstruction time. J. Magn. Reson. Imaging 2008;28:1226–1232. © 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.     

k‐TE generalized autocalibrating partially parallel acquisition (GRAPPA) for accelerated multiple gradient‐recalled echo (MGRE) R2* mapping in the abdomen

Multiple gradient‐recalled echo (MGRE) methods are commonly used for abdominal R₂* mapping. Accelerated MGRE acquisitions would offer the potential to shorten requisite breathhold times and/or increase spatial resolution and coverage. In both phantom and normal volunteer studies, view‐sharing (VS) methods, generalized autocalibrating partially parallel acquisition (GRAPPA) methods, and newly proposed k–echo time (k‐TE) GRAPPA methods were compared for the purpose of accelerating MGRE acquisitions. Utilization of water‐selective spatial spectral excitation pulses reduced artifact levels for both VS and k‐TE GRAPPA approaches. VS approaches were found to be highly sensitive to off‐resonance effects, particularly at increasing acceleration rates. k‐TE GRAPPA significantly reduced residual artifact levels compared to GRAPPA approaches while improving the accuracy of accelerated abdominal R₂* measurements. These initial feasibility studies demonstrate that k‐TE GRAPPA is an effective method to reduce scan times during abdominal R₂*‐mapping procedures. Magn Reson Med, 2009. © 2008 Wiley‐Liss, 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.     

Motion compensated generalized reconstruction for free‐breathing dynamic contrast‐enhanced MRI

The analysis of abdominal and thoracic dynamic contrast‐enhanced MRI is often impaired by artifacts and misregistration caused by physiological motion. Breath‐hold is too short to cover long acquisitions. A novel multipurpose reconstruction technique, entitled dynamic contrast‐enhanced generalized reconstruction by inversion of coupled systems, is presented. It performs respiratory motion compensation in terms of both motion artefact correction and registration. It comprises motion modeling and contrast‐change modeling. The method feeds on physiological signals and x‐f space properties of dynamic series to invert a coupled system of linear equations. The unknowns solved for represent the parameters for a linear nonrigid motion model and the parameters for a linear contrast‐change model based on B‐splines. Performance is demonstrated on myocardial perfusion imaging, on six simulated data sets and six clinical exams. The main purpose consists in removing motion‐induced errors from time–intensity curves, thus improving curve analysis and postprocessing in general. This method alleviates postprocessing difficulties in dynamic contrast‐enhanced MRI and opens new possibilities for dynamic contrast‐enhanced MRI analysis. Magn Reson Med, 2011. © 2010 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.     

Improved MR phase‐contrast velocimetry using a novel nine‐point balanced motion‐encoding scheme with increased robustness to eddy current effects

Phase‐contrast MRI (PC‐MRI) velocimetry is a noninvasive, high‐resolution motion assessment tool. However, high motion sensitivity requires strong motion‐encoding magnetic gradients, making phase‐contrast‐MRI prone to baseline shift artifacts due to the generation of eddy currents. In this study, we propose a novel nine‐point balanced velocity‐encoding strategy, designed to be more accurate in the presence of strong and rapidly changing gradients. The proposed method was validated using a rotating phantom, and its robustness and precision were explored and compared with established approaches through computer simulations and in vivo experiments. Computer simulations yielded a 39–57% improvement in velocity–noise ratio (corresponding to a 27–33% reduction in measurement error), depending on which method was used for comparison. Moreover, in vivo experiments confirmed this by demonstrating a 26–53% reduction in accumulated velocity error over the R–R interval. The nine‐point balanced phase‐contrast‐MRI‐encoding strategy is likely useful for settings where high spatial and temporal resolution and/or high motion sensitivity is required, such as in high‐resolution rodent myocardial tissue phase mapping. Magn Reson Med, 2013. © 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.     

Three‐element phased‐array coil for imaging of rat spinal cord at 7T

To overcome some of the limitations of an implantable coil, including its invasive nature and limited spatial coverage, a three‐element phased‐array coil is described for high‐resolution magnetic resonance imaging (MRI) of rat spinal cord. This coil allows imaging both thoracic and cervical segments of rat spinal cord. In the current design, coupling between the nearest neighbors was minimized by overlapping the coil elements. A simple capacitive network was used for decoupling the next neighbor elements. The dimensions of individual coils in the array were determined based on the signal‐to‐noise ratio (SNR) measurements performed on a phantom with three different surface coils. SNR measurements on a phantom demonstrated higher SNR for the phased array coil relative to two different volume coils. In vivo images acquired on rat spinal cord with our coil demonstrated excellent gray and white matter contrast. To evaluate the performance of the phased array coil under parallel imaging, g‐factor maps were obtained for acceleration factors of 2 and 3. These simulations indicate that parallel imaging with an acceleration factor of 2 would be possible without significant image reconstruction–related noise amplifications. Magn Reson Med 60:1498–1505, 2008. © 2008 Wiley‐Liss, Inc.     

Comprehensive quantification of signal‐to‐noise ratio and g‐factor for image‐based and k‐space‐based parallel imaging reconstructions

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g‐factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal‐to‐noise ratio and g‐factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple “prescan” measurement of noise amplitude and correlation in the phased‐array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal‐to‐noise ratio and g‐factor. The “pseudo multiple replica” method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel‐by‐pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k‐space trajectories, image reconstruction, or noise conditioning techniques. Magn Reson Med 60:895–907, 2008. © 2008 Wiley‐Liss, Inc.     

Respiratory motion‐compensated radial dynamic contrast‐enhanced (DCE)‐MRI of chest and abdominal lesions

Dynamic contrast‐enhanced (DCE)‐MRI is becoming an increasingly important tool for evaluating tumor vascularity and assessing the effectiveness of emerging antiangiogenic and antivascular agents. In chest and abdominal regions, however, respiratory motion can seriously degrade the achievable image quality in DCE‐MRI studies. The purpose of this work is to develop a respiratory motion‐compensated DCE‐MRI technique that combines the self‐gating properties of radial imaging with the reconstruction flexibility afforded by the golden‐angle view‐order strategy. Following radial data acquisition, the signal at k‐space center is first used to determine the respiratory cycle, and consecutive views during the expiratory phase of each respiratory period (34–55 views, depending on the breathing rate) are grouped into individual segments. Residual intrasegment translation of lesion is subsequently compensated for by an autofocusing technique that optimizes image entropy, while intersegment translation (among different respiratory cycles) is corrected using 3D image correlation. The resulting motion‐compensated, undersampled dynamic image series is then processed to reduce image streaking and to enhance the signal‐to‐noise ratio (SNR) prior to perfusion analysis, using either the k‐space‐weighted image contrast (KWIC) radial filtering technique or principal component analysis (PCA). The proposed data acquisition scheme also allows for high frame‐rate arterial input function (AIF) sampling and free‐breathing baseline T₁ mapping. The performance of the proposed radial DCE‐MRI technique is evaluated in subjects with lung and liver lesions, and results demonstrate that excellent pixelwise perfusion maps can be obtained with the proposed methodology. Magn Reson Med 60:1135–1146, 2008. © 2008 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.     

Improved parallel MR imaging using a coefficient penalized regularization for GRAPPA reconstruction

A novel coefficient penalized regularization method for generalized autocalibrating partially parallel acquisitions (GRAPPA) reconstruction is developed for improving MR image quality. In this method, the fitting coefficients of the source data are weighted with different penalty factors, which are highly dependent upon the relative displacements from the source data to the target data in k‐space. The imaging data from both phantom testing and in vivo MRI experiments demonstrate that the coefficient penalized regularization method in GRAPPA reconstruction is able to reduce noise amplification to a greater degree. Therefore, the method enhances the quality of images significantly when compared to the previous least squares and Tikhonov regularization methods. Magn Reson Med 69:1109–1114, 2013. © 2012 Wiley Periodicals, Inc.     

Highly accelerated real‐time cardiac cine MRI using k–t SPARSE‐SENSE

For patients with impaired breath‐hold capacity and/or arrhythmias, real‐time cine MRI may be more clinically useful than breath‐hold cine MRI. However, commercially available real‐time cine MRI methods using parallel imaging typically yield relatively poor spatio‐temporal resolution due to their low image acquisition speed. We sought to achieve relatively high spatial resolution (～2.5 × 2.5 mm²) and temporal resolution (～40 ms), to produce high‐quality real‐time cine MR images that could be applied clinically for wall motion assessment and measurement of left ventricular function. In this work, we present an eightfold accelerated real‐time cardiac cine MRI pulse sequence using a combination of compressed sensing and parallel imaging (k‐t SPARSE‐SENSE). Compared with reference, breath‐hold cine MRI, our eightfold accelerated real‐time cine MRI produced significantly worse qualitative grades (1–5 scale), but its image quality and temporal fidelity scores were above 3.0 (adequate) and artifacts and noise scores were below 3.0 (moderate), suggesting that acceptable diagnostic image quality can be achieved. Additionally, both eightfold accelerated real‐time cine and breath‐hold cine MRI yielded comparable left ventricular function measurements, with coefficient of variation <10% for left ventricular volumes. Our proposed eightfold accelerated real‐time cine MRI with k–t SPARSE‐SENSE is a promising modality for rapid imaging of myocardial function. J. Magn. Reson. Imaging 2013. © 2012 Wiley Periodicals, 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.     

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.