Parallel imaging for first-pass myocardial perfusion

Two parallel imaging methods used for first-pass myocardial perfusion imaging were compared in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and image artifacts. One used adaptive Time-adaptive SENSitivity Encoding (TSENSE) and the other used GeneRalized Autocalibrating Partially Parallel Acquisition (GRAPPA), which are both applied to a gradient-echo sequence. Both methods were tested on 12 patients with coronary artery disease. The order of perfusion sequences was inverted in every other patient. Image acquisition was started during the administration of a contrast bolus followed by a 20-ml saline flush (3 ml/s), and the next perfusion was started at least 15 min thereafter using an identical bolus. An acceleration rate of 2 was used in both methods, and acquisition was performed during breath-holding. Significantly higher SNR, CNR and image quality were obtained with GRAPPA images than with TSENSE images. GRAPPA, however, did not yield a higher CNR when applied after the second bolus. GRAPPA perfusion imaging produced larger differences between subjects than did TSENSE. Compared to TSENSE, GRAPPA produced significantly better CNR on the first bolus. More consistent SNR and CNR were obtained from TSENSE images than from GRAPPA images, indicating that the diagnostic value of TSENSE may be better.     

Performance Analysis of 2-D GRAPPA and Partial Fourier GRAPPA for 3-D MRI

The acquisition time of three-dimensional magnetic resonance imaging (3-D MRI) is too long to tolerate in many clinical applications. At present, parallel MRI (pMRI) and partial Fourier (PF) with homodyne detection, including 2-D pMRI (two-dimensional pMRI) and PF_pMRI (the combination of PF and pMRI), are often used to accelerate data sampling in 3-D MRI. However, the performances of 2-D pMRI and PF_pMRI have been seldom discussed. In this paper, we choose GRAPPA (generalized auto-calibrating partially parallel acquisition) as a representative pMRI to analyze and compare the performances of 2-D GRAPPA and PF_GRAPPA, including the noise standard deviation (SD), root mean-square error (RMSE) and g factor, through a series of in vitro experiments. A series of phantom experiments show that the SD, RMSE and g-factor values of PF_GRAPPA are lower than those of 2-D GRAPPA under the same acceleration factor. It demonstrates that the performance of PF_GRAPPA is better than that of 2-D GRAPPA. PF_GRAPPA can be used in any thickness of imaging slab, while 2-D GRAPPA can only be used in thick slab due to the difficulties in determination of the fitting coefficients which result from imperfect RF pulse. In vivo brain experiment results also show that the performance of PF_GRAPPA is better than that of 2-D GRAPPA.     

APIR4EMC: Autocalibrated parallel imaging reconstruction for extended multi-contrast imaging

PurposeTo improve image quality of multi-contrast imaging with the proposed Autocalibrated Parallel Imaging Reconstruction for Extended Multi-Contrast Imaging (APIR4EMC).MethodsAPIR4EMC reconstructs multi-contrast images in an autocalibrated parallel imaging reconstruction framework by adding contrasts as virtual coils. Compensation of signal evolution along the echo train of different contrasts is performed to improve signal prediction for missing samples. As a proof of concept, we performed prospectively accelerated phantom and in-vivo brain acquisitions with T1, T1-fat saturated (Fatsat), T2, PD, and FLAIR contrasts. The k-space sampling patterns of these acquisitions were jointly optimized. Images were jointly reconstructed with the proposed APIR4EMC method as well as individually with GRAPPA. Root mean square error (RMSE) to fully sampled reference images and g-factor maps were computed for both methods in the phantom experiment. Visual evaluation was performed in the in-vivo experiment.ResultsCompared to GRAPPA, APIR4EMC reduced artifacts and improved SNR of the reconstructed images in the phantom acquisitions. Quantitatively, APIR4EMC substantially reduced noise amplification (g-factor) as well as RMSE compared to GRAPPA. Signal evolution compensation reduced artifacts. In the in-vivo experiments, 1 mm³ isotropic 3D images with contrasts of T1, T1-Fatsat, T2, PD, and FLAIR were acquired in as little as 7.5 min with the acceleration factor of 9. Reconstruction quality was consistent with the phantom results.ConclusionCompared to single contrast reconstruction with GRAPPA, APIR4EMC reduces artifacts and noise amplification in accelerated multi-contrast imaging.     

Diagnosis of subclavian steal syndrome using dynamic time-resolved magnetic resonance angiography: a technical note

We developed a dynamic magnetic resonance (MR) angiographic imaging protocol that can aide the diagnosis of subclavian steal syndrome (SSS). Our protocol combines a new pulse sequence: time-resolved echo-shared angiographic technique (TREAT) with parallel imaging: generalized autocalibrating partially parallel acquisition (GRAPPA). Our pulse sequence, like traditional catheter angiography exams, provides anatomic and dynamic flow pattern information in one scan. If included in comprehensive SSS MR imaging examinations, this sequence can potentially reduce the need for diagnostic X-ray angiography.     

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.     

A simple application of compressed sensing to further accelerate partially parallel imaging

Compressed sensing (CS) and partially parallel imaging (PPI) enable fast magnetic resonance (MR) imaging by reducing the amount of k-space data required for reconstruction. Past attempts to combine these two have been limited by the incoherent sampling requirement of CS since PPI routines typically sample on a regular (coherent) grid. Here, we developed a new method, “CS+GRAPPA,” to overcome this limitation. We decomposed sets of equidistant samples into multiple random subsets. Then, we reconstructed each subset using CS and averaged the results to get a final CS k-space reconstruction. We used both a standard CS and an edge- and joint-sparsity-guided CS reconstruction. We tested these intermediate results on both synthetic and real MR phantom data and performed a human observer experiment to determine the effectiveness of decomposition and to optimize the number of subsets. We then used these CS reconstructions to calibrate the generalized autocalibrating partially parallel acquisitions (GRAPPA) complex coil weights. In vivo parallel MR brain and heart data sets were used. An objective image quality evaluation metric, Case-PDM, was used to quantify image quality. Coherent aliasing and noise artifacts were significantly reduced using two decompositions. More decompositions further reduced coherent aliasing and noise artifacts but introduced blurring. However, the blurring was effectively minimized using our new edge- and joint-sparsity-guided CS using two decompositions. Numerical results on parallel data demonstrated that the combined method greatly improved image quality as compared to standard GRAPPA, on average halving Case-PDM scores across a range of sampling rates. The proposed technique allowed the same Case-PDM scores as standard GRAPPA using about half the number of samples. We conclude that the new method augments GRAPPA by combining it with CS, allowing CS to work even when the k-space sampling pattern is equidistant.     

GRAPPA-based susceptibility-weighted imaging of normal volunteers and patients with brain tumor at 7 T

Susceptibility-weighted imaging (SWI) is a valuable technique for high-resolution imaging of brain vasculature that greatly benefits from the emergence of higher field strength MR scanners. Autocalibrating partially parallel imaging techniques can be employed to reduce lengthy acquisition times as long as the decrease in signal-to-noise ratio does not significantly affect the contrast between vessels and brain parenchyma. This study assessed the feasibility of a Generalized Autocalibrating Partially Parallel Acquisition (GRAPPA)-based SWI technique at 7 T in both healthy volunteers and brain tumor patients. GRAPPA-based SWI allowed a twofold or more reduction in scan time without compromising vessel contrast and small vessel detection. Postprocessing parameters for the SWI needed to be modified for patients where the tumor causes high-frequency phase wrap artifacts but did not adversely affect vessel contrast. GRAPPA-based SWI at 7 T revealed regions of microvascularity, hemorrhage and calcification within heterogeneous brain tumors that may aid in characterizing active or necrotic tumor and monitoring treatment effects.     

Autocalibrated parallel imaging reconstruction with sampling pattern optimization for GRASE: APIR4GRASE

PurposeTo reduce artifacts and scan time of GRASE imaging by selecting an optimal sampling pattern and jointly reconstructing gradient echo and spin echo images.MethodsWe jointly reconstruct images for the different echo types by considering these as additional virtual coil channels in the novel Autocalibrated Parallel Imaging Reconstruction with Sampling Pattern Optimization for GRASE (APIR4GRASE) method. Besides image reconstruction, we identify optimal sampling patterns for the acquisition. The selected optimal patterns were validated on phantom and in-vivo acquisitions. Comparison to the conventional GRASE without acceleration, and to the GRAPPA reconstruction with a single echo type was also performed.ResultsUsing identified optimal sampling patterns, APIR4GRASE eliminated modulation artifacts in both phantom and in-vivo experiments; mean square error (MSE) was reduced by 78% and 94%, respectively, compared to the conventional GRASE with similar scan time. Both artifacts and g-factor were reduced compared to the GRAPPA reconstruction with a single echo type.ConclusionAPIR4GRASE substantially improves the speed and quality of GRASE imaging over the state-of-the-art, and is able to reconstruct both spin echo and gradient echo images.     

High-resolution intracranial MRA at 7T using autocalibrating parallel imaging: initial experience in vascular disease patients

Purpose

Greater spatial resolution in intracranial three-dimensional time-of-flight (TOF) magnetic resonance angiography (MRA) is possible at higher field strengths, due to the increased contrast-to-noise ratio (CNR) from the higher signal-to-noise ratio and the improved background suppression. However, at very high fields, spatial resolution is limited in practice by the acquisition time required for sequential phase encoding. In this study, we applied parallel imaging to 7T TOF MRA studies of normal volunteers and patients with vascular disease, in order to obtain very high resolution (0.12 mm³) images within a reasonable scan time.

Materials and Methods

Custom parallel imaging acquisition and reconstruction methods were developed for 7T MRA, based on generalized autocalibrating partially parallel acquisition (GRAPPA). The techniques were compared and applied to studies of seven normal volunteers and three patients with cerebrovascular disease.

Results

The technique produced high resolution studies free from discernible reconstruction artifacts in all subjects and provided excellent depiction of vascular pathology in patients.

Conclusions

7T TOF MRA with parallel imaging is a valuable noninvasive angiographic technique that can attain very high spatial resolution.     

Data consistency criterion for selecting parameters for k-space-based reconstruction in parallel imaging

k-space-based reconstruction in parallel imaging depends on the reconstruction kernel setting, including its support. An optimal choice of the kernel depends on the calibration data, coil geometry and signal-to-noise ratio, as well as the criterion used. In this work, data consistency, imposed by the shift invariance requirement of the kernel, is introduced as a goodness measure of k-space-based reconstruction in parallel imaging and demonstrated. Data consistency error (DCE) is calculated as the sum of squared difference between the acquired signals and their estimates obtained based on the interpolation of the estimated missing data. A resemblance between DCE and the mean square error in the reconstructed image was found, demonstrating DCE's potential as a metric for comparing or choosing reconstructions. When used for selecting the kernel support for generalized autocalibrating partially parallel acquisition (GRAPPA) reconstruction and the set of frames for calibration as well as the kernel support in temporal GRAPPA reconstruction, DCE led to improved images over existing methods. Data consistency error is efficient to evaluate, robust for selecting reconstruction parameters and suitable for characterizing and optimizing k-space-based reconstruction in parallel imaging.     

Real-time imaging with radial GRAPPA: Implementation on a heterogeneous architecture for low-latency reconstructions

Combination of non-Cartesian trajectories with parallel MRI permits to attain unmatched acceleration rates when compared to traditional Cartesian MRI during real-time imaging. However, computationally demanding reconstructions of such imaging techniques, such as k-space domain radial generalized auto-calibrating partially parallel acquisitions (radial GRAPPA) and image domain conjugate gradient sensitivity encoding (CG-SENSE), lead to longer reconstruction times and unacceptable latency for online real-time MRI on conventional computational hardware. Though CG-SENSE has been shown to work with low-latency using a general purpose graphics processing unit (GPU), to the best of our knowledge, no such effort has been made for radial GRAPPA. Radial GRAPPA reconstruction, which is robust even with highly undersampled acquisitions, is not iterative, requiring only significant computation during initial calibration while achieving good image quality for low-latency imaging applications. In this work, we present a very fast, low-latency, reconstruction framework based on a heterogeneous system using multi-core CPUs and GPUs. We demonstrate an implementation of radial GRAPPA that permits reconstruction times on par with or faster than acquisition of highly accelerated datasets in both cardiac and dynamic musculoskeletal imaging scenarios. Acquisition and reconstruction times are reported.     

Diffusion-weighted three-dimensional MP-RAGE MR imaging

The advantages of three-dimensional (3D) acquisition are that you obtain thinner and more slices with better profiles, and better signal-to-noise ratio for an equivalent slice thickness. Three-dimensional acquisition is preferable for obtaining contiguous thin-slice MR images. However, the acquisition time extends compared with the two-dimensional acquisition because the second phase-encode axis is applied by the 3D acquisition. Therefore, 3D acquisition should be a high-speed imaging method. In this paper, a new diffusion-sensitive 3D magnetization-prepared rapid gradient-echo (3D MP-RAGE) sequence was studied. In this sequence, a preparation phase with a 90 degrees RF-motion proving gradient (MPG): MPG-180 degrees RF-MPG-90 degrees RF pulse train (diffusion-weighted driven-equilibrium Fourier transform) was used to sensitize the magnetization to diffusion. Centric k-space acquisition order is necessary to minimize saturation effects from tissues with short relaxation times. From phantom experimental results, the effect of the diffusion weighting was changed by the centric vs. sequential k-space acquisition order. The effect of centric k-space acquisition order was larger than the effect of sequential k-space acquisition order. The contrast of centric k-space acquisition order became equal to the contrast of conventional diffusion-weighted spin echo. From rat experimental results, small isotropic diffusion-weighted image data (voxel size: 0.625 x 0.625 x 0.625 mm3) were obtained. This sequence was useful in vivo.     

基于同时多层激发和并行成像的心脏磁共振电影成像

磁共振成像（MRI）无创无害、对比度多、可以任意剖面成像的特点特别适合用于心脏成像,却因扫描时间长限制了其在临床上的应用.为了解决心脏磁共振电影成像屏气扫描时间过长的问题,该文提出了一种基于同时多层激发的多倍加速心脏磁共振电影成像及其影像重建的方法,该方法将相位调制多层激发（CAIPIRINHA）技术与并行加速（PPA）技术相结合,运用到分段采集心脏电影成像序列中,实现了在相位编码方向和选层方向的四倍加速,并使用改进的SENSE/GRAPPA算法对图像进行重建.分别在水模以及人体上进行了实验,将加速序列图像与不加速序列图像进行对比,结果验证了重建算法的有效性,表明该方法可以在保障图像质量以及准确测量心脏功能的前提下成倍节省扫描时间.     

Magnetic resonance imaging of coronary arteries and heart valves in a living mouse: techniques and preliminary results

New investigations in MRI of a mouse heart showed high-contrast cardiac images and thereby the possibility of doing functional cardiac studies of in vivo mice. But is MRI, in addition, capable of visualizing microstructures such as the coronary arteries and the heart valves of a living mouse? To answer this question, 2D and 3D gradient echo sequences with and without flow compensation were used to image the coronary arteries. To increase signal-to-noise ratio, a birdcage resonator was optimized for mouse heart imaging. Contrast between blood and myocardium was achieved through the inflow effect. A segmented three-dimensional FLASH sequence acquired with a multiple overlap thin slab technique showed the best results. With this technique an isotropic resolution of 100 microm was achieved. The left coronary artery could be visualized up to the apex of the heart. This is demonstrated with short axis views and 3D surface reconstructions of the mouse heart. The four cardiac valves were also visible with the 3D method.     

Single breath-hold multi-slab and cine cardiac-synchronized gadolinium-enhanced three-dimensional angiography

The rest period of the coronary arteries has been shown to be on the order of 120–160 msec. Restriction of the acquisition window in breath-hold cardiac-synchronized gadolinium-enhanced imaging to this duration limits the amount of sampled k-space data and hence the information when compared with conventional gadolinium-enhanced imaging. Two techniques for gadolinium-enhanced cardiac-synchronized angiography were implemented that acquire additional data during the unused portions of the cardiac cycle. Data acquisition is synchronized with the heart cycle and is restricted to a short period of each heart cycle. In a single breath-hold, a multi-slab acquisition (n = 5) allowed ECG-synchronized imaging of the entire heart or a CINE acquisition (n = 5) provided multiple stacks of images at different phases in the cardiac cycle over a smaller area. Preliminary results acquired in healthy volunteers and patients with aortic disease indicate that additional information can be acquired without an increase in breath-hold duration or a reduction in image quality.     

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.     

A nonlinear regularization strategy for GRAPPA calibration

A regularization strategy is described for generalized autocalibrating partially parallel acquisition (GRAPPA) that allows successful calibration using a small number of autocalibration signals (ACS). The approach requires certain nonlinear relationships between the GRAPPA coefficients to be satisfied, which increases the redundancy so that fewer ACS need to be acquired.     

Feasibility of 3D harmonic contrast imaging

Improved endocardial border delineation with the application of contrast agents should allow for less complex and faster tracing algorithms for left ventricular volume analysis. We developed a fast rotating phased array transducer for 3D imaging of the heart with harmonic capabilities making it suitable for contrast imaging. In this study the feasibility of 3D harmonic contrast imaging is evaluated in vitro. A commercially available tissue mimicking flow phantom was used in combination with Sonovue. Backscatter power spectra from a tissue and contrast region of interest were calculated from recorded radio frequency data. The spectra and the extracted contrast to tissue ratio from these spectra were used to optimize the excitation frequency, the pulse length and the receive filter settings of the transducer. Frequencies ranging from 1.66 to 2.35 MHz and pulse lengths of 1.5, 2 and 2.5 cycles were explored. An increase of more than 15 dB in the contrast to tissue ratio was found around the second harmonic compared with the fundamental level at an optimal excitation frequency of 1.74 MHz and a pulse length of 2.5 cycles. Using the optimal settings for 3D harmonic contrast recordings volume measurements of a left ventricular shaped agar phantom were performed. Without contrast the extracted volume data resulted in a volume error of 1.5%, with contrast an accuracy of 3.8% was achieved. The results show the feasibility of accurate volume measurements from 3D harmonic contrast images. Further investigations will include the clinical evaluation of the presented technique for improved assessment of the heart.     

Reconstruction in image space using basis functions for partially parallel imaging

General theory of a new reconstruction technique for partially parallel imaging (PPI) is presented in this study. Reconstruction in Image space using Basis functions (RIB) is based on the general principle that the PPI reconstruction in image space can be represented by a pixel-wise weighted summation of the aliased images directly from undersampled data. By assuming that these weighting coefficients for unaliasing can be approximated from the linear combination of a few predefined basis functions, RIB is capable of reconstructing the image within an arbitrary region. This paper discusses the general theory of RIB and its relationship to the classical reconstruction method, GRAPPA. The presented experiments demonstrate RIB with several MRI applications. It is shown that the performance of RIB is comparable to that of GRAPPA. In some cases, RIB shows advantages of increasing reconstruction efficiency, suppressing artifacts and alleviating the nonuniformity of noise distribution. It is anticipated that RIB would be especially useful for cardiac and prostate imaging, where the field of view during data acquisition is required to be much larger than the region of interest.     

Breath-hold 3D MR coronary angiography with a new intravascular contrast agent (feruglose)--first clinical experiences

Demonstration of the initial results of breath-hold 3D MR coronary angiography with patients using a new intravascular contrast agent (feruglose). Contrast-enhanced 3D MR-coronary angiography was performed in 5 patients with coronary artery disease after administration of feruglose in three different doses (0.5 (n = 3), 2, 5 mg Fe/kg body weight for each patient). MR coronary angiography was performed with an ECG-triggered 3D-FLASH-sequence during breath-hold at 1.5 T (TR 6.8 ms, TE 2.5 ms, flip-angle 30 degrees ). To reduce data acquisition time, only the two anterior elements of the phased-array body coil were activated. The data acquisition window within the cardiac cycle ranged between 217-326 ms depending on the matrix. Signal-to-noise (SNR) and contrast-to-noise ratios (CNR) of the coronary arteries were analyzed, and the results for the detection of coronary artery stenoses were compared with those obtained by conventional coronary angiography. SNR and CNR revealed an improved image quality at a dose of 2 mg Fe/kg compared with the lower dose, but no further improvement was obtained by rising the dose to 5 mg Fe/kg. Except for the left circumflex artery of one patient, at minimum the proximal parts of all four main coronary arteries could be imaged for all patients. Within the visible parts of the coronary arteries, six of eight significant coronary stenoses were identified correctly. Imaging of the proximal parts of the coronary arteries including detection of stenoses is possible during breath-hold using an intravascular contrast agent.