Respiratory motion corrected 4D flow using golden radial phase encoding.

PURPOSE: To minimize respiratory motion artifacts while achieving predictable scan times with 100% scan efficiency for thoracic 4D flow MRI. METHODS: A 4D flow sequence with golden radial phase encoding (GRPE) was acquired in 9 healthy volunteers covering the heart, aorta, and venae cavae. Scan time was 15 min, and data were acquired without motion gating during acquisition. Data were retrospectively re-binned into respiratory and cardiac phases based on respiratory self-navigation and the electrocardiograph signals, respectively. Nonrigid respiratory motion fields were extracted and corrected for during the k-t SENSE reconstruction. A respiratory-motion corrected (GRPE-MOCO) and a free-breathing (GRPE-UNCORR) 4D flow dataset was reconstructed using 100% of the acquired data. For comparison, a respiratory gated Cartesian 4D flow acquisition (CART-REF) covering the aorta was acquired. Stroke volumes and peak flows were compared. Additionally, an internal flow validation based on mass conservation was performed on the GRPE-MOCO and GRPE-UNCORR. Statistically significant differences were analyzed using a paired Wilcoxon test. RESULTS: Stroke volumes and peak flows in the aorta between GRPE-MOCO and the CART-REF showed a mean difference of -1.5 ± 10.3 mL (P > 0.05) and 25.2 ± 55.9 mL/s (P > 0.05), respectively. Peak flow in the GRPE-UNCORR data was significantly different compared with CART-REF (P < 0.05). GRPE-MOCO showed higher accuracy for internal consistency analysis than GRPE-UNCORR. CONCLUSION: The proposed 4D flow sequence allows a straight-forward planning by covering the entire thorax and ensures a predictable scan time independent of cardiac cycle variations and breathing patterns.

Accelerated aortic 4D flow cardiovascular magnetic resonance using compressed sensing: applicability, validation and clinical integration.

BACKGROUND: Three-dimensional time-resolved phase-contrast cardiovascular magnetic resonance (4D flow CMR) enables the quantification and visualisation of blood flow, but its clinical applicability remains hampered by its long scan time. The aim of this study was to evaluate the use of compressed sensing (CS) with on-line reconstruction to accelerate the acquisition and reconstruction of 4D flow CMR of the thoracic aorta. METHODS: 4D flow CMR of the thoracic aorta was acquired in 20 healthy subjects using CS with acceleration factors ranging from 4 to 10. As a reference, conventional parallel imaging (SENSE) with acceleration factor 2 was used. Flow curves, net flows, peak flows and peak velocities were extracted from six contours along the aorta. To measure internal data consistency, a quantitative particle trace analysis was performed. Additionally, scan-rescan, inter- and intraobserver reproducibility were assessed. Subsequently, 4D flow CMR with CS factor 6 was acquired in 3 patients with differing aortopathies. The flow patterns resulting from particle trace visualisation were qualitatively analysed. RESULTS: All collected data were successfully acquired and reconstructed on-line. The average acquisition time including respiratory navigator efficiency with CS factor 6 was 5:02 ± 2:23 min while reconstruction took approximately 9 min. For CS factors of 8 or less, mean differences in net flow, peak flow and peak velocity as compared to SENSE were below 2.2 ± 7.8 ml/cycle, 4.6 ± 25.2 ml/s and - 7.9 ± 13.0 cm/s, respectively. For a CS factor of 10 differences reached 5.4 ± 8.0 ml/cycle, 14.4 ± 28.3 ml/s and - 4.0 ± 12.2 cm/s. Scan-rescan analysis yielded mean differences in net flow of - 0.7 ± 4.9 ml/cycle for SENSE and - 0.2 ± 8.5 ml/cycle for CS factor of 6. CONCLUSIONS: A six- to eightfold acceleration of 4D flow CMR using CS is feasible. Up to a CS acceleration rate of 6, no statistically significant differences in measured flow parameters could be observed with respect to the reference technique. Acquisitions in patients with aortopathies confirm the potential to integrate the proposed method in a clinical routine setting, whereby its main benefits are scan-time savings and direct on-line reconstruction.

Respiration Dependency of Caval Blood Flow in Patients with Fontan Circulation: Quantification Using 5D Flow MRI.

PURPOSE: To measure respiration-dependent blood flow in the total cavopulmonary connection (TCPC) of patients with Fontan circulation by using free-running, fully self-gated five-dimensional (5D) flow MRI. MATERIALS AND METHODS: From July to November 2018, 10 volunteers (six female volunteers, mean age, 25.1 years ± 4.4 [standard deviation]) and six patients with Fontan circulation (two female patients, mean age, 19.7 years ± 7.5) with a TCPC were examined by using a cardiac- and respiration-resolved three-directional and three-dimensional phase-contrast MRI sequence (hereafter, 5D flow MRI). This prospective study was conducted with approval of the local ethics committee, and written informed consent was obtained from all participants and/or their representative. 5D flow data were acquired during free breathing. Data were reconstructed into 15-20 heart phases and four respiratory phases: end-expiration, inspiration, end-inspiration, and expiration. Respiration-dependent stroke volumes (SVs) and particle traces were analyzed from the caval circulation of volunteers and patients with Fontan circulation. Statistical analysis was performed by using parametric tests and scatterplots. RESULTS: The respiration dependency of caval blood flow was evaluated in all participants and was significantly elevated in patients with Fontan circulation as compared with volunteers. In patients, SV in the inferior vena cava (IVC) showed variations of 120% between inspiration and expiration (P = .002). The flow distribution in the IVC and superior vena cava among the four respiratory phases was differentiated by 20% (range, 9%-30%) and 4% (range, 0%-13%), respectively. CONCLUSION: Hemodynamic parameters (volume flow and blood flow distribution) throughout the cardiac and respiratory cycle can be measured using a single scan, potentially providing further insights into the Fontan circulation.© RSNA, 2019Supplemental material is available for this article.