XD-GRASP: Golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing

Recent advances in parallel imaging for MRI

Magnetic Resonance Imaging (MRI) is an essential technology in modern medicine. However, one of its main drawbacks is the long scan time needed to localize the MR signal in space to generate an image. This review article summarizes some basic principles and recent developments in parallel imaging, a class of image reconstruction techniques for shortening scan time. First, the fundamentals of MRI data acquisition are covered, including the concepts of k-space, undersampling, and aliasing. It is demonstrated that scan time can be reduced by sampling a smaller number of phase encoding lines in k-space; however, without further processing, the resulting images will be degraded by aliasing artifacts. Nearly all modern clinical scanners acquire data from multiple independent receiver coil arrays. Parallel imaging methods exploit properties of these coil arrays to separate aliased pixels in the image domain or to estimate missing k-space data using knowledge of nearby acquired k-space points. Three parallel imaging methods-SENSE, GRAPPA, and SPIRiT-are described in detail, since they are employed clinically and form the foundation for more advanced methods. These techniques can be extended to non-Cartesian sampling patterns, where the collected k-space points do not fall on a rectangular grid. Non-Cartesian acquisitions have several beneficial properties, the most important being the appearance of incoherent aliasing artifacts. Recent advances in simultaneous multi-slice imaging are presented next, which use parallel imaging to disentangle images of several slices that have been acquired at once. Parallel imaging can also be employed to accelerate 3D MRI, in which a contiguous volume is scanned rather than sequential slices. Another class of phase-constrained parallel imaging methods takes advantage of both image magnitude and phase to achieve better reconstruction performance. Finally, some applications are presented of parallel imaging being used to accelerate MR Spectroscopic Imaging.

Comprehensive Multi-Dimensional MRI for the Simultaneous Assessment of Cardiopulmonary Anatomy and Physiology

Diagnostic testing often assesses the cardiovascular or respiratory systems in isolation, ignoring the major pathophysiologic interactions between the systems in many diseases. When both systems are assessed currently, multiple modalities are utilized in costly fashion with burdensome logistics and decreased accessibility. Thus, we have developed a new acquisition and reconstruction paradigm using the flexibility of MRI to enable a comprehensive exam from a single 5-15 min scan. We constructed a compressive-sensing approach to pseudo-randomly acquire highly subsampled, multi-dimensionally-encoded and time-stamped data from which we reconstruct volumetric cardiac and respiratory motion phases, contrast-agent dynamics, and blood flow velocity fields. The proposed method, named XD flow, is demonstrated for (a) evaluating congenital heart disease, where the impact of bulk motion is reduced in a non-sedated neonatal patient and (b) where the observation of the impact of respiration on flow is necessary for diagnostics; (c) cardiopulmonary imaging, where cardiovascular flow, function, and anatomy information is needed along with pulmonary perfusion quantification; and in (d) renal function imaging, where blood velocities and glomerular filtration rates are simultaneously measured, which highlights the generality of the technique. XD flow has the ability to improve quantification and to provide additional data for patient diagnosis for comprehensive evaluations.

Fast, precise, and accurate myocardial T1 mapping using a radial MOLLI sequence with FLASH readout

PURPOSE

Quantitative cardiac MRI, and more particularly T₁ mapping, has become a most important modality to characterize myocardial tissue. In this work, the value of a radial variant of the conventional modified Look-Locker inversion recovery sequence (raMOLLI) is demonstrated.

METHODS

The raMOLLI acquisition scheme consisted of five radial echo trains of 80 spokes acquired using either a fast low-angle shot (FLASH) or a true fast imaging with steady-state-precession (TrueFISP) readout at different time points after a single magnetization inversion. View sharing combined with a compressed sensing algorithm allowed the reconstruction of 50 images along the T₁ relaxation recovery curve, to which a dictionary-fitting approach was applied to estimate T₁ . The sequence was validated on a nine-vial phantom, on 19 healthy subjects, and one patient suffering from dilated cardiomyopathy.

RESULTS

The raMOLLI sequence allowed a significant decrease of myocardial T₁ map acquisition time down to five heartbeats, while exhibiting a higher degree of accuracy and a comparable precision on T₁ value estimation than the conventional modified Look-Locker inversion recovery sequence. The FLASH readout demonstrated a better robustness to B₀ inhomogeneities than TrueFISP, and was therefore preferred for in vivo acquisitions.

CONCLUSIONS

This sequence represents a good candidate for ultrafast acquisition of myocardial T₁ maps. Magn Reson Med 79:1387-1398, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Recent Advances in Cardiovascular Magnetic Resonance: Techniques and Applications

Cardiovascular magnetic resonance imaging has become the gold standard for evaluating myocardial function, volumes, and scarring. Additionally, cardiovascular magnetic resonance imaging is unique in its comprehensive tissue characterization, including assessment of myocardial edema, myocardial siderosis, myocardial perfusion, and diffuse myocardial fibrosis. Cardiovascular magnetic resonance imaging has become an indispensable tool in the evaluation of congenital heart disease, heart failure, cardiac masses, pericardial disease, and coronary artery disease. This review will highlight some recent novel cardiovascular magnetic resonance imaging techniques, concepts, and applications.

Multiecho pseudo-golden angle stack of stars thermometry with high spatial and temporal resolution using k-space weighted image contrast

PURPOSE

Implement and evaluate a 3D MRI method to measure temperature changes with high spatial and temporal resolution and large field of view.

METHODS

A multiecho pseudo-golden angle stack-of-stars (SOS) sequence with k-space weighted image contrast (KWIC) reconstruction was implemented to simultaneously measure multiple quantities, including temperature, initial signal magnitude M(0), transverse relaxation time ( T2*), and water/fat images. Respiration artifacts were corrected using self-navigation. KWIC artifacts were removed using a multi-baseline library. The phases of the multiple echo images were combined to improve proton resonance frequency precision. Temperature precision was tested through in vivo breast imaging (N = 5 healthy volunteers) using both coronal and sagittal orientations and with focused ultrasound (FUS) heating in a pork phantom using a breast specific MR-guided FUS system.

RESULTS

Temperature measurement precision was significantly improved after echo combination when compared with the no echo combination case (spatial average of the standard deviation through time of 0.3-1.0 and 0.7-1.9°C, respectively). Temperature measurement accuracy during heating was comparable to a 3D seg-EPI sequence. M(0) and T2* values showed temperature dependence during heating in pork adipose tissue.

CONCLUSION

A self-navigated 3D multiecho SOS sequence with dynamic KWIC reconstruction is a promising thermometry method that provides multiple temperature sensitive quantitative values. Magn Reson Med 79:1407-1419, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Rigid-body motion correction of the liver in image reconstruction for golden-angle stack-of-stars DCE MRI

PURPOSE

Respiratory motion can affect pharmacokinetic perfusion parameters quantified from liver dynamic contrast-enhanced MRI. Image registration can be used to align dynamic images after reconstruction. However, intra-image motion blur remains after alignment and can alter the shape of contrast-agent uptake curves. We introduce a method to correct for inter- and intra-image motion during image reconstruction.

METHODS

Sixteen liver dynamic contrast-enhanced MRI examinations of nine subjects were performed using a golden-angle stack-of-stars sequence. For each examination, an image time series with high temporal resolution but severe streak artifacts was reconstructed. Images were aligned using region-limited rigid image registration within a region of interest covering the liver. The transformations resulting from alignment were used to correct raw data for motion by modulating and rotating acquired lines in k-space. The corrected data were then reconstructed using view sharing.

RESULTS

Portal-venous input functions extracted from motion-corrected images had significantly greater peak signal enhancements (mean increase: 16%, t-test, P <  0.001) than those from images aligned using image registration after reconstruction. In addition, portal-venous perfusion maps estimated from motion-corrected images showed fewer artifacts close to the edge of the liver.

CONCLUSIONS

Motion-corrected image reconstruction restores uptake curves distorted by motion. Motion correction also reduces motion artifacts in estimated perfusion parameter maps. Magn Reson Med 79:1345-1353, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Multi-cycle Reconstruction of Cardiac MRI for the Analysis of Inter-ventricular Septum Motion During Free Breathing

Small variations in left-ventricular preload due to respiration produce measurable changes in cardiac function in normal subjects. We show that this mechanism is altered in patients with reduced ejection fraction (EF), hypertrophy, or volume-loaded right ventricle (RV). We propose a multi-dimensional retrospective image reconstruction, based on an adaptive, soft classification of data into respiratory and cardiac phases, to study these effects.

5D whole-heart sparse MRI

PURPOSE

A 5D whole-heart sparse imaging framework is proposed for simultaneous assessment of myocardial function and high-resolution cardiac and respiratory motion-resolved whole-heart anatomy in a single continuous noncontrast MR scan.

METHODS

A non-electrocardiograph (ECG)-triggered 3D golden-angle radial balanced steady-state free precession sequence was used for data acquisition. The acquired 3D k-space data were sorted into a 5D dataset containing separated cardiac and respiratory dimensions using a self-extracted respiratory motion signal and a recorded ECG signal. Images were then reconstructed using XD-GRASP, a multidimensional compressed sensing technique exploiting correlations/sparsity along cardiac and respiratory dimensions. 5D whole-heart imaging was compared with respiratory motion-corrected 3D and 4D whole-heart imaging in nine volunteers for evaluation of the myocardium, great vessels, and coronary arteries. It was also compared with breath-held, ECG-gated 2D cardiac cine imaging for validation of cardiac function quantification.

RESULTS

5D whole-heart images received systematic higher quality scores in the myocardium, great vessels and coronary arteries. Quantitative coronary sharpness and length were always better for the 5D images. Good agreement was obtained for quantification of cardiac function compared with 2D cine imaging.

CONCLUSION

5D whole-heart sparse imaging represents a robust and promising framework for simplified comprehensive cardiac MRI without the need for breath-hold and motion correction. Magn Reson Med 79:826-838, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Magnetic resonance imaging of myocardial strain: A review of current approaches

Contraction of the heart is central to its purpose of pumping blood around the body. While simple global function measures (such as the ejection fraction) are most commonly used in the clinical assessment of cardiac function, MRI also provides a range of approaches for quantitatively characterizing regional cardiac function, including the local deformation (or strain) within the heart wall. While they have been around for some years, these methods are still undergoing further technical development, and they have had relatively little clinical evaluation. However, they can provide potentially useful new ways to assess cardiac function, which may be able to contribute to better classification and treatment of heart disease. This article provides some basic background on the physical and physiological factors that determine the motion of the heart, in health and disease and then reviews some of the ways that MRI methods are being developed to image and quantify strain within the myocardium.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017;46:1263-1280.

Free-breathing liver fat quantification using a multiecho 3D stack-of-radial technique

PURPOSE

The diagnostic gold standard for nonalcoholic fatty liver disease is an invasive biopsy. Noninvasive Cartesian MRI fat quantification remains limited to a breath-hold (BH). In this work, a novel free-breathing 3D stack-of-radial (FB radial) liver fat quantification technique is developed and evaluated in a preliminary study.

METHODS

Phantoms and healthy subjects (n = 11) were imaged at 3 Tesla. The proton-density fat fraction (PDFF) determined using FB radial (with and without scan acceleration) was compared to BH single-voxel MR spectroscopy (SVS) and BH 3D Cartesian MRI using linear regression (correlation coefficient ρ and concordance coefficient ρ_c ) and Bland-Altman analysis.

RESULTS

In phantoms, PDFF showed significant correlation (ρ > 0.998, ρ_c  > 0.995) and absolute mean differences < 2.2% between FB radial and BH SVS, as well as significant correlation (ρ > 0.999, ρ_c  > 0.998) and absolute mean differences < 0.6% between FB radial and BH Cartesian. In the liver and abdomen, PDFF showed significant correlation (ρ > 0.986, ρ_c  > 0.985) and absolute mean differences < 1% between FB radial and BH SVS, as well as significant correlation (ρ > 0.996, ρ_c  > 0.995) and absolute mean differences < 0.9% between FB radial and BH Cartesian.

CONCLUSION

Accurate 3D liver fat quantification can be performed in 1 to 2 min using a novel FB radial technique. Magn Reson Med 79:370-382, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

High-Resolution Self-Gated Dynamic Abdominal MRI Using Manifold Alignment

We present a novel retrospective self-gating method based on manifold alignment (MA), which enables reconstruction of free breathing, high spatial, and temporal resolution abdominal magnetic resonance imaging sequences. Based on a radial golden-angle acquisition trajectory, our method enables a multidimensional self-gating signal to be extracted from the k -space data for more accurate motion representation. The k -space radial profiles are evenly divided into a number of overlapping groups based on their radial angles. MA is then used to simultaneously learn and align the low dimensional manifolds of all groups, and embed them into a common manifold. In the manifold, k -space profiles that represent similar respiratory positions are close to each other. Image reconstruction is performed by combining radial profiles with evenly distributed angles that are close in the manifold. Our method was evaluated on both 2-D and 3-D synthetic and in vivo data sets. On the synthetic data sets, our method achieved high correlation with the ground truth in terms of image intensity and virtual navigator values. Using the in vivo data, compared with a state-of-the-art approach based on the center of k -space gating, our method was able to make use of much richer profile data for self-gating, resulting in statistically significantly better quantitative measurements in terms of organ sharpness and image gradient entropy.

Cardiac 4D phase-contrast CMR at 9.4 T using self-gated ultra-short echo time (UTE) imaging

BACKGROUND

Time resolved 4D phase contrast (PC) cardiovascular magnetic resonance (CMR) in mice is challenging due to long scan times, small animal ECG-gating and the rapid blood flow and cardiac motion of small rodents. To overcome several of these technical challenges we implemented a retrospectively self-gated 4D PC radial ultra-short echo-time (UTE) acquisition scheme and assessed its performance in healthy mice by comparing the results with those obtained with an ECG-triggered 4D PC fast low angle shot (FLASH) sequence.

METHODS

Cardiac 4D PC CMR images were acquired at 9.4 T in healthy mice using the proposed self-gated radial center-out UTE acquisition scheme (TE/TR of 0.5 ms/3.1 ms) and a standard Cartesian 4D PC imaging sequence (TE/TR of 2.1 ms/5.0 ms) with a four-point Hadamard flow encoding scheme. To validate the proposed UTE flow imaging technique, experiments on a flow phantom with variable pump rates were performed.

RESULTS

The anatomical images and flow velocity maps of the proposed 4D PC UTE technique showed reduced artifacts and an improved SNR (left ventricular cavity (LV): 8.9 ± 2.5, myocardium (MC): 15.7 ± 1.9) compared to those obtained using a typical Cartesian FLASH sequence (LV: 5.6 ± 1.2, MC: 10.1 ± 1.4) that was used as a reference. With both sequences comparable flow velocities were obtained in the flow phantom as well as in the ascending aorta (UTE: 132.8 ± 18.3 cm/s, FLASH: 134.7 ± 13.4 cm/s) and pulmonary artery (UTE: 78.5 ± 15.4 cm/s, FLASH: 86.6 ± 6.2 cm/s) of the animals. Self-gated navigator signals derived from information of the oversampled k-space center were successfully extracted for all animals with a higher gating efficiency of time spent on acquiring gated data versus total measurement time (UTE: 61.8 ± 11.5%, FLASH: 48.5 ± 4.9%).

CONCLUSIONS

The proposed self-gated 4D PC UTE sequence enables robust and accurate flow velocity mapping of the mouse heart in vivo at high magnetic fields. At the same time SNR, gating efficiency, flow artifacts and image quality all improved compared to the images obtained using the well-established, ECG-triggered, 4D PC FLASH sequence.

Respiratory motion compensation for simultaneous PET/MR based on highly undersampled MR data

PURPOSE

Positron emission tomography (PET) of the thorax region is impaired by respiratory patient motion. To account for motion, the authors propose a new method for PET/magnetic resonance (MR) respiratory motion compensation (MoCo), which uses highly undersampled MR data with acquisition times as short as 1 min/bed.

METHODS

The proposed PET/MR MoCo method (4D jMoCo PET) uses radial MR data to estimate the respiratory patient motion employing MR joint motion estimation and image reconstruction with temporal median filtering. Resulting motion vector fields are incorporated into the system matrix of the PET reconstruction. The proposed approach is evaluated for the thorax region utilizing a PET/MR simulation with 1 min MR acquisition time and simultaneous PET/MR measurements of six patients with MR acquisition times of 1 and 5 min and radial undersampling factors of 11.2 and 2.2, respectively. Reconstruction results are compared to 3D PET, 4D gated PET and a standard MoCo method (4D sMoCo PET), which performs iterative image reconstruction and motion estimation sequentially. Quantitative analysis comprises the parameters SUV_mean, SUV_max, full width at half-maximum/lesion volume, contrast and signal-to-noise ratio.

RESULTS

For simulated PET data, our quantitative analysis shows that the proposed 4D jMoCo PET approach with temporal filtering achieves the best quantification accuracy of all tested reconstruction methods with a mean absolute deviation of 2.3% when compared to the ground truth. For measured PET patient data, the mean absolute deviation of 4D jMoCo PET using a 1 min MR acquisition for motion estimation is 2.1% relative to the 5 min MR acquisition. This demonstrates a robust behavior even in case of strong undersampling at MR acquisition times as short as 1 min. In contrast, 4D sMoCo PET shows considerable reduction of quantification accuracy for the 1 min MR acquisition time. Relative to 3D PET, the proposed 4D jMoCo PET approach with temporal filtering yields an average increase of SUV_mean, SUV_max, and contrast of 29.9% and 13.8% for simulated and measured PET data, respectively.

CONCLUSIONS

Employing artifact-robust motion estimation enables PET/MR respiratory MoCo with MR acquisition times as short as 1 min/bed improving PET image quality and quantification accuracy.

Respiratory motion-resolved, self-gated 4D-MRI using rotating cartesian k-space (ROCK)

PURPOSE

To propose and validate a respiratory motion resolved, self-gated (SG) 4D-MRI technique to assess patient-specific breathing motion of abdominal organs for radiation treatment planning.

METHODS

The proposed 4D-MRI technique was based on the balanced steady-state free-precession (bSSFP) technique and 3D k-space encoding. A novel rotating cartesian k-space (ROCK) reordering method was designed which incorporates repeatedly sampled k-space centerline as the SG motion surrogate and allows for retrospective k-space data binning into different respiratory positions based on the amplitude of the surrogate. The multiple respiratory-resolved 3D k-space data were subsequently reconstructed using a joint parallel imaging and compressed sensing method with spatial and temporal regularization. The proposed 4D-MRI technique was validated using a custom-made dynamic motion phantom and was tested in six healthy volunteers, in whom quantitative diaphragm and kidney motion measurements based on 4D-MRI images were compared with those based on 2D-CINE images.

RESULTS

The 5-minute 4D-MRI scan offers high-quality volumetric images in 1.2 × 1.2 × 1.6 mm³ and eight respiratory positions, with good soft-tissue contrast. In phantom experiments with triangular motion waveform, the motion amplitude measurements based on 4D-MRI were 11.89% smaller than the ground truth, whereas a -12.5% difference was expected due to data binning effects. In healthy volunteers, the difference between the measurements based on 4D-MRI and the ones based on 2D-CINE were 6.2 ± 4.5% for the diaphragm, 8.2 ± 4.9% and 8.9 ± 5.1% for the right and left kidney.

CONCLUSION

The proposed 4D-MRI technique could provide high-resolution, high-quality, respiratory motion-resolved 4D images with good soft-tissue contrast and are free of the "stitching" artifacts usually seen on 4D-CT and 4D-MRI based on resorting 2D-CINE. It could be used to visualize and quantify abdominal organ motion for MRI-based radiation treatment planning.

Multiresolution imaging using golden angle stack-of-stars and compressed sensing for dynamic MR urography

PURPOSE

To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo.

MATERIALS AND METHODS

A three-dimensional golden-angle radial stack-of-stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution reconstruction and analysis was performed using arterial input function reconstructed at 1-s. temporal resolution and renal dynamic data reconstructed using compressed sensing (CS) with 4-s temporal resolution. The method was first validated using simulations and the clinical utility of the technique was evaluated by comparing the GFR estimates from the proposed method to the estimated GFR (eGFR) obtained from serum creatinine for 10 subjects.

RESULTS

The 4-s temporal resolution CS images minimized streaking artifacts and noise while the 1-s temporal resolution AIF minimized errors in GFR estimates. A paired t-test showed that there was no statistically significant difference between MRI based total GFR values and serum creatinine based eGFR estimates (P = 0.92).

CONCLUSION

We have demonstrated the feasibility of multiresolution MRI using a golden angle radial stack-of-stars scheme to accurately estimate GFR as well as produce diagnostic quality dynamic images in vivo.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:303-311.

Self-gated fetal cardiac MRI with tiny golden angle iGRASP: A feasibility study

PURPOSE

To develop and assess a technique for self-gated fetal cardiac cine magnetic resonance imaging (MRI) using tiny golden angle radial sampling combined with iGRASP (iterative Golden-angle RAdial Sparse Parallel) for accelerated acquisition based on parallel imaging and compressed sensing.

MATERIALS AND METHODS

Fetal cardiac data were acquired from five volunteers in gestational week 29-37 at 1.5T using tiny golden angles for eddy currents reduction. The acquired multicoil radial projections were input to a principal component analysis-based compression stage. The cardiac self-gating (CSG) signal for cardiac gating was extracted from the acquired radial projections and the iGRASP reconstruction procedure was applied. In all acquisitions, a total of 4000 radial spokes were acquired within a breath-hold of less than 15 seconds using a balanced steady-state free precession pulse sequence. The images were qualitatively compared by two independent observers (on a scale of 1-4) to a single midventricular cine image from metric optimized gating (MOG) and real-time acquisitions.

RESULTS

For iGRASP and MOG images, good overall image quality (2.8 ± 0.4 and 2.6 ± 1.3, respectively, for observer 1; 3.6 ± 0.5 and 3.4 ± 0.9, respectively, for observer 2) and cardiac diagnostic quality (3.8 ± 0.4 and 3.4 ± 0.9, respectively, for observer 1; 3.6 ± 0.5 and 3.6 ± 0.9, respectively, for observer 2) were obtained, with visualized myocardial thickening over the cardiac cycle and well-defined myocardial borders to ventricular lumen and liver/lung tissue. For iGRASP, MOG, and real time, left ventricular lumen diameter (14.1 ± 2.2 mm, 14.2 ± 1.9 mm, 14.7 ± 1.1 mm, respectively) and wall thickness (2.7 ± 0.3 mm, 2.6 ± 0.3 mm, 3.0 ± 0.4, respectively) showed agreement and no statistically significant difference was found (all P > 0.05). Images with iGRASP tended to have higher overall image quality scores compared with MOG and particularly real-time images, albeit not statistically significant in this feasibility study (P > 0.99 and P = 0.12, respectively).

CONCLUSION

Fetal cardiac cine MRI can be performed with iGRASP using tiny golden angles and CSG. Comparison with other fetal cardiac cine MRI methods showed that the proposed method produces high-quality fetal cardiac reconstructions.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:207-217.

Highly-accelerated self-gated free-breathing 3D cardiac cine MRI: validation in assessment of left ventricular function

OBJECTIVE

This work presents a highly-accelerated, self-gated, free-breathing 3D cardiac cine MRI method for cardiac function assessment.

MATERIALS AND METHODS

A golden-ratio profile based variable-density, pseudo-random, Cartesian undersampling scheme was implemented for continuous 3D data acquisition. Respiratory self-gating was achieved by deriving motion signal from the acquired MRI data. A multi-coil compressed sensing technique was employed to reconstruct 4D images (3D+time). 3D cardiac cine imaging with self-gating was compared to bellows gating and the clinical standard breath-held 2D cine imaging for evaluation of self-gating accuracy, image quality, and cardiac function in eight volunteers. Reproducibility of 3D imaging was assessed.

RESULTS

Self-gated 3D imaging provided an image quality score of 3.4 ± 0.7 vs 4.0 ± 0 with the 2D method (p = 0.06). It determined left ventricular end-systolic volume as 42.4 ± 11.5 mL, end-diastolic volume as 111.1 ± 24.7 mL, and ejection fraction as 62.0 ± 3.1%, which were comparable to the 2D method, with bias ± 1.96 × SD of -0.8 ± 7.5 mL (p = 0.90), 2.6 ± 3.3 mL (p = 0.84) and 1.4 ± 6.4% (p = 0.45), respectively.

CONCLUSION

The proposed 3D cardiac cine imaging method enables reliable respiratory self-gating performance with good reproducibility, and provides comparable image quality and functional measurements to 2D imaging, suggesting that self-gated, free-breathing 3D cardiac cine MRI framework is promising for improved patient comfort and cardiac MRI scan efficiency.

Free breathing whole-heart 3D CINE MRI with self-gated Cartesian trajectory

Purpose

To present a method that uses a novel free-running self-gated acquisition to achieve isotropic resolution in whole heart 3D Cartesian cardiac CINE MRI.

Material and methods

3D cardiac CINE MRI using navigator gating results in long acquisition times. Recently, several frameworks based on self-gated non-Cartesian trajectories have been proposed to accelerate this acquisition. However, non-Cartesian reconstructions are computationally expensive due to gridding, particularly in 3D. In this work, we propose a novel highly efficient self-gated Cartesian approach for 3D cardiac CINE MRI. Acquisition is performed using CArtesian trajectory with Spiral PRofile ordering and Tiny golden angle step for eddy current reduction (so called here CASPR-Tiger). Data is acquired continuously under free breathing (retrospective ECG gating, no preparation pulses interruption) for 4–5 min and 4D whole-heart volumes (3D + cardiac phases) with isotropic spatial resolution are reconstructed from all available data using a soft gating technique combined with temporal total variation (TV) constrained iterative SENSE reconstruction.

Results

For data acquired on eight healthy subjects and three patients, the reconstructed images using the proposed method had good contrast and spatio-temporal variations, correctly recovering diastolic and systolic cardiac phases. Non-significant differences (P > 0.05) were observed in cardiac functional measurements obtained with proposed 3D approach and gold standard 2D multi-slice breath-hold acquisition.

Conclusion

The proposed approach enables isotropic 3D whole heart Cartesian cardiac CINE MRI in 4 to 5 min free breathing acquisition.

•

A novel self-gated 3D Cartesian acquisition is proposed for free breathing whole-heart cardiac MRI

•

The proposed framework has efficient k-space sampling, better eddy current performance and high computational efficiency

•

The Proposed method is able to achieve high spatio-temporal resolution 3D cardiac CINE

•

The proposed method only requires four to five minute free breathing scan

Compressed sensing for body MRI

The introduction of compressed sensing for increasing imaging speed in magnetic resonance imaging (MRI) has raised significant interest among researchers and clinicians, and has initiated a large body of research across multiple clinical applications over the last decade. Compressed sensing aims to reconstruct unaliased images from fewer measurements than are traditionally required in MRI by exploiting image compressibility or sparsity. Moreover, appropriate combinations of compressed sensing with previously introduced fast imaging approaches, such as parallel imaging, have demonstrated further improved performance. The advent of compressed sensing marks the prelude to a new era of rapid MRI, where the focus of data acquisition has changed from sampling based on the nominal number of voxels and/or frames to sampling based on the desired information content. This article presents a brief overview of the application of compressed sensing techniques in body MRI, where imaging speed is crucial due to the presence of respiratory motion along with stringent constraints on spatial and temporal resolution. The first section provides an overview of the basic compressed sensing methodology, including the notion of sparsity, incoherence, and nonlinear reconstruction. The second section reviews state-of-the-art compressed sensing techniques that have been demonstrated for various clinical body MRI applications. In the final section, the article discusses current challenges and future opportunities.

LEVEL OF EVIDENCE

5 J. Magn. Reson. Imaging 2017;45:966-987.

Accelerated dynamic EPR imaging using fast acquisition and compressive recovery

Electron paramagnetic resonance (EPR) allows quantitative imaging of tissue redox status, which provides important information about ischemic syndromes, cancer and other pathologies. For continuous wave EPR imaging, however, poor signal-to-noise ratio and low acquisition efficiency limit its ability to image dynamic processes in vivo including tissue redox, where conditions can change rapidly. Here, we present a data acquisition and processing framework that couples fast acquisition with compressive sensing-inspired image recovery to enable EPR-based redox imaging with high spatial and temporal resolutions. The fast acquisition (FA) allows collecting more, albeit noisier, projections in a given scan time. The composite regularization based processing method, called spatio-temporal adaptive recovery (STAR), not only exploits sparsity in multiple representations of the spatio-temporal image but also adaptively adjusts the regularization strength for each representation based on its inherent level of the sparsity. As a result, STAR adjusts to the disparity in the level of sparsity across multiple representations, without introducing any tuning parameter. Our simulation and phantom imaging studies indicate that a combination of fast acquisition and STAR (FASTAR) enables high-fidelity recovery of volumetric image series, with each volumetric image employing less than 10 s of scan. In addition to image fidelity, the time constants derived from FASTAR also match closely to the ground truth even when a small number of projections are used for recovery. This development will enhance the capability of EPR to study fast dynamic processes that cannot be investigated using existing EPR imaging techniques.

Use of self-gated radial cardiovascular magnetic resonance to detect and classify arrhythmias (atrial fibrillation and premature ventricular contraction)

BACKGROUND

Arrhythmia can significantly alter the image quality of cardiovascular magnetic resonance (CMR); automatic detection and sorting of the most frequent types of arrhythmias during the CMR acquisition could potentially improve image quality. New CMR techniques, such as non-Cartesian CMR, can allow self-gating: from cardiac motion-related signal changes, we can detect cardiac cycles without an electrocardiogram. We can further use this data to obtain a surrogate for RR intervals (valley intervals: VV). Our purpose was to evaluate the feasibility of an automated method for classification of non-arrhythmic (NA) (regular cycles) and arrhythmic patients (A) (irregular cycles), and for sorting of common arrhythmia patterns between atrial fibrillation (AF) and premature ventricular contraction (PVC), using the cardiac motion-related signal obtained during self-gated free-breathing radial cardiac cine CMR with compressed sensing reconstruction (XD-GRASP).

METHODS

One hundred eleven patients underwent cardiac XD-GRASP CMR between October 2015 and February 2016; 33 were included for retrospective analysis with the proposed method (6 AF, 8 PVC, 19 NA; by recent ECG). We analyzed the VV, using pooled statistics (histograms) and sequential analysis (Poincaré plots), including the median (medVV), the weighted mean (meanVV), the total number of VV values (VVval), and the total range (VVTR) and half range (VVHR) of the cumulative frequency distribution of VV, including the median to half range (medVV/VVHR) and the half range to total range (VVHR/VVTR) ratios. We designed a simple algorithm for using the VV results to differentiate A from NA, and AF from PVC.

RESULTS

Between NA and A, meanVV, VVval, VVTR, VVHR, medVV/VVHR and VVHR/VVTR ratios were significantly different (p values = 0.00014, 0.0027, 0.000028, 5×10-9, 0.002, respectively). Between AF and PVC, meanVV, VVval and medVV/VVHR ratio were significantly different (p values = 0.018, 0.007, 0.044, respectively). Using our algorithm, sensitivity, specificity, and accuracy were 93 %, 95 % and 94 % to discriminate between NA and A, and 83 %, 71 %, and 77 % to discriminate between AF and PVC, respectively; areas under the ROC curve were 0.93 and 0.89.

CONCLUSIONS

Our study shows we can reliably detect arrhythmias and differentiate AF from PVC, using self-gated cardiac cine XD-GRASP CMR.

Motion correction based reconstruction method for compressively sampled cardiac MR imaging

Respiratory motion during Magnetic Resonance (MR) acquisition causes strong blurring artifacts in the reconstructed images. These artifacts become more pronounced when used with the fast imaging reconstruction techniques like compressed sensing (CS). Recently, an MR reconstruction technique has been done with the help of compressed sensing (CS), to provide good quality sparse images from the highly under-sampled k-space data. In order to maximize the benefits of CS, it is obvious to use CS with the motion corrected samples. In this paper, we propose a novel CS based motion corrected image reconstruction technique. First, k-space data have been assigned to different respiratory state with the help of frequency domain phase correlation method. Then, multiple sparsity constraints has been used to provide good quality reconstructed cardiac cine images with the highly under-sampled k-space data. The proposed method exploits the multiple sparsity constraints, in combination with demon based registration technique and a novel reconstruction technique to provide the final motion free images. The proposed method is very simple to implement in clinical settings as compared to existing motion corrected methods. The performance of the proposed method is examined using simulated data and clinical data. Results show that this method performs better than the reconstruction of CS based method of cardiac cine images. Different acceleration rates have been used to show the performance of the proposed method.

Free-breathing volumetric fat/water separation by combining radial sampling, compressed sensing, and parallel imaging

PURPOSE

Conventional fat/water separation techniques require that patients hold breath during abdominal acquisitions, which often fails and limits the achievable spatial resolution and anatomic coverage. This work presents a novel approach for free-breathing volumetric fat/water separation.

METHODS

Multiecho data are acquired using a motion-robust radial stack-of-stars three-dimensional GRE sequence with bipolar readout. To obtain fat/water maps, a model-based reconstruction is used that accounts for the off-resonant blurring of fat and integrates both compressed sensing and parallel imaging. The approach additionally enables generation of respiration-resolved fat/water maps by detecting motion from k-space data and reconstructing different respiration states. Furthermore, an extension is described for dynamic contrast-enhanced fat-water-separated measurements.

RESULTS

Uniform and robust fat/water separation is demonstrated in several clinical applications, including free-breathing noncontrast abdominal examination of adults and a pediatric subject with both motion-averaged and motion-resolved reconstructions, as well as in a noncontrast breast exam. Furthermore, dynamic contrast-enhanced fat/water imaging with high temporal resolution is demonstrated in the abdomen and breast.

CONCLUSION

The described framework provides a viable approach for motion-robust fat/water separation and promises particular value for clinical applications that are currently limited by the breath-holding capacity or cooperation of patients. Magn Reson Med 78:565-576, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

CONVEX CLUSTERING AND RECOVERY OF PARTIALLY OBSERVED DATA

We propose a convex clustering and reconstruction algorithm for data with missing entries. The algorithm uses a similarity measure between every pair of points to cluster and recover the data. The cluster centres can be recovered reliably when the ground-truth similarity matrix is available. Moreover, the similarity matrix can also be reliably estimated from the partially observed data, when the clusters are well-separated and the coherence of the difference between points from different clusters is low. The algorithm performs well using the estimated similarity matrix on a simulated dataset. The method is also successful in reconstructing images from under-sampled Fourier data.

Self-gated 4D multiphase, steady-state imaging with contrast enhancement (MUSIC) using rotating cartesian K-space (ROCK): Validation in children with congenital heart disease

PURPOSE

To develop and validate a cardiac-respiratory self-gating strategy for the recently proposed multiphase steady-state imaging with contrast enhancement (MUSIC) technique.

METHODS

The proposed SG strategy uses the ROtating Cartesian K-space (ROCK) sampling, which allows for retrospective k-space binning based on motion surrogates derived from k-space center line. The k-space bins are reconstructed using a compressed sensing algorithm. Ten pediatric patients underwent cardiac MRI for clinical reasons. The original MUSIC and 2D-CINE images were acquired as a part of the clinical protocol, followed by the ROCK-MUSIC acquisition, all under steady-state intravascular distribution of ferumoxytol. Subjective scores and image sharpness were used to compare the images of ROCK-MUSIC and original MUSIC.

RESULTS

All scans were completed successfully without complications. The ROCK-MUSIC acquisition took 5 ± 1 min, compared to 8 ± 2 min for the original MUSIC. Image scores of ROCK-MUSIC were significantly better than original MUSIC at the ventricular outflow tracts (3.9 ± 0.3 vs. 3.3 ± 0.6, P < 0.05). There was a strong trend toward superior image scores for ROCK-MUSIC in the other anatomic locations.

CONCLUSION

ROCK-MUSIC provided images of equal or superior image quality compared to original MUSIC, and this was achievable with 40% savings in scan time and without the need for physiologic signal. Magn Reson Med 78:472-483, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

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.

Accelerated MRI for the assessment of cardiac function

Heart disease is a worldwide public health problem; assessment of cardiac function is an important part of the diagnosis and management of heart disease. MRI of the heart can provide clinically useful information on cardiac function, although it is still not routinely used in clinical practice, in part because of limited imaging speed. New accelerated methods for performing cardiovascular MRI (CMR) have the potential to provide both increased imaging speed and robustness to CMR, as well as access to increased functional information. In this review, we will briefly discuss the main methods currently employed to accelerate CMR methods, such as parallel imaging, k-t undersampling and compressed sensing, as well as new approaches that extend the idea of compressed sensing and exploit sparsity to provide richer information of potential use in clinical practice.

Dynamic MRI Using SmooThness Regularization on Manifolds (SToRM)

We introduce a novel algorithm to recover real time dynamic MR images from highly under-sampled k- t space measurements. The proposed scheme models the images in the dynamic dataset as points on a smooth, low dimensional manifold in high dimensional space. We propose to exploit the non-linear and non-local redundancies in the dataset by posing its recovery as a manifold smoothness regularized optimization problem. A navigator acquisition scheme is used to determine the structure of the manifold, or equivalently the associated graph Laplacian matrix. The estimated Laplacian matrix is used to recover the dataset from undersampled measurements. The utility of the proposed scheme is demonstrated by comparisons with state of the art methods in multi-slice real-time cardiac and speech imaging applications.

Four-dimensional respiratory motion-resolved whole heart coronary MR angiography

PURPOSE

Free-breathing whole-heart coronary MR angiography (MRA) commonly uses navigators to gate respiratory motion, resulting in lengthy and unpredictable acquisition times. Conversely, self-navigation has 100% scan efficiency, but requires motion correction over a broad range of respiratory displacements, which may introduce image artifacts. We propose replacing navigators and self-navigation with a respiratory motion-resolved reconstruction approach.

METHODS

Using a respiratory signal extracted directly from the imaging data, individual signal-readouts are binned according to their respiratory states. The resultant series of undersampled images are reconstructed using an extradimensional golden-angle radial sparse parallel imaging (XD-GRASP) algorithm, which exploits sparsity along the respiratory dimension. Whole-heart coronary MRA was performed in 11 volunteers and four patients with the proposed methodology. Image quality was compared with that obtained with one-dimensional respiratory self-navigation.

RESULTS

Respiratory-resolved reconstruction effectively suppressed respiratory motion artifacts. The quality score for XD-GRASP reconstructions was greater than or equal to self-navigation in 80/88 coronary segments, reaching diagnostic quality in 61/88 segments versus 41/88. Coronary sharpness and length were always superior for the respiratory-resolved datasets, reaching statistical significance (P < 0.05) in most cases.

CONCLUSION

XD-GRASP represents an attractive alternative for handling respiratory motion in free-breathing whole heart MRI and provides an effective alternative to self-navigation. Magn Reson Med 77:1473-1484, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Joint Reconstruction of Multiple Images and Motion in MRI: Application to Free-Breathing Myocardial T₂Quantification

Exploiting redundancies between multiple images of an MRI examination can be formalized as the joint reconstruction of these images. The anatomy is preserved indeed so that specific constraints can be implemented (e.g. most of the features or spatial gradients should be in the same place in all these images) and only the contrast changes from one image to another need to be encoded. The application of this concept is particularly challenging in cardiovascular and body imaging due to the complex organ deformations, especially with the patient breathing. In this study a joint optimization framework is proposed for reconstructing multiple MR images together with a nonrigid motion model. The motion model takes into account both intra-image and inter-image motion and therefore can correct for most ghosting/blurring artifacts and misregistration between images. The framework was validated with free-breathing myocardial T2 mapping experiments from nine heart transplant patients at 1.5 T. Results showed improved image quality and excellent image alignment with the multi-image reconstruction compared to the independent reconstruction of each image. Segment-wise myocardial T2 values were in good agreement with the reference values obtained from multiple breath-holds (62.5 ± 11.1 ms against 62.2 ± 11.2 ms which was not significant with p=0.49).

Robust self-navigated body MRI using dense coil arrays

PURPOSE

To develop a robust motion estimation method for free-breathing body MRI using dense coil arrays.

METHODS

Self-navigating pulse sequences can measure subject motion without using external motion monitoring devices. With dense coil arrays, individual coil elements can provide localized motion estimates. An averaged motion estimate over all coils is often used for motion compensation. However, this motion estimate may not accurately represent the dominant motion within the imaging volume. In this work, a coil clustering method is proposed to automatically determine the dominant motion for dense coil arrays. The feasibility of the proposed method is investigated in free-breathing abdominal MRI and cardiac MRI, and compared with manual motion estimate selection for respiratory motion estimation and electrocardiography for cardiac motion estimation.

RESULTS

Automated motion estimation achieved similar respiratory motion estimation compared to manual selection (averaged correlation coefficient 0.989 and 0.988 for abdominal MRI and cardiac MRI, respectively), and accurate cardiac triggering compared to electrocardiography (averaged temporal variability 17.5 ms).

CONCLUSION

The proposed method can provide accurate automated motion estimation for body MRI using dense coil arrays. It can enable self-navigated free-breathing abdominal and cardiac MRI without the need for external motion monitoring devices. Magn Reson Med 76:197-205, 2016. © 2015 Wiley Periodicals, Inc.