Background The application of cardiovascular magnetic resonance angiography (CMRA) for the assessment of thoracic aortic disease is often associated with prolonged and unpredictable acquisition times and residual motion artefacts. To overcome these limitations, we have integrated undersampled acquisition with image-based navigators and inline non-rigid motion correction to enable a free-breathing, contrast-free Cartesian CMRA framework for the visualization of the thoracic aorta in a short and predictable scan of 3 min. Methods 35 patients with thoracic aortic disease (36 ± 13y, 14 female) were prospectively enrolled in this single-center study. The proposed 3D T2-prepared balanced steady state free precession (bSSFP) sequence with image-based navigator (iNAV) was compared to the clinical 3D T2-prepared bSSFP with diaphragmatic-navigator gating (dNAV), in terms of image acquisition time. Three cardiologists blinded to iNAV vs. dNAV acquisition, recorded image quality scores across four aortic segments and their overall diagnostic confidence. Contrast ratio (CR) and relative standard deviation (RSD) of signal intensity (SI) in the corresponding segments were estimated. Co-axial aortic dimensions in six landmarks were measured by two readers to evaluate the agreement between the two methods, along with inter-observer and intra-observer agreement. Kolmogorov–Smirnov test, Mann–Whitney U (MWU), Bland–Altman analysis (BAA), intraclass correlation coefficient (ICC) were used for statistical analysis. Results The scan time for the iNAV-based approach was significantly shorter (3.1 ± 0.5 min vs. 12.0 ± 3.0 min for dNAV, P = 0.005). Reconstruction was performed inline in 3.0 ± 0.3 min. Diagnostic confidence was similar for the proposed iNAV versus dNAV for all three reviewers (Reviewer 1: 3.9 ± 0.3 vs. 3.8 ± 0.4, P = 0.7; Reviewer 2: 4.0 ± 0.2 vs. 3.9 ± 0.3, P = 0.4; Reviewer 3: 3.8 ± 0.4 vs. 3.7 ± 0.6, P = 0.3). The proposed method yielded higher image quality scores in terms of artefacts from respiratory motion, and non-diagnostic images due to signal inhomogeneity were observed less frequently. While the dNAV approach outperformed the iNAV method in the CR assessment, the iNAV sequence showed improved signal homogeneity along the entire thoracic aorta [RSD SI 5.1 (4.4, 6.5) vs. 6.5 (4.6, 8.6), P = 0.002]. BAA showed a mean difference of < 0.05 cm across the 6 landmarks between the two datasets. ICC showed excellent inter- and intra-observer reproducibility. Conclusions Thoracic aortic iNAV-based CMRA with fast acquisition (~ 3 min) and inline reconstruction (3 min) is proposed, resulting in high diagnostic confidence and reproducible aortic measurements.
The aim of the current study was to develop a novel approach for 2D breath‐hold cardiac cine imaging from a single heartbeat, by combining cardiac motion‐corrected reconstructions and nonrigidly aligned patch‐based regularization. Conventional cardiac cine imaging is obtained via motion‐resolved reconstructions of data acquired over multiple heartbeats. Here, we achieve single‐heartbeat cine imaging by incorporating nonrigid cardiac motion correction into the reconstruction of each cardiac phase, in conjunction with a motion‐aligned patch‐based regularization. The proposed Motion‐Corrected CINE (MC‐CINE) incorporates all acquired data into the reconstruction of each (motion‐corrected) cardiac phase, resulting in a better posed problem than motion‐resolved approaches. MC‐CINE was compared with iterative sensitivity encoding (itSENSE) and Extra‐Dimensional Golden Angle Radial Sparse Parallel (XD‐GRASP) in 14 healthy subjects in terms of image sharpness, reader scoring (range: 1–5) and reader ranking (range: 1–9) of image quality, and single‐slice left ventricular assessment. MC‐CINE was significantly superior to both itSENSE and XD‐GRASP using 20 heartbeats, two heartbeats, and one heartbeat. Iterative SENSE, XD‐GRASP, and MC‐CINE achieved a sharpness of 74%, 74%, and 82% using 20 heartbeats, and 53%, 66%, and 82% with one heartbeat, respectively. The corresponding results for reader scoring were 4.0, 4.7, and 4.9 with 20 heartbeats, and 1.1, 3.0, and 3.9 with one heartbeat. The corresponding results for reader ranking were 5.3, 7.3, and 8.6 with 20 heartbeats, and 1.0, 3.2, and 5.4 with one heartbeat. MC‐CINE using a single heartbeat presented nonsignificant differences in image quality to itSENSE with 20 heartbeats. MC‐CINE and XD‐GRASP at one heartbeat both presented a nonsignificant negative bias of less than 2% in ejection fraction relative to the reference itSENSE. It was concluded that the proposed MC‐CINE significantly improves image quality relative to itSENSE and XD‐GRASP, enabling 2D cine from a single heartbeat.
BackgroundBright‐blood lumen and black‐blood vessel wall imaging are required for the comprehensive assessment of aortic disease. These images are usually acquired separately, resulting in long examinations and potential misregistration between images.PurposeTo characterize the performance of an accelerated and respiratory motion‐compensated three‐dimensional (3D) cardiac MRI technique for simultaneous contrast‐free aortic lumen and vessel wall imaging with an interleaved T2 and inversion recovery prepared sequence (iT2Prep‐BOOST).Study TypeProspective.PopulationA total of 30 consecutive patients with aortopathy referred for a clinically indicated cardiac MRI examination (9 females, mean age ± standard deviation: 32 ± 12 years).Field Strength/Sequence1.5‐T; bright‐blood MR angiography (diaphragmatic navigator‐gated T2‐prepared 3D balanced steady‐state free precession [bSSFP], T2Prep‐bSSFP), breath‐held black‐blood two‐dimensional (2D) half acquisition single‐shot turbo spin echo (HASTE), and 3D bSSFP iT2Prep‐BOOST.AssessmentiT2Prep‐BOOST bright‐blood images were compared to T2prep‐bSSFP images in terms of aortic vessel dimensions, lumen‐to‐myocardium contrast ratio (CR), and image quality (diagnostic confidence, vessel sharpness and presence of artifacts, assessed by three cardiologists on a 4‐point scale, 1: nondiagnostic to 4: excellent). The iT2Prep‐BOOST black‐blood images were compared to 2D HASTE images for quantification of wall thickness. A visual comparison between computed tomography (CT) and iT2Prep‐BOOST was performed in a patient with chronic aortic dissection.Statistical TestsPaired t‐tests, Wilcoxon signed‐rank tests, intraclass correlation coefficient (ICC), Bland–Altman analysis. A P value < 0.05 was considered statistically significant.ResultsBright‐blood iT2Prep‐BOOST resulted in significantly improved image quality (mean ± standard deviation 3.8 ± 0.5 vs. 3.3 ± 0.8) and CR (2.9 ± 0.8 vs. 1.8 ± 0.5) compared with T2Prep‐bSSFP, with a shorter scan time (7.8 ± 1.7 minutes vs. 12.9 ± 3.4 minutes) while providing a complementary 3D black‐blood image. Aortic lumen diameter and vessel wall thickness measurements in bright‐blood and black‐blood images were in good agreement with T2Prep‐bSSFP and HASTE images (<0.02 cm and <0.005 cm bias, respectively) and good intrareader (ICC > 0.96) and interreader (ICC > 0.94) agreement was observed for all measurements.Data ConclusioniT2Prep‐BOOST might enable time‐efficient simultaneous bright‐ and black‐blood aortic imaging, with improved image quality compared to T2Prep‐bSSFP and HASTE imaging, and comparable measurements for aortic wall and lumen dimensions.Evidence Level2.Technical EfficacyStage 2.
Develop a novel approach for accelerated 2D free-breathing myocardial perfusion via low-rank motion-corrected (LRMC) reconstructions.Methods: Myocardial perfusion imaging requires high spatial and temporal resolution, despite scan time constraints. Here, we incorporate LRMC models into the reconstruction-encoding operator, together with high-dimensionality patch-based regularization, to produce high quality, motion-corrected myocardial perfusion series from free-breathing acquisitions. The proposed framework estimates beat-to-beat nonrigid respiratory (and any other incidental) motion and the dynamic contrast subspace from the actual acquired data, which are then incorporated into the proposed LRMC reconstruction. LRMC was compared with iterative SENSitivity Encoding (SENSE) (itSENSE) and low-rank plus sparse (LpS) reconstruction in 10 patients based on image-quality scoring and ranking by two clinical expert readers.Results: LRMC achieved significantly improved results relative to itSENSE and LpS in terms of image sharpness, temporal coefficient of variation, and expert reader evaluation. Left ventricle image sharpness was approximately 75%, 79%, and 86% for itSENSE, LpS and LRMC, respectively, indicating improved image sharpness for the proposed approach. Corresponding temporal coefficient of variation results were 23%, 11% and 7%, demonstrating improved temporal fidelity of the perfusion signal with the proposed LRMC. Corresponding clinical expert reader scores (1-5, from poor to excellent image quality) were 3.3, 3.9 and 4.9, demonstrating improved image quality with the proposed LRMC, in agreement with the automated metrics. Conclusion:LRMC produces motion-corrected myocardial perfusion in free-breathing acquisitions with substantially improved image quality when compared with iterative SENSE and LpS reconstructions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.