Faculty Bibliography

PURPOSE: Golden-angle radial sparse parallel (GRASP) MRI reconstruction requires gridding and regridding to transform data between radial and Cartesian k-space. These operations are repeatedly performed in each iteration, which makes the reconstruction computationally demanding. This work aimed to accelerate GRASP reconstruction using self-calibrating GRAPPA operator gridding (GROG) and to validate its performance in clinical imaging. METHODS: GROG is an alternative gridding approach based on parallel imaging, in which k-space data acquired on a non-Cartesian grid are shifted onto a Cartesian k-space grid using information from multicoil arrays. For iterative non-Cartesian image reconstruction, GROG is performed only once as a preprocessing step. Therefore, the subsequent iterative reconstruction can be performed directly in Cartesian space, which significantly reduces computational burden. Here, a framework combining GROG with GRASP (GROG-GRASP) is first optimized and then compared with standard GRASP reconstruction in 22 prostate patients. RESULTS: GROG-GRASP achieved approximately 4.2-fold reduction in reconstruction time compared with GRASP ( approximately 333 min versus approximately 78 min) while maintaining image quality (structural similarity index approximately 0.97 and root mean square error approximately 0.007). Visual image quality assessment by two experienced radiologists did not show significant differences between the two reconstruction schemes. With a graphics processing unit implementation, image reconstruction time can be further reduced to approximately 14 min. CONCLUSION: The GRASP reconstruction can be substantially accelerated using GROG. This framework is promising toward broader clinical application of GRASP and other iterative non-Cartesian reconstruction methods. Magn Reson Med, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.

OBJECTIVES: Residual respiratory motion degrades image quality in conventional cardiac cine MRI (CCMRI). We evaluated whether a free-breathing (FB) radial imaging CCMRI sequence with compressed sensing reconstruction [extradimensional (e.g. cardiac and respiratory phases) golden-angle radial sparse parallel, or XD-GRASP] could provide better image quality than a conventional Cartesian breath-held (BH) sequence in an unselected population of patients undergoing clinical CCMRI. MATERIALS AND METHODS: One hundred one patients who underwent BH and FB imaging in a midventricular short-axis plane at a matching location were included. Visual and quantitative image analysis was performed by two blinded experienced readers, using a five-point qualitative scale to score overall image quality and visual signal-to-noise ratio (SNR) grade, with measures of noise and sharpness. End-diastolic and end-systolic left ventricular areas were also measured and compared for both BH and FB images. RESULTS: Image quality was generally better with the BH cines (overall quality grade for BH vs FB images 4 vs 2.9, p < 0.001; noise 0.06 vs 0.08 p < 0.001; SNR grade 4.1 vs 3, p < 0.001), except for sharpness (p = 0.48). There were no significant differences between BH and FB images regarding end-diastolic or end-systolic areas (p = 0.35 and p = 0.12). Eighteen of the 101 patients had poor BH image quality (grade 1 or 2). In this subgroup, the quality of the FB images was better (p = 0.0032), as was the SNR grade (p = 0.003), but there were no significant differences regarding noise and sharpness (p = 0.45 and p = 0.47). CONCLUSION: Although FB XD-GRASP CCMRI was visually inferior to conventional BH CCMRI in general, it provided improved image quality in the subgroup of patients with respiratory-motion-induced artifacts on BH images.

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, 2017. (c) 2017 International Society for Magnetic Resonance in Medicine.

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.

OBJECTIVE:This work presents a highly-accelerated, self-gated, free-breathing 3D cardiac cine MRI method for cardiac function assessment. MATERIALS AND METHODS/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/CONCLUSIONS: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.

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 2016.

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, 2016. (c) 2016 International Society for Magnetic Resonance in Medicine.

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, 2016. (c) 2016 Wiley Periodicals, Inc.

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 (Poincare 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, 5x10-9, 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.

Background: Conventional cine MRI provides data on the variation of cardiac dimensions across the cardiac cycle; cardiac function analysis primarily focuses on the difference between end-diastolic (ED) and endsystolic (ES) dimensions of the left and right ventricles (LV and RV). With cardiorespiratory-synchronized (CRS) CMR, there is an additional effective dimension of information available, related to the effect of the respiratory cycle phase on cardiac dimensions. However, there are currently no established ways to analyze this potentially useful additional physiological data. We have developed a set of tools for the functional analysis of CRS CMR, particularly for the study of the respiratory effects on LV-RV interaction, and derived some initial normative values for the results. Methods: We have developed a set of interactive CMR function analysis programs. Images from CRS CMR are organized in a two-dimensional matrix, sorted by cardiac and respiratory cycle phases. The user can interactively position an analysis line across the ventricles in a representative image; this line can then be automatically tracked across the other cardiac and respiratory phases. The intensity profile along the line is then used to automatically track the corresponding positions of the edges of the LV and RV free walls and the interventricular septum (IVS). A variety of absolute and normalized variables can be derived from these varying positions, including ED and ES dimensions, and displayed as functional images over the cardiac and respiratory cycle dimensions. CRS CMR was performed with a sparsity-based method (XD-GRASP), using continuous acquisition of radial k-space samples with golden-angle increments and retrospective cardiac and respiratory phase sorting in reconstruction. An initial set of CRS CMR data from 9 normal subjects (age 28.33 +/- 5.85) was analyzed, as well as from 3 patients (age 40 +/- 9.66, one with HCM). Results: On visual inspection of the images, it is apparent that there is a clear shift in the relative position of the IVS over the respiratory cycle, to the left in inspiration and to the right in expiration, reflecting the LV-RV interaction; this is much more prominent near ED than ES. For the normal subjects, in midlevel short-axis views, the respiratory-related absolute shift in IVS position was 1.07-3.23 mm at ED and 0.69-2.14 mm at ES; corresponding values normalized to ED dimension were 2.65-7.08 pp and 1.99-5.18 pp. The ED-ES difference for the normalized shift ranges was -1.9-4.35 pp (median 1.35, first quartile 0.68). For the HCM patient, the difference between the shift ranges was 0.79 pp. Linear regression when plotting NCD against NEDD (reflecting the Frank-Starling relationship and giving an estimate of contractility) was 0.68 +/- 0.11 in the normal subjects. Conclusions: Novel physiologic data on LV-RV interaction can be derived from CRS CMR; this seems to show consistent ranges in normal subjects, and may provide useful information on disease-related changes in cardiac function. (Figure Presented)