Free-Breathing and Ungated Dynamic MRI Using Navigator-Less Spiral SToRM.
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ABSTRACT:
SUBMITTER: Ahmed AH
PROVIDER: S-EPMC7806246 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We introduce a local manifold regularization approach to recover dynamic MRI data from highly undersampled measurements. The proposed scheme relies on the manifold structure of local image patches at the same spatial location in a free-breathing cardiac MRI dataset; this approach is a generalization of the SmooThness Regularization on Manifolds (SToRM) scheme that exploits the global manifold structure of images in the dataset. Since the manifold structure of the patches varies depending on the spatial location and is often considerably simpler than the global one, this approach significantly reduces the data demand, facilitating the recovery from shorter scans. Since the navigator-based estimation of manifold structure pursued in SToRM is not feasible in this setting, a reformulation of SToRM is introduced. Specifically, the regularization term of the cost function involves the sum of robust distances between images sub-patches in the dataset. The optimization algorithm alternates between updating the images and estimating the manifold structure of the image patches. The utility of the proposed scheme is demonstrated in the context of in-vivo prospective free-breathing cardiac CINE MRI imaging with multichannel acquisitions and simulated phantoms. The new framework facilitates a reduction in scan time, as compared to the SToRM strategy.
| S-EPMC7893810 | biostudies-literature
Project description:PurposeTo achieve motion robust high resolution 3D free-breathing pulmonary MRI utilizing a novel dynamic 3D image navigator derived directly from imaging data.MethodsFive-minute free-breathing scans were acquired with a 3D ultrashort echo time (UTE) sequence with 1.25 mm isotropic resolution. From this data, dynamic 3D self-navigating images were reconstructed under locally low rank (LLR) constraints and used for motion compensation with one of two methods: a soft-gating technique to penalize the respiratory motion induced data inconsistency, and a respiratory motion-resolved technique to provide images of all respiratory motion states.ResultsRespiratory motion estimation derived from the proposed dynamic 3D self-navigator of 7.5 mm isotropic reconstruction resolution and a temporal resolution of 300 ms was successful for estimating complex respiratory motion patterns. This estimation improved image quality compared to respiratory belt and DC-based navigators. Respiratory motion compensation with soft-gating and respiratory motion-resolved techniques provided good image quality from highly undersampled data in volunteers and clinical patients.ConclusionAn optimized 3D UTE sequence combined with the proposed reconstruction methods can provide high-resolution motion robust pulmonary MRI. Feasibility was shown in patients who had irregular breathing patterns in which our approach could depict clinically relevant pulmonary pathologies. Magn Reson Med 79:2954-2967, 2018. © 2017 International Society for Magnetic Resonance in Medicine.
| S-EPMC6474413 | biostudies-literature
Project description:A navigator-gated 3D spiral cine displacement encoding with stimulated echoes (DENSE) pulse sequence for imaging 3D myocardial mechanics was developed. In addition, previously described 2D postprocessing algorithms including phase unwrapping, tissue tracking, and strain tensor calculation for the left ventricle (LV) were extended to 3D. These 3D methods were evaluated in five healthy volunteers, using 2D cine DENSE and historical 3D myocardial tagging as reference standards. With an average scan time of 20.5 ± 5.7 min, 3D data sets with a matrix size of 128 × 128 × 22, voxel size of 2.8 × 2.8 × 5.0 mm(3), and temporal resolution of 32 msec were obtained with displacement encoding in three orthogonal directions. Mean values for end-systolic mid-ventricular mid-wall radial, circumferential, and longitudinal strain were 0.33 ± 0.10, -0.17 ± 0.02, and -0.16 ± 0.02, respectively. Transmural strain gradients were detected in the radial and circumferential directions, reflecting high spatial resolution. Good agreement by linear correlation and Bland-Altman analysis was achieved when comparing normal strains measured by 2D and 3D cine DENSE. Also, the 3D strains, twist, and torsion results obtained by 3D cine DENSE were in good agreement with historical values measured by 3D myocardial tagging.
| S-EPMC2946451 | biostudies-literature
Project description:PurposeTo introduce a novel framework to combine deep-learned priors along with complementary image regularization penalties to reconstruct free breathing & ungated cardiac MRI data from highly undersampled multi-channel measurements.MethodsImage recovery is formulated as an optimization problem, where the cost function is the sum of data consistency term, convolutional neural network (CNN) denoising prior, and SmooThness regularization on manifolds (SToRM) prior that exploits the manifold structure of images in the dataset. An iterative algorithm, which alternates between denoizing of the image data using CNN and SToRM, and conjugate gradients (CG) step that minimizes the data consistency cost is introduced. Unrolling the iterative algorithm yields a deep network, which is trained using exemplar data.ResultsThe experimental results demonstrate that the proposed framework can offer fast recovery of free breathing and ungated cardiac MRI data from less than 8.2s of acquisition time per slice. The reconstructions are comparable in image quality to SToRM reconstructions from 42s of acquisition time, offering a fivefold reduction in scan time.ConclusionsThe results show the benefit in combining deep learned CNN priors with complementary image regularization penalties. Specifically, this work demonstrates the benefit in combining the CNN prior that exploits local and population generalizable redundancies together with SToRM, which capitalizes on patient-specific information including cardiac and respiratory patterns. The synergistic combination is facilitated by the proposed framework.
| S-EPMC7895318 | biostudies-literature
Project description:PurposeTo develop a whole-heart, free-breathing, non-electrocardiograph (ECG)-gated, cardiac-phase-resolved myocardial perfusion MRI framework (CRIMP; Continuous Radial Interleaved simultaneous Multi-slice acquisitions at sPoiled steady-state) and test its quantification feasibility.MethodsCRIMP used interleaved radial simultaneous multi-slice (SMS) slice groups to cover the whole heart in 9 or 12 short-axis slices. The sequence continuously acquired data without magnetization preparation, ECG gating or breath-holding, and captured multiple cardiac phases. Images were reconstructed by a motion-compensated patch-based locally low-rank reconstruction. Bloch simulations were performed to study the signal-to-noise ratio/contrast-to-noise ratio (SNR/CNR) for CRIMP and to study the steady-state signal under motion. Seven patients were scanned with CRIMP at stress and rest to develop the sequence. One human and two dogs were scanned at rest with a dual-bolus method to test the quantification feasibility of CRIMP. The dual-bolus scans were performed using both CRIMP and an ungated radial SMS saturation recovery (SMS-SR) sequence with injection dose = 0.075 mmol/kg to compare the sequences in terms of SNR, cardiac phase resolution and quantitative myocardial blood flow (MBF).ResultsPerfusion images with multiple cardiac phases in all image slices with a temporal resolution of 72 ms/frame were obtained. Simulations and in-vivo acquisitions showed CRIMP kept the inner slices in steady-state regardless of motion. CRIMP outperformed SMS-SR in slice coverage (9 over 6), SNR (mean 20% improvement), and provided cardiac phase resolution. CRIMP and SMS-SR sequences provided comparable MBF values (rest systolic CRIMP = 0.58 ± 0.07, SMS-SR = 0.61 ± 0.16).ConclusionCRIMP allows for whole-heart, cardiac-phase-resolved myocardial perfusion images without ECG-gating or breath-holding. The sequence can provide MBF if an accurate arterial input function is obtained separately.
| S-EPMC7710603 | biostudies-literature
Project description:To develop and optimize a rapid dynamic hyperpolarized 129 Xe ventilation (DXeV) MRI protocol and investigate the feasibility of capturing pulmonary signal-time curves in human lungs.Spiral k-space trajectories were designed with the number of interleaves Nint ?=?1, 2, 4, and 8 corresponding to voxel sizes of 8?mm, 5?mm, 4?mm, and 2.5?mm, respectively, for field of view?=?15?cm. DXeV images were acquired from a gas-flow phantom to investigate the ability of Nint ?=?1, 2, 4, and 8 to capture signal-time curves. A finite element model was constructed to investigate gas-flow dynamics corroborating the experimental signal-time curves. DXeV images were also carried out in six subjects (three healthy and three chronic obstructive pulmonary disease subjects).DXeV images and numerical modelling of signal-time curves permitted the quantification of temporal and spatial resolutions for different numbers of spiral interleaves. The two-interleaved spiral (Nint ?=?2) was found to be the most time-efficient to obtain DXeV images and signal-time curves of whole lungs with a temporal resolution of 624 ms for 13 slices. Signal-time curves were well matched in three healthy volunteers. The Spearman's correlations of chronic obstructive pulmonary disease subjects were statistically different from three healthy subjects (P?<?0.05).The Nint ?=?2 spiral demonstrates the successful acquisition of DXeV images and signal-time curves in healthy subjects and chronic obstructive pulmonary disease patients. Magn Reson Med 79:2597-2606, 2018. © 2017 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.
| S-EPMC5836876 | biostudies-other
Project description:BACKGROUND:Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been shown to be a promising technique for assessing lung lesions. However, DCE-MRI often suffers from motion artifacts and insufficient imaging speed. Therefore, highly accelerated free-breathing DCE-MRI is of clinical interest for lung exams. PURPOSE:To test the performance of rapid free-breathing DCE-MRI for simultaneous qualitative and quantitative assessment of pulmonary lesions using Golden-angle RAdial Sparse Parallel (GRASP) imaging. STUDY TYPE:Prospective. POPULATION:Twenty-six patients (17 males, mean age?=?55.1?±?14.4) with known pulmonary lesions. FIELD STRENGTH/SEQUENCE:3T MR scanner; a prototype fat-saturated, T1 -weighted stack-of-stars golden-angle radial sequence for data acquisition and a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence for comparison. ASSESSMENT:After a dual-mode GRASP reconstruction, one with 3-second temporal resolution (3s-GRASP) and the other with 15-second temporal resolution (15s-GRASP), all GRASP and BH-VIBE images were pooled together for blind assessment by two experienced radiologists, who independently scored the overall image quality, lesion delineation, overall artifact level, and diagnostic confidence of each case. Perfusion analysis was performed for the 3s-GRASP images using a Tofts model to generate the volume transfer coefficient (Ktrans ) and interstitial volume (Ve ). STATISTICAL TESTS:Nonparametric paired two-tailed Wilcoxon signed-rank test; Cohen's kappa; unpaired Student's t-test. RESULTS:15s-GRASP achieved comparable image quality with conventional BH-VIBE (P?>?0.05), except for the higher overall artifact level in the precontrast phase (P?=?0.018). The Ktrans and Ve in inflammation were higher than those in malignant lesions (Ktrans : 0.78?±?0.52?min-1 vs. 0.37?±?0.22?min-1 , P?=?0.020; Ve : 0.36?±?0.16 vs. 0.26?±?0.1, P?=?0.177). Also, the Ktrans and Ve in malignant lesions were also higher than those in benign lesions (Ktrans : 0.37?±?0.22?min-1 vs. 0.04?±?0.04?min-1 , P?=?0.001; Ve : 0.26?±?0.12 vs. 0.10?±?0.00, P?=?0.063). DATA CONCLUSION:This feasibility study demonstrated the performance of high spatiotemporal resolution free-breathing DCE-MRI of the lung using GRASP for qualitative and quantitative assessment of pulmonary lesions. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:459-468.
| S-EPMC6089682 | biostudies-literature
Project description:To develop a method for fast pediatric 3D free-breathing abdominal dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) and investigate its clinical feasibility.A combined locally low rank parallel imaging method with soft gating is proposed for free-breathing DCE MRI acquisition. With Institutional Review Board (IRB) approval and informed consent/assent, 23 consecutive pediatric patients were recruited for this study. Free-breathing DCE MRI with ?1 mm(3) spatial resolution and a 6.5-sec frame rate was acquired on a 3T scanner. Undersampled data were reconstructed with a compressed sensing method without motion correction (FB-CS) and the proposed method (FB-LR). A follow-up respiratory-triggered acquisition (RT-CS) was performed as a reference standard. The reconstructed images were evaluated independently by two radiologists. Wilcoxon tests were performed to test the hypothesis that there was no significant difference between different reconstructions. Quantitative evaluation of contrast dynamics was also performed.The mean score of overall image quality of FB-LR was 4.0 on a 5-point scale, significantly better (P < 0.05) than FB-CS reconstruction (mean score 2.9), and similar to RT-CS (mean score 4.1). FB-LR also matched the temporal fidelity of contrast dynamics with a root mean square error less than 5%.Fast 3D free-breathing DCE MRI with high scan efficiency and image quality similar to respiratory-triggered acquisition is feasible in a pediatric clinical setting.
| S-EPMC4065644 | biostudies-literature
Project description:ObjectivesTo visualize and quantitatively assess regional lung function of survivors of COVID-19 who were hospitalized using pulmonary free-breathing 1H MRI.MethodsA total of 12 healthy volunteers and 27 COVID-19 survivors (62.4 ± 8.1 days between infection and image acquisition) were recruited in this prospective study and performed chest 1H MRI acquisitions with free tidal breathing. Then, conventional Fourier decomposition ventilation (FD-V) and global fractional ventilation (FVGlobal) were analyzed. Besides, a modified PREFUL (mPREFUL) method was developed to adapt to COVID-19 survivors and generate dynamic ventilation maps and parameters. All the ventilation maps and parameters were analyzed using Student's t-test. Pearson's correlation and a Bland-Altman plot between FVGlobal and mPREFUL were analyzed.ResultsThere was no significant difference between COVID-19 and healthy groups regarding a static FD-V map (0.47 ± 0.12 vs 0.42 ± 0.08; p = .233). However, mPREFUL demonstrated lots of regional high ventilation areas (high ventilation percentage (HVP): 23.7% ± 10.6%) existed in survivors. This regional heterogeneity (i.e., HVP) in survivors was significantly higher than in healthy volunteers (p = .003). The survivors breathed deeper (flow-volume loop: 5375 ± 3978 vs 1688 ± 789; p = .005), and breathed more air in respiratory cycle (total amount: 62.6 ± 19.3 vs 37.3 ± 9.9; p < .001). Besides, mPREFUL showed both good Pearson's correlation (r = 0.74; p < .001) and Bland-Altman consistency (mean bias = -0.01) with FVGlobal.ConclusionsDynamic ventilation imaging using pulmonary free-breathing 1H MRI found regional abnormity of dynamic ventilation function in COVID-19 survivors.Key points• Pulmonary free-breathing1H MRI was used to visualize and quantitatively assess regional lung ventilation function of COVID-19 survivors. • Dynamic ventilation maps generated from 1H MRI were more sensitive to distinguish the COVID-19 and healthy groups (total air amount: 62.6 ± 19.3 vs 37.3 ± 9.9; p < .001), compared with static ventilation maps (FD-V value: 0.47 ± 0.12 vs 0.42 ± 0.08; p = .233). • COVID-19 survivors had larger regional heterogeneity (high ventilation percentage: 23.7% ± 10.6% vs 13.1% ± 7.9%; p = .003), and breathed deeper (flow-volume loop: 5375 ± 3978 vs 1688 ± 789; p = .005) than healthy volunteers.
| S-EPMC8858033 | biostudies-literature
Project description:The clinical utility of myocardial perfusion MR imaging (MPI) is often restricted by the inability of current acquisition schemes to simultaneously achieve high spatio-temporal resolution, good volume coverage, and high signal to noise ratio. Moreover, many subjects often find it difficult to hold their breath for sufficiently long durations making it difficult to obtain reliable MPI data. Accelerated acquisition of free breathing MPI data can overcome some of these challenges. Recently, an algorithm termed as k - t SLR has been proposed to accelerate dynamic MRI by exploiting sparsity and low rank properties of dynamic MRI data. The main focus of this paper is to further improve k - t SLR and demonstrate its utility in considerably accelerating free breathing MPI. We extend its previous implementation to account for multi-coil radial MPI acquisitions. We perform k - t sampling experiments to compare different radial trajectories and determine the best sampling pattern. We also introduce a novel augmented Lagrangian framework to considerably improve the algorithm's convergence rate. The proposed algorithm is validated using free breathing rest and stress radial perfusion data sets from two normal subjects and one patient with ischemia. k - t SLR was observed to provide faithful reconstructions at high acceleration levels with minimal artifacts compared to existing MPI acceleration schemes such as spatio-temporal constrained reconstruction and k - t SPARSE/SENSE.
| S-EPMC3902973 | biostudies-literature