SPIRiT: Iterative self-consistent parallel imaging reconstruction from arbitrary k-space

MR Image Reconstruction Using a Combination of Compressed Sensing and Partial Fourier Acquisition: ESPReSSo

A Cartesian subsampling scheme is proposed incorporating the idea of PF acquisition and variable-density Poisson Disc (vdPD) subsampling by redistributing the sampling space onto a smaller region aiming to increase k-space sampling density for a given acceleration factor. Especially the normally sparse sampled high-frequency components benefit from this sampling redistribution, leading to improved edge delineation. The prospective subsampled and compacted k-space can be reconstructed by a seamless combination of a CS-algorithm with a Hermitian symmetry constraint accounting for the missing part of the k-space. This subsampling and reconstruction scheme is called Compressed Sensing Partial Subsampling (ESPReSSo) and was tested on in-vivo abdominal MRI datasets. Different reconstruction methods and regularizations are investigated and analyzed via global (intensity-based) and local (region-of-interest and line evaluation) image metrics, to conclude a clinical feasible setup. Results substantiate that ESPReSSo can provide improved edge delineation and regional homogeneity for multidimensional and multi-coil MRI datasets and is therefore useful in applications depending on well-defined tissue boundaries, such as image registration and segmentation or detection of small lesions in clinical diagnostics.

Variable density sampling and non-Cartesian super-resolved reconstruction for spatiotemporally encoded single-shot MRI

Spatiotemporally encoded (SPEN) single-shot MRI is an emerging ultrafast technique, which is capable of spatially selective acquisition and reduced field-of-view imaging. Compared to uniform sampling, variable density sampling has great potential in reducing aliasing artifacts and improving sampling efficiency. In this study, variable density spiral trajectory and non-Cartesian super-resolved (SR) reconstruction method are developed for SPEN MRI. The gradient waveforms design of spiral trajectory is mathematically described as an optimization problem subjected to the limitations of hardware. Non-Cartesian SR reconstruction with specific gridding method is developed to retrieve a resolution enhanced image from raw SPEN data. The robustness and efficiency of the proposed methods are demonstrated by numerical simulation and various experiments. The results indicate that variable density SPEN MRI can provide better spatial resolution and fewer aliasing artifacts compared to Cartesian counterpart. The proposed methods will facilitate the development of variable density SPEN MRI.

A Cylindrical, Inner Volume Selecting 2D-T2-Prep Improves GRAPPA-Accelerated Image Quality in MRA of the Right Coronary Artery

BACKGROUND

Two-dimensional (2D) spatially selective radiofrequency (RF) pulses may be used to excite restricted volumes. By incorporating a "pencil beam" 2D pulse into a T2-Prep, one may create a "2D-T2-Prep" that combines T2-weighting with an intrinsic outer volume suppression. This may particularly benefit parallel imaging techniques, where artefacts typically originate from residual foldover signal. By suppressing foldover signal with a 2D-T2-Prep, image quality may therefore improve. We present numerical simulations, phantom and in vivo validations to address this hypothesis.

METHODS

A 2D-T2-Prep and a conventional T2-Prep were used with GRAPPA-accelerated MRI (R = 1.6). The techniques were first compared in numerical phantoms, where per pixel maps of SNR (SNRmulti), noise, and g-factor were predicted for idealized sequences. Physical phantoms, with compartments doped to mimic blood, myocardium, fat, and coronary vasculature, were scanned with both T2-Preparation techniques to determine the actual SNRmulti and vessel sharpness. For in vivo experiments, the right coronary artery (RCA) was imaged in 10 healthy adults, using accelerations of R = 1,3, and 6, and vessel sharpness was measured for each.

RESULTS

In both simulations and phantom experiments, the 2D-T2-Prep improved SNR relative to the conventional T2-Prep, by an amount that depended on both the acceleration factor and the degree of outer volume suppression. For in vivo images of the RCA, vessel sharpness improved most at higher acceleration factors, demonstrating that the 2D-T2-Prep especially benefits accelerated coronary MRA.

CONCLUSION

Suppressing outer volume signal with a 2D-T2-Prep improves image quality particularly well in GRAPPA-accelerated acquisitions in simulations, phantoms, and volunteers, demonstrating that it should be considered when performing accelerated coronary MRA.

Accuracy of UTE-MRI-based patient setup for brain cancer radiation therapy

PURPOSE

Radiation therapy simulations solely based on MRI have advantages compared to CT-based approaches. One feature readily available from computed tomography (CT) that would need to be reproduced with MR is the ability to compute digitally reconstructed radiographs (DRRs) for comparison against on-board radiographs commonly used for patient positioning. In this study, the authors generate MR-based bone images using a single ultrashort echo time (UTE) pulse sequence and quantify their 3D and 2D image registration accuracy to CT and radiographic images for treatments in the cranium.

METHODS

Seven brain cancer patients were scanned at 1.5 T using a radial UTE sequence. The sequence acquired two images at two different echo times. The two images were processed using an in-house software to generate the UTE bone images. The resultant bone images were rigidly registered to simulation CT data and the registration error was determined using manually annotated landmarks as references. DRRs were created based on UTE-MRI and registered to simulated on-board images (OBIs) and actual clinical 2D oblique images from ExacTrac™.

RESULTS

UTE-MRI resulted in well visualized cranial, facial, and vertebral bones that quantitatively matched the bones in the CT images with geometric measurement errors of less than 1 mm. The registration error between DRRs generated from 3D UTE-MRI and the simulated 2D OBIs or the clinical oblique x-ray images was also less than 1 mm for all patients.

CONCLUSIONS

UTE-MRI-based DRRs appear to be promising for daily patient setup of brain cancer radiotherapy with kV on-board imaging.

Seven-Tesla MRI and neuroimaging biomarkers for Alzheimer's disease

The goal of this paper was to review the effectiveness of using 7-T MRI to study neuroimaging biomarkers for Alzheimer's disease (AD). The authors reviewed the literature for articles published to date on the use of 7-T MRI to study AD. Thus far, there are 3 neuroimaging biomarkers for AD that have been studied using 7-T MRI in AD tissue: 1) neuroanatomical atrophy; 2) molecular characterization of hypointensities; and 3) microinfarcts. Seven-Tesla MRI has had mixed results when used to study the 3 aforementioned neuroimaging biomarkers for AD. First, in the detection of neuroanatomical atrophy, 7-T MRI has exciting potential. Historically, noninvasive imaging of neuroanatomical atrophy during AD has been limited by suboptimal resolution. However, now there is compelling evidence that the high resolution of 7-T MRI may help overcome this hurdle. Second, in detecting the characterization of hypointensities, 7-T MRI has had varied success. PET scans will most likely continue to lead in the noninvasive imaging of amyloid plaques; however, there is emerging evidence that 7-T MRI can accurately detect iron deposits within activated microglia, which may help shed light on the role of the immune system in AD pathogenesis. Finally, in the detection of microinfarcts, 7-T MRI may also play a promising role, which may help further elucidate the relationship between cerebrovascular health and AD progression.

Motion correction for functional MRI with three-dimensional hybrid radial-Cartesian EPI

Purpose

Subject motion is a major source of image degradation for functional MRI (fMRI), especially when using multishot sequences like three‐dimensional (3D EPI). We present a hybrid radial‐Cartesian 3D EPI trajectory enabling motion correction in k‐space for functional MRI.

Methods

The EPI “blades” of the 3D hybrid radial‐Cartesian EPI sequence, called TURBINE, are rotated about the phase‐encoding axis to fill out a cylinder in 3D k‐space. Angular blades are acquired over time using a golden‐angle rotation increment, allowing reconstruction at flexible temporal resolution. The self‐navigating properties of the sequence are used to determine motion parameters from a high temporal‐resolution navigator time series. The motion is corrected in k‐space as part of the image reconstruction, and evaluated for experiments with both cued and natural motion.

Results

We demonstrate that the motion correction works robustly and that we can achieve substantial artifact reduction as well as improvement in temporal signal‐to‐noise ratio and fMRI activation in the presence of both severe and subtle motion.

Conclusion

We show the potential for hybrid radial‐Cartesian 3D EPI to substantially reduce artifacts for application in fMRI, especially for subject groups with significant head motion. The motion correction approach does not prolong the scan, and no extra hardware is required. Magn Reson Med 78:527–540, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Evaluating the Role of Reduced Oxygen Saturation and Vascular Damage in Traumatic Brain Injury Using Magnetic Resonance Perfusion-Weighted Imaging and Susceptibility-Weighted Imaging and Mapping

The cerebral vasculature, along with neurons and axons, is vulnerable to biomechanical insult during traumatic brain injury (TBI). Trauma-induced vascular injury is still an underinvestigated area in TBI research. Cerebral blood flow and metabolism could be important future treatment targets in neural critical care. Magnetic resonance imaging offers a number of key methods to probe vascular injury and its relationship with traumatic hemorrhage, perfusion deficits, venous blood oxygen saturation changes, and resultant tissue damage. They make it possible to image the hemodynamics of the brain, monitor regional damage, and potentially show changes induced in the brain's function not only acutely but also longitudinally following treatment. These methods have recently been used to show that even mild TBI (mTBI) subjects can have vascular abnormalities, and thus they provide a major step forward in better diagnosing mTBI patients.

Hybrid-Space SENSE Reconstruction for Simultaneous Multi-Slice MRI

Simultaneous Multi-Slice (SMS) magnetic resonance imaging (MRI) is a rapidly evolving technique for increasing imaging speed. Controlled aliasing techniques utilize periodic undersampling patterns to help mitigate the loss in signal-to-noise ratio (SNR) in SMS MRI. To evaluate the performance of different undersampling patterns, a quantitative description of the image SNR loss is needed. Additionally, eddy current effects in echo planar imaging (EPI) lead to slice-specific Nyquist ghosting artifacts. These artifacts cannot be accurately corrected for each individual slice before or after slice-unaliasing. In this work, we propose a hybrid-space sensitivity encoding (SENSE) reconstruction framework for SMS MRI by adopting a three-dimensional representation of the SMS acquisition. Analytical SNR loss maps are derived for SMS acquisitions with arbitrary phase encoding undersampling patterns. Moreover, we propose a matrix-decoding correction method that corrects the slice-specific Nyquist ghosting artifacts in SMS EPI acquisitions. Brain images demonstrate that the proposed hybrid-space SENSE reconstruction generates images with comparable quality to commonly used split-slice-generalized autocalibrating partially parallel acquisition reconstruction. The analytical SNR loss maps agree with those calculated by a Monte Carlo based method, but require less computation time for high quality maps. The analytical maps enable a fair comparison between the performances of coherent and incoherent SMS undersampling patterns. Phantom and brain SMS EPI images show that the matrix-decoding method performs better than the single-slice and slice-averaged Nyquist ghosting correction methods under the hybrid-space SENSE reconstruction framework.

Identification and reduction of image artifacts in non-contrast-enhanced velocity-selective peripheral angiography at 3T

PURPOSE

To identify and reduce image artifacts in non-contrast-enhanced velocity-selective (VS) magnetization-prepared peripheral MR angiography (MRA) at 3T.

METHODS

To avoid signal loss in the arteries, double and quadruple refocused VS excitation pulse sequences were designed that were robust to a wide range of B0 and B1 offset. To suppress stripe artifact and background signal variation, we successively applied two VS preparations with excitation profiles shifted by half the period of the stripes. VS-MRA using single, double, and quadruple refocused VS preparations was tested in healthy subjects and a patient.

RESULTS

In the regions of large B0 and B1 offsets, arterial signal loss was yielded by single refocused VS preparation, but was avoided with double or quadruple refocused preparations. Compared with single VS preparation, the two consecutive preparations with shifted excitation profiles substantially reduced the stripe artifact and background signal variation, as demonstrated by increased mean and decreased standard deviation of relative contrast-to-noise ratio. The proposed VS-MRA identified multilevel disease in the femoral arteries of the patient, as validated by digital subtraction angiography.

CONCLUSION

Two multiple refocused VS magnetization preparations with shifted excitation profiles yield artifact-free peripheral angiograms at 3T. Magn Reson Med 76:466-477, 2016. © 2015 Wiley Periodicals, Inc.

A robust method for suppressing motion-induced coil sensitivity variations during prospective correction of head motion in fMRI

Prospective motion correction is a promising candidate solution to suppress the effects of head motion during fMRI, ideally allowing the imaging plane to remain fixed with respect to the moving head. Residual signal artifacts may remain, however, because head motion in relation to a fixed multi-channel receiver coil (with non-uniform sensitivity maps) can potentially introduce unwanted signal variations comparable to the weak fMRI BOLD signal (~1%-4% at 1.5-3.0T). The present work aimed to investigate the magnitude of these residual artifacts, and characterize the regime over which prospective motion correction benefits from adjusting sensitivity maps to reflect relative positional change between the head and the coil. Numerical simulations were used to inform human fMRI experiments. The simulations indicated that for axial imaging within a commonly used 12-channel head coil, 5° of head rotation in-plane produced artifact signal changes of ~3%. Subsequently, six young adults were imaged with and without overt head motions of approximately this extent, with and without prospective motion correction using the Prospective Acquisition CorrEction (PACE) method, and with and without sensitivity map adjustments. Sensitivity map adjustments combined with PACE strongly protected against the artifacts of interest, as indicated by comparing three metrics of data quality (number of activated voxels, Dice coefficient of activation overlap, temporal standard deviation of baseline fMRI timeseries data) across the different experimental conditions. It is concluded that head motion in relation to a fixed multi-channel coil can adversely affect fMRI with prospective motion correction, and that sensitivity map adjustment can mitigate this effect at 3.0T.

ACCELERATING MAGNETIC RESONANCE IMAGING VIA DEEP LEARNING

This paper proposes a deep learning approach for accelerating magnetic resonance imaging (MRI) using a large number of existing high quality MR images as the training datasets. An off-line convolutional neural network is designed and trained to identify the mapping relationship between the MR images obtained from zero-filled and fully-sampled k-space data. The network is not only capable of restoring fine structures and details but is also compatible with online constrained reconstruction methods. Experimental results on real MR data have shown encouraging performance of the proposed method for efficient and effective imaging.

Interactions between head motion and coil sensitivity in accelerated fMRI

BACKGROUND

Parallel imaging is widely adopted to accelerate functional MRI (fMRI) data acquisition, through various strategies that involve multi-channel receiver coils. However, the non-uniform spatial sensitivity of multi-channel receiver coils may introduce unwanted artifacts when head motion occurs during the few-minute long fMRI scans. Although prospective correction provides a promising solution for alleviating the head motion artifacts in fMRI, the relative position of the fixed multi-channel receiver coils moves in the moving reference frame, potentially resulting in artifactual signal.

NEW METHOD

We used numerical simulations to investigate this effect on fMRI using two parallel imaging schemes: sensitivity encoding (SENSE) and generalized autocalibrating partially parallel acquisitions (GRAPPA) with acceleration factors 2 and 4, towards characterizing the regime over which parallel-imaging fMRI with prospective motion correction will benefit from updating coil sensitivities to reflect relative positional change between the head and the receiver coil. Moreover, six subjects were scanned with acceleration factors 2 and 4 while performing a simple finger-tapping task with and without overt head motion.

RESULTS

Updating coil sensitivities showed significant positive impact on standard deviation and activation maps in presence of overt head motion compared to that obtained with no overt head motion.

COMPARISON WITH EXISTING METHODS

The parallel imaging fMRI with updated coil sensitivity maps were compared to that with the coil sensitivity maps acquired at the reference position.

CONCLUSIONS

Head motion in relation to a fixed multi-channel coil can adversely affect the quality of parallel imaging fMRI data; and updating coil sensitivity map can mitigate this effect.

Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.

Fast temperature estimation from undersampled k-space with fully-sampled center for MR guided microwave ablation

PURPOSE

This study aims to accelerate MR temperature imaging using the proton resonance frequency (PRF) shift method for real time temperature monitoring during thermal ablation.

MATERIALS AND METHODS

The proposed method estimates temperature changes from undersampled k-space with a fully sampled center. This proposed algorithm is based on the hybrid multi-baseline and referenceless treatment image model and can be seen as an extension of the conventional k-space-based hybrid thermometry. The parameters of hybrid model are acquired by utilizing information from low resolution images which are obtained from fully-sampled centers of k-space. Registration is used to correct temperature errors due to the displacement of the subject. Phantom heating simulations, motion simulations, phantom heating and in-vivo experiments were performed to investigate the efficiency of the proposed method. SPIRiT and the conventional k-space estimation reconstruction thermometry were implemented for comparison using the same sampling pattern.

RESULTS

The phantom heating simulations showed that the proposed method results in lower RMSEs than the conventional k-space hybrid thermometry and SPIRiT at various reduction factors tested. The motion simulations indicated the robustness of the proposed method to displacement of the subject. Phantom heating experiment further demonstrated the ability of the method to reconstruct temperature maps with less computation time and higher accuracy (RMSEs lower than 0.4°C) at a net reduction factor of 3.5 in the presence of large noise caused by a microwave needle. In-vivo experiments validated the feasibility of the proposed method to estimate temperature changes from undersampled k-space (net reduction factor 4.3) in presence of respiratory motion and complicated anatomical structure, while reducing computation time as much as 10-fold compared with the conventional k-space method.

CONCLUSION

The proposed method accelerates the PRF-shift MR thermometry and provides more accurate temperature maps in presence of motion with relatively short computation time, which may make real time imaging for MR-guided microwave ablation possible.

MR Image Reconstruction Using Block Matching and Adaptive Kernel Methods

An approach to Magnetic Resonance (MR) image reconstruction from undersampled data is proposed. Undersampling artifacts are removed using an iterative thresholding algorithm applied to nonlinearly transformed image block arrays. Each block array is transformed using kernel principal component analysis where the contribution of each image block to the transform depends in a nonlinear fashion on the distance to other image blocks. Elimination of undersampling artifacts is achieved by conventional principal component analysis in the nonlinear transform domain, projection onto the main components and back-mapping into the image domain. Iterative image reconstruction is performed by interleaving the proposed undersampling artifact removal step and gradient updates enforcing consistency with acquired k-space data. The algorithm is evaluated using retrospectively undersampled MR cardiac cine data and compared to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT reconstruction. Evaluation of image quality and root-mean-squared-error (RMSE) reveal improved image reconstruction for up to 8-fold undersampled data with the proposed approach relative to k-t SPARSE-SENSE, block matching with spatial Fourier filtering and k-t ℓ1-SPIRiT. In conclusion, block matching and kernel methods can be used for effective removal of undersampling artifacts in MR image reconstruction and outperform methods using standard compressed sensing and ℓ1-regularized parallel imaging methods.

Image Reconstruction for a Rotating Radiofrequency Coil (RRFC) Using Self-Calibrated Sensitivity From Radial Sampling

The purpose of this study was to develop a practical magnetic resonance imaging (MRI) scheme for the latest rotating radiofrequency coil (RRFC) design at 9.4 T. The new prototype RRFC was integrated with an optical sensor to facilitate recording of its angular positions relative to the sequence timing. In imaging, the RRFC was used together with radial k-space trajectories. To recover the image, the radial spokes were grouped according to the coil locations. Using an Eigen-decomposition approach, an array of location-dependent sensitivity maps was extracted from the central regions of the segmented k-space, enabling parallel-imaging techniques for image recovery in a straightforward manner. When the RRFC angular velocity is carefully designed and accurately controlled according to the sequence timing, the encoding by means of varying RRFC sensitivity maps can be accurately calibrated for a faithful image recovery. Approximations were made to counteract the variations of the RRFC angular velocity, providing successful image reconstruction at 9.4 T. The current study demonstrated a new and practical imaging scheme for RRFC-MRI. It is able to extract the temporally varying sensitivity maps retrospectively from the k-space acquisition itself, without resorting to electromagnetic simulation or numerical interpolation. The proposed imaging scheme and the supporting engineering solutions of the RRFC prototype enable accurate image reconstructions. These new developments pave the way for routine applications of the RRFC, and bode well for its further development in providing simultaneous multinuclear imaging by incorporating, for example, independent X-nuclear coil elements into the rotating structure.

3D Cartesian MRI with compressed sensing and variable view sharing using complementary poisson-disc sampling

PURPOSE

To enable robust, high spatio-temporal-resolution three-dimensional Cartesian MRI using a scheme incorporating a novel variable density random k-space sampling trajectory allowing flexible and retrospective selection of the temporal footprint with compressed sensing (CS).

METHODS

A complementary Poisson-disc k-space sampling trajectory was designed to allow view sharing and varying combinations of reduced view sharing with CS from the same prospective acquisition. These schemes were used for two-point Dixon-based dynamic contrast-enhanced MRI (DCE-MRI) of the breast and abdomen. Results were validated in vivo with a novel approach using variable-flip-angle data, which was retrospectively accelerated using the same methods but offered a ground truth.

RESULTS

In breast DCE-MRI, the temporal footprint could be reduced 2.3-fold retrospectively without introducing noticeable artifacts, improving depiction of rapidly enhancing lesions. Further, experiments with variable-flip-angle data showed that reducing view sharing improved accuracy in reconstruction and T₁ mapping. In abdominal MRI, 2.3-fold and 3.6-fold reductions in temporal footprint allowed reduced motion artifacts.

CONCLUSION

The complementary-Poisson-disc k-space sampling trajectory allowed a retrospective spatiotemporal resolution tradeoff using CS and view sharing, imparting robustness to motion and contrast enhancement. The technique was also validated using a novel approach of fully acquired variable-flip-angle acquisition. Magn Reson Med 77:1774-1785, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

CNR improvement of MP2RAGE from slice encoding directional acceleration

PURPOSE

While MP2RAGE shows the potential to generate B1 insensitive T1 contrast, the long TR of MP2RAGE (≥6s at 7T) is essential to provide the large dynamic range of apparent T1 relaxation for dual inversion time acquisitions. We present a 2 direction (2D) accelerated MP2RAGE, which provides an increased flip angle while maintaining similar dynamic recovery as 1D accelerated MP2RAGE.

METHOD

Simulations were conducted to optimize 2D accelerated MP2RAGE parameters and healthy subjects were scanned with 1D and 2D accelerated MP2RAGE at 7T. Images were compared visually and contrast to noise (CNR) between brain tissues was measured.

RESULT

Simulations showed that CNR is primarly determined by the TR, followed by the number of the first partition encoding steps in MP2RAGE. Keeping TR constant, a smaller number of partition encoding steps increases the achievable maximal CNR. In-vivo 2D MP2RAGE improves CNR between white and gray matters by 9% when compared to 1D accelerated MP2RAGE with identical voxel size.

CONCLUSION

We presented 2D accelated MP2RAGE at 7T with the increased flip angle. We show that this leads to CNR improvement, and consequently a reduction of scan time to be compared to 1D accelerated MP2RAGE.

Real-time free-breathing cardiac imaging with self-calibrated through-time radial GRAPPA

PURPOSE

Real-time free-breathing cardiac imaging with highly undersampled radial trajectories has previously been successfully demonstrated using calibrated radial generalized autocalibrating partially parallel acquisition (rGRAPPA). A self-calibrated approach for rGRAPPA is proposed that removes the need for the calibration prescan.

METHODS

To investigate the effect of various parameters on image quality, a comprehensive imaging study on one normal swine was performed. Root mean squared errors (RMSEs) were computed with respect to gold standard acquisitions, and several acquisition/reconstruction strategies were compared. Additionally, the method was tested on 13 human subjects, and RMSEs relative to standard through-time radial GRAPPA were computed.

RESULTS

Real-time images with high spatiotemporal resolution were obtained. Image quality was comparable to calibrated through-time rGRAPPA with endocardial and epicardial borders clearly delineated. In the swine, the average RMSE between self-calibrated and gold-standard calibrated images was 5.18 ± 0.84%. In normal human subjects, the average RMSE between self-calibrated and calibrated through-time rGRAPPA was 3.79 ± 0.64%. For lower accelerations rates (R = 6-8) image quality was similar to comparable calibrated scans though RMSE increased for higher degrees of undersampling (R = 12-16).

CONCLUSION

Highly accelerated real-time imaging with undersampled radial trajectories without additional calibration data is feasible. Image quality was acceptable for real-time cardiac MRI applications demanding high speed. Magn Reson Med 77:250-264, 2017. © 2016 Wiley Periodicals, Inc.

Desynchronization of Cartesian k-space sampling and periodic motion for improved retrospectively self-gated 3D lung MRI using quasi-random numbers

PURPOSE

To demonstrate that desynchronization between Cartesian k-space sampling and periodic motion in free-breathing lung MRI improves the robustness and efficiency of retrospective respiratory self-gating.

METHODS

Desynchronization was accomplished by reordering the phase (k_y ) and partition (k_z ) encoding of a three-dimensional FLASH sequence according to two-dimensional, quasi-random (QR) numbers. For retrospective respiratory self-gating, the k-space center signal (DC signal) was acquired separately after each encoded k-space line. QR sampling results in a uniform distribution of k-space lines after gating. Missing lines resulting from the gating process were reconstructed using iterative GRAPPA. Volunteer measurements were performed to compare quasi-random with conventional sampling. Patient measurements were performed to demonstrate the feasibility of QR sampling in a clinical setting.

RESULTS

The uniformly sampled k-space after retrospective gating allows for a more stable iterative GRAPPA reconstruction and improved ghost artifact reduction compared with conventional sampling. It is shown that this stability can either be used to reduce the total scan time or to reconstruct artifact-free data sets in different respiratory phases, both resulting in an improved efficiency of retrospective respiratory self-gating.

CONCLUSION

QR sampling leads to desynchronization between repeated data acquisition and periodic respiratory motion. This results in an improved motion artifact reduction in shorter scan time. Magn Reson Med 77:787-793, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Efficient parallel reconstruction for high resolution multishot spiral diffusion data with low rank constraint

PURPOSE

To propose a novel reconstruction method using parallel imaging with low rank constraint to accelerate high resolution multishot spiral diffusion imaging.

THEORY AND METHODS

The undersampled high resolution diffusion data were reconstructed based on a low rank (LR) constraint using similarities between the data of different interleaves from a multishot spiral acquisition. The self-navigated phase compensation using the low resolution phase data in the center of k-space was applied to correct shot-to-shot phase variations induced by motion artifacts. The low rank reconstruction was combined with sensitivity encoding (SENSE) for further acceleration. The efficiency of the proposed joint reconstruction framework, dubbed LR-SENSE, was evaluated through error quantifications and compared with ℓ1 regularized compressed sensing method and conventional iterative SENSE method using the same datasets.

RESULTS

It was shown that with a same acceleration factor, the proposed LR-SENSE method had the smallest normalized sum-of-squares errors among all the compared methods in all diffusion weighted images and DTI-derived index maps, when evaluated with different acceleration factors (R = 2, 3, 4) and for all the acquired diffusion directions.

CONCLUSION

Robust high resolution diffusion weighted image can be efficiently reconstructed from highly undersampled multishot spiral data with the proposed LR-SENSE method. Magn Reson Med 77:1359-1366, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Development of Real-Time Magnetic Resonance Imaging of Mouse Hearts at 9.4 Tesla--Simulations and First Application

A novel method for real-time magnetic resonance imaging for the assessment of cardiac function in mice at 9.4 T is proposed. The technique combines a highly undersampled radial gradient echo acquisition with an image reconstruction utilizing both parallel imaging and compressed sensing. Simulations on an in silico phantom were performed to determine the achievable acceleration factor and to optimize regularization parameters. Several parameters characterizing the quality of the reconstructed images (such as spatial and temporal image sharpness or compartment areas) were calculated for this purpose. Subsequently, double-gated segmented cine data as well as non-gated undersampled real-time data using only six projections per timeframe (temporal resolution  ∼ 10 ms) were acquired in a mid-ventricular slice of four normal mouse hearts in vivo. The highly accelerated data sets were then subjected to the introduced reconstruction technique and results were validated against the fully sampled references. Functional parameters obtained from real-time and fully sampled data agreed well with a comparable accuracy for left-ventricular volumes and a slightly larger scatter for mass. This study introduces and validates a real-time cine-MRI technique, which significantly reduces scan time in preclinical cardiac functional imaging and has the potential to investigate mouse models with abnormal heart rhythm.

Undersampled linogram trajectory for fast imaging (ULTI): experiments at 3 T and 7 T

In this study, the performance of linogram acquisition was investigated for the reconstruction of images from undersampled data using parallel imaging methods. The point spread function (PSF) of linogram sampling was analyzed for image sharpness and artifacts. Generalized auto-calibrating partially parallel acquisition was implemented for this new sampling scheme, and images were reconstructed with high acceleration rates. The results were compared with conventional radial sampling methods using simulations and phantom experiments at 3 T. Additionally, a human volunteer was scanned at 7 T. The results demonstrated that the PSF was sharper and the mean artifact power was lower for linogram sampling compared with radial sampling. Results of simulations and phantom experiments were in accord with the findings of the PSF analysis. In simulations, errors in the reconstructed images were lower for linogram sampling. In phantom experiments, fine details and sharp edges were preserved for linogram sampling, while details were blurred for radial sampling. The in vivo human study demonstrated that linogram sampling could provide high quality images of anatomy, even at high acceleration rates. Linogram sampling not only possesses the advantages of radial sampling, such as reduced sensitivity to motion and higher acceleration rates, but it also provides sharper images with fewer artifacts. Moreover, it is less prone to off-resonance artifacts compared with radial sampling. Copyright © 2016 John Wiley & Sons, Ltd.

Accelerating chemical exchange saturation transfer (CEST) MRI by combining compressed sensing and sensitivity encoding techniques

PURPOSE

To evaluate the feasibility of accelerated chemical-exchange-saturation-transfer (CEST) imaging using a combination of compressed sensing (CS) and sensitivity encoding (SENSE) at 3 Tesla.

THEORY AND METHODS

Two healthy volunteers and six high-grade glioma patients were recruited. Raw CEST image k-space data were acquired (with varied radiofrequency saturation power levels for the healthy volunteer study), and a sequential CS and SENSE reconstruction (CS-SENSE) was assessed. The MTR_asym (3.5 ppm) signals were compared with varied CS-SENSE acceleration factors.

RESULTS

In the healthy volunteer study, a CS-SENSE acceleration factor of R = 2 × 2 (CS × SENSE) was achieved without compromising the reconstructed MTR_asym (3.5 ppm) image quality. The MTR_asym (3.5 ppm) signals obtained from the CS-SENSE reconstruction with R = 2 × 2 were well preserved compared with the reference image (R = 2 for only SENSE). In the glioma patient study, the MTR_asym (3.5 ppm) signals were significantly higher in the tumor region (Gd-enhancing tumor core) than in the normal-appearing white matter (P < 0.001). There was no significant MTR_asym (3.5 ppm) difference between the reference image and CS-SENSE-reconstructed image in the acceleration factor of R = 2 × 2.

CONCLUSION

Combining the SENSE technique with CS (R = 2 × 2) enables considerable acceleration of CEST image acquisition and potentially has a wide range of clinical applications. Magn Reson Med 77:779-786, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

A subspace-based coil combination method for phased-array magnetic resonance imaging

PURPOSE

Coil-by-coil reconstruction methods are followed by coil combination to obtain a single image representing a spin density map. Typical coil combination methods, such as square-root sum-of-squares and adaptive coil combining, yield images that exhibit spatially varying modulation of image intensity. Existing practice is to first combine coils according to a signal-to-noise criterion, then postprocess to correct intensity inhomogeneity. If inhomogeneity is severe, however, intensity correction methods can yield poor results. The purpose of this article is to present an alternative optimality criterion for coil combination; the resulting procedure yields reduced intensity inhomogeneity while preserving contrast.

THEORY AND METHODS

A minimum mean squared error criterion is adopted for combining coils via a subspace decomposition. Techniques are compared using both simulated and in vivo data.

RESULTS

Experimental results for simulated and in vivo data demonstrate lower bias, higher signal-to-noise ratio (about 7×) and contrast-to-noise ratio (about 2×), compared to existing coil combination techniques.

CONCLUSION

The proposed coil combination method is noniterative and does not require estimation of coil sensitivity maps or image mask; the method is particularly suited to cases where intensity inhomogeneity is too severe for existing approaches.

Diagnostic quality assessment of compressed sensing accelerated magnetic resonance neuroimaging

PURPOSE

To determine the efficacy of compressed sensing (CS) reconstructions for specific clinical magnetic resonance neuroimaging applications beyond more conventional acceleration techniques such as parallel imaging (PI) and low-resolution acquisitions.

MATERIALS AND METHODS

Raw k-space data were acquired from five healthy volunteers on a 3T scanner using a 32-channel head coil using T2 -FLAIR, FIESTA-C, time of flight (TOF), and spoiled gradient echo (SPGR) sequences. In a series of blinded studies, three radiologists independently evaluated CS, PI (GRAPPA), and low-resolution images at up to 5× accelerations. Synthetic T2 -FLAIR images with artificial lesions were used to assess diagnostic accuracy for CS reconstructions.

RESULTS

CS reconstructions were of diagnostically acceptable quality at up to 4× acceleration for T2 -FLAIR and FIESTA-C (average qualitative scores 3.7 and 4.3, respectively, on a 5-point scale at 4× acceleration), and at up to 3× acceleration for TOF and SPGR (average scores 4.0 and 3.7, respectively, at 3× acceleration). The qualitative scores for CS reconstructions were significantly better than low-resolution images for T2 -FLAIR, FIESTA-C, and TOF and significantly better than GRAPPA for TOF and SPGR (Wilcoxon signed rank test, P < 0.05) with no significant difference found otherwise. Diagnostic accuracy was acceptable for both CS and low-resolution images at up to 3× acceleration (area under the ROC curve 0.97 and 0.96, respectively.)

CONCLUSION

Mild to moderate accelerations are possible for those sequences by a combined CS and PI reconstruction. Nevertheless, for certain sequences/applications one might mildly reduce the acquisition time by appropriately reducing the imaging resolution rather than the more complicated CS reconstruction. J. Magn. Reson. Imaging 2016;44:433-444.

Accelerated exponential parameterization of T2 relaxation with model-driven low rank and sparsity priors (MORASA)

PURPOSE

This work is to develop a novel image reconstruction method from highly undersampled multichannel acquisition to reduce the scan time of exponential parameterization of T2 relaxation.

THEORY AND METHODS

On top of the low-rank and joint-sparsity constraints, we propose to exploit the linear predictability of the T2 exponential decay to further improve the reconstruction of the T2-weighted images from undersampled acquisitions. Specifically, the exact rank prior (i.e., number of non-zero singular values) is adopted to enforce the spatiotemporal low rankness, while the mixed L2-L1 norm of the wavelet coefficients is used to promote joint sparsity, and the Hankel low-rank approximation is used to impose linear predictability, which integrates the exponential behavior of the temporal signal into the reconstruction process. An efficient algorithm is adopted to solve the reconstruction problem, where corresponding nonlinear filtering operations are performed to enforce corresponding priors in an iterative manner.

RESULTS

Both simulated and in vivo datasets with multichannel acquisition were used to demonstrate the feasibility of the proposed method. Experimental results have shown that the newly introduced linear predictability prior improves the reconstruction quality of the T2-weighted images and benefits the subsequent T2 mapping by achieving high-speed, high-quality T2 mapping compared with the existing fast T2 mapping methods.

CONCLUSION

This work proposes a novel fast T2 mapping method integrating the linear predictable property of the exponential decay into the reconstruction process. The proposed technique can effectively improve the reconstruction quality of the state-of-the-art fast imaging method exploiting image sparsity and spatiotemporal low rankness. Magn Reson Med 76:1865-1878, 2016. © 2016 International Society for Magnetic Resonance in Medicine.

R2*-corrected water-fat imaging using compressed sensing and parallel imaging

PURPOSE

To demonstrate an approach to water-fat separation with R2* correction using compressed sensing and parallel imaging.

METHODS

Acquisition times for chemical shift based water-fat separation imaging are lengthy, and many applications rely on image acceleration techniques. In this study, we present an integrated compressed sensing, parallel imaging, R2* corrected water-fat separation technique for water-fat imaging of highly accelerated acquisitions. Reconstruction times are reduced using coil compression.

RESULTS

The proposed technique is demonstrated using a customized IDEAL-SPGR pulse sequence to acquire retrospectively and prospectively undersampled datasets of the liver, calf, knee, and abdominal cavity. This technique is shown to offer comparable image quality relative to fully sampled reference images for a range of acceleration factors. At high acceleration factors, this technique is shown to offer improved image quality over parallel imaging.

CONCLUSION

A technique is described that uses compressed sensing and parallel imaging to reconstruct R2*-corrected water and fat images from accelerated datasets. Acceleration factors as high as 7.0 are shown with excellent image quality. These high acceleration factors enable water-fat separation with higher resolution or greater anatomical coverage in breath-hold applications.

Efficient Compressed Sensing SENSE pMRI Reconstruction With Joint Sparsity Promotion

The theory and techniques of compressed sensing (CS) have shown their potential as a breakthrough in accelerating k-space data acquisition for parallel magnetic resonance imaging (pMRI). However, the performance of CS reconstruction models in pMRI has not been fully maximized, and CS recovery guarantees for pMRI are largely absent. To improve reconstruction accuracy from parsimonious amounts of k-space data while maintaining flexibility, a new CS SENSitivity Encoding (SENSE) pMRI reconstruction framework promoting joint sparsity (JS) across channels (JS CS SENSE) is proposed in this paper. The recovery guarantee derived for the proposed JS CS SENSE model is demonstrated to be better than that of the conventional CS SENSE model and similar to that of the coil-by-coil CS model. The flexibility of the new model is better than the coil-by-coil CS model and the same as that of CS SENSE. For fast image reconstruction and fair comparisons, all the introduced CS-based constrained optimization problems are solved with split Bregman, variable splitting, and combined-variable splitting techniques. For the JS CS SENSE model in particular, these techniques lead to an efficient algorithm. Numerical experiments show that the reconstruction accuracy is significantly improved by JS CS SENSE compared with the conventional CS SENSE. In addition, an accurate residual-JS regularized sensitivity estimation model is also proposed and extended to calibration-less (CaL) JS CS SENSE. Numerical results show that CaL JS CS SENSE outperforms other state-of-the-art CS-based calibration-less methods in particular for reconstructing non-piecewise constant images.

High-temporospatial-resolution dynamic contrast-enhanced (DCE) wrist MRI with variable-density pseudo-random circular Cartesian undersampling (CIRCUS) acquisition: evaluation of perfusion in rheumatoid arthritis patients

This study is to evaluate highly accelerated three-dimensional (3D) dynamic contrast-enhanced (DCE) wrist MRI for assessment of perfusion in rheumatoid arthritis (RA) patients. A pseudo-random variable-density undersampling strategy, circular Cartesian undersampling (CIRCUS), was combined with k-t SPARSE-SENSE reconstruction to achieve a highly accelerated 3D DCE wrist MRI. Two healthy volunteers and 10 RA patients were studied. Two patients were on methotrexate (MTX) only (Group I) and the other eight were treated with a combination therapy of MTX and anti-tumor necrosis factor (TNF) therapy (Group II). Patients were scanned at baseline and 3 month follow-up. DCE MR images were used to evaluate perfusion in synovitis and bone marrow edema pattern in the RA wrist joints. A series of perfusion parameters was derived and compared with clinical disease activity scores of 28 joints (DAS28). 3D DCE wrist MR images were obtained with a spatial resolution of 0.3 × 0.3 × 1.5 mm(3) and temporal resolution of 5 s (with an acceleration factor of 20). The derived perfusion parameters, most notably transition time (dT) of synovitis, showed significant negative correlations with DAS28-ESR (r = -0.80, p < 0.05) and DAS28-CRP (r = -0.87, p < 0.05) at baseline and also correlated significantly with treatment responses evaluated by clinical score changes between baseline and 3 month follow-up (with DAS28-ESR r = -0.79, p < 0.05, and DAS28-CRP r = -0.82, p < 0.05). Highly accelerated 3D DCE wrist MRI with improved temporospatial resolution has been achieved in RA patients and provides accurate assessment of neovascularization and perfusion in RA joints, showing promise as a potential tool for evaluating treatment responses.

Development and testing of hyperpolarized (13)C MR calibrationless parallel imaging

A calibrationless parallel imaging technique developed previously for (1)H MRI was modified and tested for hyperpolarized (13)C MRI for applications requiring large FOV and high spatial resolution. The technique was demonstrated with both retrospective and prospective under-sampled data acquired in phantom and in vivo rat studies. A 2-fold acceleration was achieved using a 2D symmetric EPI readout equipped with random blips on the phase encode dimension. Reconstructed images showed excellent qualitative agreement with fully sampled data. Further acceleration can be achieved using acquisition schemes that incorporate multi-dimensional under-sampling.

Combining parallel detection of proton echo planar spectroscopic imaging (PEPSI) measurements with a data-consistency constraint improves SNR

One major challenge of MRSI is the poor signal-to-noise ratio (SNR), which can be improved by using a surface coil array. Here we propose to exploit the spatial sensitivity of different channels of a coil array to enforce the k-space data consistency (DC) in order to suppress noise and consequently to improve MRSI SNR. MRSI data were collected using a proton echo planar spectroscopic imaging (PEPSI) sequence at 3 T using a 32-channel coil array and were averaged with one, two and eight measurements (avg-1, avg-2 and avg-8). The DC constraint was applied using a regularization parameter λ of 1, 2, 3, 5 or 10. Metabolite concentrations were quantified using LCModel. Our results show that the suppression of noise by applying the DC constraint to PEPSI reconstruction yields up to 32% and 27% SNR gain for avg-1 and avg-2 data with λ = 5, respectively. According to the reported Cramer-Rao lower bounds, the improvement in metabolic fitting was significant (p < 0.01) when the DC constraint was applied with λ ≥ 2. Using the DC constraint with λ = 3 or 5 can minimize both root-mean-square errors and spatial variation for all subjects using the avg-8 data set as reference values. Our results suggest that MRSI reconstructed with a DC constraint can save around 70% of scanning time to obtain images and spectra with similar SNRs using λ = 5.

Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation

PURPOSE

This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion.

METHODS

Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing.

RESULTS

Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing.

CONCLUSION

Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation.

Improved quantification and mapping of anomalous pulmonary venous flow with four-dimensional phase-contrast MRI and interactive streamline rendering

BACKGROUND

Cardiac MRI is routinely performed for quantification of shunt flow in patients with anomalous pulmonary veins, but can be technically-challenging to perform. Four-dimensional phase-contrast (4D-PC) MRI has potential to simplify this exam. We sought to determine whether 4D-PC may be a viable clinical alternative to conventional 2D phase-contrast MR imaging.

METHODS

With institutional review board approval and HIPAA-compliance, we retrospectively identified all patients with anomalous pulmonary veins who underwent cardiac MRI at either 1.5 Tesla (T) or 3T with parallel-imaging compressed-sensing (PI-CS) 4D-PC between April, 2011 and October, 2013. A total of 15 exams were included (10 male, 5 female). Algorithms for interactive streamline visualization were developed and integrated into in-house software. Blood flow was measured at the valves, pulmonary arteries and veins, cavae, and any associated shunts. Pulmonary veins were mapped to their receiving atrial chamber with streamlines. The intraobserver, interobserver, internal consistency of flow measurements, and consistency with conventional MRI were then evaluated with Pearson correlation and Bland-Altman analysis.

RESULTS

Triplicate measurements of blood flow from 4D-PC were highly consistent, particularly at the aortic and pulmonary valves (cv 2-3%). Flow measurements were reproducible by a second observer (ρ = 0.986-0.999). Direct measurements of shunt volume from anomalous veins and intracardiac shunts matched indirect estimates from the outflow valves (ρ = 0.966). Measurements of shunt fraction using 4D-PC using any approach were more consistent with ventricular volumetric displacements than conventional 2D-PC (ρ = 0.972-0.991 versus 0.929).

CONCLUSION

Shunt flow may be reliably quantified with 4D-PC MRI, either indirectly or with detailed delineation of flow from multiple shunts. The 4D-PC may be a more accurate alternative to conventional MRI.

Radiotherapy planning using MRI

The use of magnetic resonance imaging (MRI) in radiotherapy (RT) planning is rapidly expanding. We review the wide range of image contrast mechanisms available to MRI and the way they are exploited for RT planning. However a number of challenges are also considered: the requirements that MR images are acquired in the RT treatment position, that they are geometrically accurate, that effects of patient motion during the scan are minimized, that tissue markers are clearly demonstrated, that an estimate of electron density can be obtained. These issues are discussed in detail, prior to the consideration of a number of specific clinical applications. This is followed by a brief discussion on the development of real-time MRI-guided RT.

A Convex Formulation for Magnetic Particle Imaging X-Space Reconstruction

Magnetic Particle Imaging (mpi) is an emerging imaging modality with exceptional promise for clinical applications in rapid angiography, cell therapy tracking, cancer imaging, and inflammation imaging. Recent publications have demonstrated quantitative mpi across rat sized fields of view with x-space reconstruction methods. Critical to any medical imaging technology is the reliability and accuracy of image reconstruction. Because the average value of the mpi signal is lost during direct-feedthrough signal filtering, mpi reconstruction algorithms must recover this zero-frequency value. Prior x-space mpi recovery techniques were limited to 1d approaches which could introduce artifacts when reconstructing a 3d image. In this paper, we formulate x-space reconstruction as a 3d convex optimization problem and apply robust a priori knowledge of image smoothness and non-negativity to reduce non-physical banding and haze artifacts. We conclude with a discussion of the powerful extensibility of the presented formulation for future applications.

Low-Cost High-Performance MRI

Magnetic Resonance Imaging (MRI) is unparalleled in its ability to visualize anatomical structure and function non-invasively with high spatial and temporal resolution. Yet to overcome the low sensitivity inherent in inductive detection of weakly polarized nuclear spins, the vast majority of clinical MRI scanners employ superconducting magnets producing very high magnetic fields. Commonly found at 1.5-3 tesla (T), these powerful magnets are massive and have very strict infrastructure demands that preclude operation in many environments. MRI scanners are costly to purchase, site, and maintain, with the purchase price approaching $1 M per tesla (T) of magnetic field. We present here a remarkably simple, non-cryogenic approach to high-performance human MRI at ultra-low magnetic field, whereby modern under-sampling strategies are combined with fully-refocused dynamic spin control using steady-state free precession techniques. At 6.5 mT (more than 450 times lower than clinical MRI scanners) we demonstrate (2.5 × 3.5 × 8.5) mm(3) imaging resolution in the living human brain using a simple, open-geometry electromagnet, with 3D image acquisition over the entire brain in 6 minutes. We contend that these practical ultra-low magnetic field implementations of MRI (<10 mT) will complement traditional MRI, providing clinically relevant images and setting new standards for affordable (<$50,000) and robust portable devices.

Evaluation of optimized breath-hold and free-breathing 3D ultrashort echo time contrast agent-free MRI of the human lung

PURPOSE

To evaluate an optimized stack of radials ultrashort echo time (UTE) 3D magnetic resonance imaging (MRI) sequence for breath-hold and free-breathing imaging of the human lung.

MATERIALS AND METHODS

A 3D stack of ultrashort echo time radials trajectory was optimized for coronal and axial lower-resolution breath-hold and higher-resolution free-breathing scans using Bloch simulations. The sequence was evaluated in 10 volunteers, without the use of contrast agents. Signal-to-noise ratio (SNR) mean and 95% confidence interval (CI) were determined from separate signal and noise images in a semiautomated fashion. The four scanning schemes were evaluated for significant differences in image quality using Student's t-test. Ten clinical patients were scanned with the sequence and findings were compared with concomitant computed tomography (CT) in nine patients. Breath-hold 3D spokes images were compared with 3D stack of radials in five volunteers. A Mann-Whitney U-test was performed to test significance in both cases.

RESULTS

Breath-hold imaging of the entire lung in volunteers was performed with SNR (mean = 42.5 [CI]: 35.5-49.5; mean = 34.3 [CI]: 28.6-40) in lung parenchyma for coronal and axial scans, respectively, which can be used as a quick scout scan. Longer respiratory triggered free-breathing scan enabled high-resolution UTE scanning with mean SNR of 14.2 ([CI]: 12.9-15.5) and 9.2 ([CI]: 8.2-10.2) for coronal and axial scans, respectively. Axial free-breathing scans showed significantly higher image quality (P = 0.008) than the three other scanning schemes. The mean score for comparison with CT was 1.67 (score 0: n = 0; 1: n = 3; 2: n = 6). There was no significant difference between CT and MRI (P = 0.25). 3D stack of radials images were significantly better than 3D spokes images (P < 0.001).

CONCLUSION

The optimized 3D stack of radials trajectory was shown to provide high-quality MR images of the lung parenchyma without the use of MRI contrast agents. The sequence may offer the possibility of breath-hold imaging and provides greater flexibility in trading off slice thickness and parallel imaging for scan time.

ESPIRiT--an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA

PURPOSE

Parallel imaging allows the reconstruction of images from undersampled multicoil data. The two main approaches are: SENSE, which explicitly uses coil sensitivities, and GRAPPA, which makes use of learned correlations in k-space. The purpose of this work is to clarify their relationship and to develop and evaluate an improved algorithm.

THEORY AND METHODS

A theoretical analysis shows: (1) The correlations in k-space are encoded in the null space of a calibration matrix. (2) Both approaches restrict the solution to a subspace spanned by the sensitivities. (3) The sensitivities appear as the main eigenvector of a reconstruction operator computed from the null space. The basic assumptions and the quality of the sensitivity maps are evaluated in experimental examples. The appearance of additional eigenvectors motivates an extended SENSE reconstruction with multiple maps, which is compared to existing methods.

RESULTS

The existence of a null space and the high quality of the extracted sensitivities are confirmed. The extended reconstruction combines all advantages of SENSE with robustness to certain errors similar to GRAPPA.

CONCLUSION

In this article the gap between both approaches is finally bridged. A new autocalibration technique combines the benefits of both.

Reducing acquisition time in clinical MRI by data undersampling and compressed sensing reconstruction

MRI is often the most sensitive or appropriate technique for important measurements in clinical diagnosis and research, but lengthy acquisition times limit its use due to cost and considerations of patient comfort and compliance. Once an image field of view and resolution is chosen, the minimum scan acquisition time is normally fixed by the amount of raw data that must be acquired to meet the Nyquist criteria. Recently, there has been research interest in using the theory of compressed sensing (CS) in MR imaging to reduce scan acquisition times. The theory argues that if our target MR image is sparse, having signal information in only a small proportion of pixels (like an angiogram), or if the image can be mathematically transformed to be sparse then it is possible to use that sparsity to recover a high definition image from substantially less acquired data. This review starts by considering methods of k-space undersampling which have already been incorporated into routine clinical imaging (partial Fourier imaging and parallel imaging), and then explains the basis of using compressed sensing in MRI. The practical considerations of applying CS to MRI acquisitions are discussed, such as designing k-space undersampling schemes, optimizing adjustable parameters in reconstructions and exploiting the power of combined compressed sensing and parallel imaging (CS-PI). A selection of clinical applications that have used CS and CS-PI prospectively are considered. The review concludes by signposting other imaging acceleration techniques under present development before concluding with a consideration of the potential impact and obstacles to bringing compressed sensing into routine use in clinical MRI.