Aortic 4D Flow Research Articles

Cluster analysis of 100 Marfan patients based on aortic 4D flow MRI and Z-score: insights into disease heterogeneity and stratification of subgroups.

4D flow MRI-derived variables from Marfan patients are highly heterogeneous. Our aim was to identify distinct Marfan patient subgroups based on aortic 4D flow MRI and Z-score for stratification of distinct hemodynamic profiles and clinical features by means of hierarchical cluster analysis. One hundred Marfan patients underwent baseline aortic 4D flow MRI at 3 T. Z-scores, degree of helical and vortical flow, wall shear stress, flow displacement, and peak velocity were determined in the ascending aorta. Sex, age, BMI, antihypertensive medication, and dural ectasia were recorded. Hierarchical cluster analysis was performed using 4D flow MRI variables and Z-scores as input. Cluster analysis resulted in three distinct clusters characterized by different Z-scores (mean ± SD); cluster 1: 0.4 ± 1.1 vs. cluster 2: 3.1 ± 1.1 vs. cluster 3: 3.6 ± 1.9. The three clusters delivered differences in helical and vortical flow patterns (global p = 0.003 and p < 0.001, respectively), wall shear stress (0.49 ± 0.11 vs. 0.44 ± 0.12 vs. 0.37 ± 0.09 N/m2, global p < 0.001), flow displacement (0.11 ± 0.05 vs. 0.16 ± 0.08 vs. 0.15 ± 0.07, global p = 0.006), and peak velocity (76.3 ± 9.0 vs. 60.1 ± 7.3 vs. 56.0 ± 7.8 cm/s, global p < 0.001). Patients in cluster 1 and 2 were relevantly younger than in cluster 3 (32.3 ± 13.8 vs. 32.8 ± 12.6 vs. 40.2 ± 15.0 years, all pairwise ∆p < 0.0297). Hierarchical cluster analysis based on aortic 4D flow MRI and Z-score revealed three distinct subgroups of Marfan patients, each characterized by specific hemodynamic profiles and clinical features. Follow-up of our patients is warranted to assess if 4D flow MRI- and Z-score-based stratification can predict future aortic diameter growth and ultimately improve outcomes. A combination of Z-score and 4D flow MRI-derived parameters may help identify subgroups of Marfan patients representing different stages or phenotypes of aortic disease, which require specific management strategies. Four-dimensional (4D) flow MRI-derived variables of Marfan patients are highly heterogeneous across varying Z-scores. Cluster analysis based on 4D flow MRI and Z-score revealed three distinct subgroups of Marfan patients. A combination of Z-score and 4D flow MRI-derived parameters may identify different stages of aortic disease in Marfan patients.

Optimizing encoding strategies for 4D Flow MRI of mean and turbulent flow

For 4D Flow MRI of mean and turbulent flow a compromise between spatiotemporal undersampling and velocity encodings needs to be found. Assuming a fixed scan time budget, the impact of trading off spatiotemporal undersampling versus velocity encodings on quantification of velocity and turbulence for aortic 4D Flow MRI was investigated. For this purpose, patient-specific mean and turbulent aortic flow data were generated using computational fluid dynamics which were embedded into the patient-specific background image data to generate synthetic MRI data with corresponding ground truth flow. Cardiac and respiratory motion were included. Using the synthetic MRI data as input, 4D Flow MRI was subsequently simulated with undersampling along pseudo-spiral Golden angle Cartesian trajectories for various velocity encoding schemes. Data were reconstructed using a locally low rank approach to obtain mean and turbulent flow fields to be compared to ground truth. Results show that, for a 15-min scan, velocity magnitudes can be reconstructed with good accuracy relatively independent of the velocity encoding scheme (SSIMU=0.938±0.003)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{U}=0.938\\pm 0.003)$$\\end{document}, good accuracy (SSIMU≥0.933\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{U}\\ge 0.933$$\\end{document}) and with peak velocity errors limited to 10%. Turbulence maps on the other hand suffer from both lower reconstruction quality (SSIMTKE≥0.323\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{TKE}\\ge 0.323$$\\end{document}) and larger sensitivity to undersampling, motion and velocity encoding strengths (SSIMTKE=0.570±0.110)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$SSI{M}_{TKE}=0.570\\pm 0.110)$$\\end{document} when compared to velocity maps. The best compromise to measure unwrapped velocity maps and turbulent kinetic energy given a fixed 15-min scan budget was found to be a 7-point multi-Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} acquisition with a low Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} tuned for best sensitivity to the range of expected intra-voxel standard deviations and a high Venc\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${V}_{enc}$$\\end{document} larger than the expected peak velocity.

Multiyear Interval Changes in Aortic Wall Shear Stress in Patients with Bicuspid Aortic Valve Assessed by 4D Flow MRI.

In patients with bicuspid aortic valve (BAV), 4D flow MRI can quantify regions exposed to abnormal aortic hemodynamics, including high wall shear stress (WSS), a known stimulus for arterial wall dysfunction. However, the long-term multiscan reproducibility of 4D flow MRI-derived hemodynamic parameters is unknown. To investigate the long-term stability of 4D flow MRI-derived peak velocity, WSS, and WSS-derived heatmaps in patients with BAV undergoing multiyear surveillance imaging. Retrospective. 20 BAV patients (mean age 48.4 ± 13.9 years; 14 males) with five 4D flow MRI scans, with intervals of at least 6 months between scans, and 125 controls (mean age: 50.7 ± 15.8 years; 67 males). 1.5 and 3.0T, prospectively ECG and respiratory navigator-gated aortic 4D flow MRI. Automated AI-based 4D flow analysis pipelines were used for data preprocessing, aorta 3D segmentation, and quantification of ascending aorta (AAo) peak velocity, peak systolic WSS, and heatmap-derived relative area of elevated WSS compared to WSS ranges in age and sex-matched normative control populations. Growth rate was derived from the maximum AAo diameters measured on the first and fifth MRI scans. One-way repeated measures analysis of variance. P < 0.05 indicated significance. One hundred 4D flow MRI exams (five per patient) were analyzed. The mean total follow-up duration was 5.5 ± 1.1 years, and the average growth rate was 0.3 ± 0.2 mm/year. Peak velocity, peak systolic WSS, and relative area of elevated WSS did not change significantly over the follow-up period (P = 0.64, P = 0.69, and P = 0.35, respectively). The patterns and areas of elevated WSS demonstrated good reproducibility on semiquantitative assessment. 4D flow MRI-derived peak velocity, WSS, and WSS-derived heatmaps showed good multiyear and multiscan stability in BAV patients with low aortic growth rates. These findings underscore the reliability of these metrics in monitoring BAV patients for potential risk of dilation. 3 TECHNICAL EFFICACY: Stage 1.

Comparison of Echo-Planar Imaging and Compressed Sensing in the Estimation of Flow Metrics from Aortic 4D Flow MR Imaging: A Healthy Volunteer Study.

Prolonged scanning of time-resolved 3D phase-contrast MRI (4D flow MRI) limits its routine use in clinical practice. An echo-planar imaging (EPI)-based sequence and compressed sensing can reduce the scan duration. We aimed to determine the impact of EPI for 4D flow MRI on the scan duration, image quality, and quantitative flow metrics. This was a prospective study of 15 healthy volunteers (all male, mean age 33 ± 5 years). Conventional sensitivity encoding (SENSE), EPI with SENSE (EPI), and compressed SENSE (CS) (reduction factors: 6 and 12, respectively) were scanned.Scan duration, qualitative indexes of image quality, and quantitative flow parameters of net flow volume, maximum flow velocity, wall shear stress (WSS), and energy loss (EL) in the ascending aorta were assessed. Two-dimensional phase-contrast cine MRI (2D-PC) was considered the gold standard of net flow volume and maximum flow velocity. Compared to SENSE, EPI and CS12 shortened scan durations by 71% and 73% (EPI, 4 min 39 sec; CS6, 7 min 29 sec; CS12, 4 min 14 sec; and SENSE, 15 min 51 sec). Visual image quality was significantly better for EPI than for SENSE and CS (P < 0.001). The net flow volumes obtained with SENSE, EPI, and CS12 and those obtained with 2D-PC were correlated well (r = 0.950, 0.871, and 0.850, respectively). However, the maximum velocity obtained with EPI was significantly underestimated (P < 0.010). The average WSS was significantly higher with EPI than with SENSE, CS6, and CS12 (P < 0.001, P = 0.040, and P = 0.012, respectively). The EL was significantly lower with EPI than with CS6 and CS12 (P = 0.002 and P = 0.007, respectively). EPI reduced the scan duration, improved visual image quality, and was associated with more accurate net flow volume than CS. However, the flow velocity, WSS, and EL values obtained with EPI and other sequences may not be directly comparable.

Evaluating a Phase-Specific Approach to Aortic Flow: A 4D Flow MRI Study.

Aortic flow parameters can be quantified using 4D flow MRI. However, data are sparse on how different methods of analysis influence these parameters and how these parameters evolve during systole. To assess multiphase segmentations and multiphase quantification of flow-related parameters in aortic 4D flow MRI. Prospective. 40 healthy volunteers (50% male, 28.9 ± 5.0 years) and 10 patients with thoracic aortic aneurysm (80% male, 54 ± 8 years). 4D flow MRI with a velocity encoded turbo field echo sequence at 3 T. Phase-specific segmentations were obtained for the aortic root and the ascending aorta. The whole aorta was segmented in peak systole. In all aortic segments, time to peak (TTP; for flow velocity, vorticity, helicity, kinetic energy, and viscous energy loss) and peak and time-averaged values (for velocity and vorticity) were calculated. Static vs. phase-specific models were assessed using Bland-Altman plots. Other analyses were performed using phase-specific segmentations for aortic root and ascending aorta. TTP for all parameters was compared to TTP of flow rate using paired t-tests. Time-averaged and peak values were assessed using Pearson correlation coefficient. P < 0.05 was considered statistically significant. In the combined group, velocity in static vs. phase-specific segmentations differed by 0.8 cm/sec for the aortic root, and 0.1 cm/sec (P = 0.214) for the ascending aorta. Vorticity differed by 167 sec-1 mL-1 (P = 0.468) for the aortic root, and by 59 sec-1 mL-1 (P = 0.481) for the ascending aorta. Vorticity, helicity, and energy loss in the ascending aorta, aortic arch, and descending aorta peaked significantly later than flow rate. Time-averaged velocity and vorticity values correlated significantly in all segments. Static 4D flow MRI segmentation yields comparable results as multiphase segmentation for flow-related parameters, eliminating the need for time-consuming multiple segmentations. However, multiphase quantification is necessary for assessing peak values of aortic flow-related parameters. 2 TECHNICAL EFFICACY STAGE: 3.

Abstract 12157: 4d Flow Mri Demonstrates Hemodynamic Normalization After Coarctation Repair in Pediatric Patients

Background: Coarctation of the aorta (COA) is a focal aortic narrowing, and intervention is required for patients with severe hemodynamic impairment. Following intervention, patients remain at risk for long-term re-coarctation. We used 4D flow MRI to assess aortic hemodynamics pre- and post- COA repair in children compared to age matched healthy controls. Methods: Aortic 4D flow MRI was performed in 5 pediatric COA patients (baseline age 6-14 yrs, 1F) pre- and post COA repair (4 native COA, 1 re-intervention) and 5 age-matched controls (ages 9-17 yrs, 2 female). Peak systolic velocities were quantified with velocity maximum intensity projections (MIP) ROIs in the ascending aorta (AAo), aortic arch, distal to the coarctation, and descending aorta (DAo) (Figure 1A). For flow quantification, nine 2D planes were placed along the aorta. Regional net flow was determined by averaging the 2D plane flows by region. The ratio between DAo to AAo (DAo/AAo) net flow was used to assess collateral flow. Results: Velocities were generally higher and more consistent across the aorta following surgery (Figure 1A). Plots highlighting changes in DAo/AAo flow ratio are shown in Figure 1B. Compared to controls, DAo/AAo flow ratio was significantly lower prior to COA repair (0.38±0.11 vs 0.61±0.05, p = 0.0004), indicating flow obstruction at the COA and presence of substantial collateral flow. Post COA repair DAo/AAo flow ratio was similar compared to age matched controls (0.59±0.06 vs 0.61±0.05, p = 0.51), indicating normalization of aortic flow. Patient 2, who underwent COA repair via stent placement showed the greatest improvement and normalization of flow consistency (DAo/AAo) across the aorta after intervention. Conclusion: A ortic 4D flow MRI shows normalization of aortic flow velocities, decreased collateral flow following COA repair, and has potential for long term surveillance and quantification of pre- and post-COA repair hemodynamic changes in children.

Machine learning for the automatic assessment of aortic rotational flow and wall shear stress from 4D flow cardiac magnetic resonance imaging.

Three-dimensional (3D) time-resolved phase-contrast cardiac magnetic resonance (4D flow CMR) allows for unparalleled quantification of blood velocity. Despite established potential in aortic diseases, the analysis is time-consuming and requires expert knowledge, hindering clinical application. The present research aimed to develop and test a fully automatic machine learning-based pipeline for aortic 4D flow CMR analysis. Four hundred and four subjects were prospectively included. Ground-truth to train the algorithms was generated by experts. The cohort was divided into training (323 patients) and testing (81) sets and used to train and test a 3D nnU-Net for segmentation and a Deep Q-Network algorithm for landmark detection. In-plane (IRF) and through-plane (SFRR) rotational flow descriptors and axial and circumferential wall shear stress (WSS) were computed at ten planes covering the ascending aorta and arch. Automatic aortic segmentation resulted in a median Dice score (DS) of 0.949 and average symmetric surface distance of 0.839 (0.632-1.071) mm, comparable with the state of the art. Aortic landmarks were located with a precision comparable with experts in the sinotubular junction and first and third supra-aortic vessels (p = 0.513, 0.592 and 0.905, respectively) but with lower precision in the pulmonary bifurcation (p = 0.028), resulting in precise localisation of analysis planes. Automatic flow assessment showed excellent (ICC > 0.9) agreement with manual quantification of SFRR and good-to-excellent agreement (ICC > 0.75) in the measurement of IRF and axial and circumferential WSS. Fully automatic analysis of complex aortic flow dynamics from 4D flow CMR is feasible. Its implementation could foster the clinical use of 4D flow CMR. • 4D flow CMR allows for unparalleled aortic blood flow analysis but requires aortic segmentation and anatomical landmark identification, which are time-consuming, limiting 4D flow CMR widespread use. • A fully automatic machine learning pipeline for aortic 4D flow CMR analysis was trained with data of 323 patients and tested in 81 patients, ensuring a balanced distribution of aneurysm aetiologies. • Automatic assessment of complex flow characteristics such as rotational flow and wall shear stress showed good-to-excellent agreement with manual quantification.

Comprehensive Neonatal Cardiac, Feed and Wrap, Non-contrast, Non-sedated, Free-breathing Compressed Sensing 4D Flow MRI Assessment.

Cardiac MRI is an important imaging tool in congenital cardiac disease, but its use has been limited in the neonatal population as general anesthesia has been needed for breath-holding. Technological advances in four-dimensional (4D) flow MRI have now made nonsedated free-breathing acquisition protocols a viable clinical option, but the method requires prospective validation in neonates. To test the feasibility of compressed sensing (CS) 4D flow MRI in the neonatal population and to compare with standard previously validated two-dimensional (2D) phase-contrast (PC) flow MRI. Prospective, cohort, image quality. A total of 14 healthy neonates (median [range] age: 2.5 [0-80] days; 8 male). Noncontrast 2D cine gradient echo sequence with through-plane velocity encoding (PC) sequence and compressed sensing (CS) three-dimensional (3D), time-resolved, cine phase-contrast MRI with 3D velocity-encoding (4D flow MRI) at 3 T. Aortic 2D PC, and aortic, pulmonary trunk and superior vena cava CS 4D flow MRI were acquired using the feed and wrap technique (nonsedated) and quantified using commercially available software. Aortic flow and peak velocity were compared between methods. Internal consistency of 4D flow MRI was determined by comparing mean forward flow of the main pulmonary artery (MPA) vs. the sum of left and right pulmonary artery flows (LPA and RPA) and by comparing mean ascending aorta forward flow (AAo) vs. the sum of superior vena cava (SVC) and descending aorta flows (DAo). Flow and peak-velocity comparisons were assessed using paired t-tests, with P < 0.05 considered significant, and Bland-Altman analysis. Interobserver and intraobserver agreement and internal consistency were analyzed by intraclass correlation co-efficient (ICC). There was no statistically significant difference between ascending aortic forward flow between 2D PC and CS 4D Flow MRI (P=0.26) with a bias of 0.11 mL (-0.59 to 0.82 mL) nor peak velocity (P =0.11), with a bias of -5cm/sec and (-26 to 16 cm/sec). There was excellent interobserver and intraobserver agreement for each vessel (interobserver ICC: AAo 1.00; DAo 0.94, SVC 0.90, MPA 0.99, RPA 0.98, LPA 0.96; intraobserver ICC: AAo 1.00; DAo 0.99, SVC 0.98, MPA 1.00, RPA 1.00, LPA 0.99). Internal consistency measures showed excellent agreement for both mean forward flow of main pulmonary artery vs. the sum of left and right pulmonary arteries (ICC: 0.95) and mean ascending aorta forward flow vs. the sum of superior vena cava and descending aorta flows (ICC: 1.00). Sedation-free neonatal feed and wrap MRI is well tolerated and feasible. CS 4D flow MRI quantification is similar to validated 2D PC free-breathing imaging with excellent interobserver and intraobserver agreement. 1 TECHNICAL EFFICACY: Stage 2.

Bicuspid aortic valve morphology and hemodynamics by same-day echocardiography and cardiac MRI.

This study investigated the impact of bicuspid aortic valve (BAV) on valve morphology and motion as well as proximal and aortic hemodynamics using a same-day echocardiography and cardiac MRI. Transthoracic echocardiography, two-dimensional cine MRI of the aortic valve, and aortic 4D flow MRI were performed on the same day in 9 normofunctional BAV patients (age = 41 ± 12, 3 female), 4 BAV with moderate to severe aortic stenosis (AS) (age = 63 ± 5, 1 female), and 36 healthy tricuspid aortic valve controls (age = 52 ± 10, 21 female). Valve opening and closing timings and transvalvular peak velocity were measured using B-mode and Doppler echocardiogram, respectively. Valve orifice morphology at a fully-opened state was characterized using cine MRI. Ascending aortic (AAo) wall shear stress (WSS) was measured using 4D flow MRI data. Valve motion timings were similar between BAV and controls. BAV was associated with an increased orifice aspect ratio (1.44 ± 0.11 vs. 1.10 ± 0.13, P < 0.001), transvalvular peak velocity (1.5 ± 0.3 vs. 1.2 ± 0.2m/s, P < 0.001) and maximum AAo WSS (1.62 ± 0.31 vs. 0.91 ± 0.24Pa, P < 0.001). The increased orifice aspect ratio was associated with the increase in transvalvular peak velocity (r = 0.80, P < 0.0001) and maximum AAo WSS (r = 0.83, P < 0.0001). Transvalvular peak velocity was also positively correlated with maximum AAo WSS (r = 0.83, P < 0.0001). A same-day echo and MRI imaging allows for a comprehensive assessment of the impact of aortic valve disease on valve function and hemodynamics. In this pilot application to BAV, we found increased orifice aspect ratio may be responsible for increased transvalvular peak velocity and maximum AAo WSS.

Flow displacement and decreased wall shear stress might be associated with the growth rate of an ascending aortic dilatation.

OBJECTIVESOur goal was to evaluate whether four-dimensional (4D) flow magnetic resonance imaging (MRI) can predict the growth rate of dilatation of the ascending aorta (AA) in patients with a tricuspid, normally functioning aortic valve.METHODSIn this prospective clinical study, aortic 4D flow MRI was performed at the Kuopio University Hospital on 30 patients diagnosed with AA dilatation (maximum diameter >40 mm) between August 2017 and July 2020. The MRI was repeated after a 1-year follow-up, with AA dimensions and 4D flow parameters analysed retrospectively at both time points. The standard error of measurement was used to assess the statistical significance of the growth rate of AA dilatation. Flow displacement (FD) was transformed to a class-scaled parameter using FD ≥5% as a threshold.RESULTSStatistically significant growth [median 2.1 mm (1.5–2.2 mm); P = 0.03] was detected in 6 male patients (20%); the AA diameter remained unchanged [0.2 mm (−0.3 to 0.9 mm)] in 24 patients (80%). An increased FD at the baseline was associated with significant growth during the 1-year follow-up in the proximal AA. An association was detected between decreased total wall shear stress and significant aortic growth in the inner curve of the sinotubular junction [529 mPa (449–664 mPa) vs 775 mPa (609–944 mPa); P = 0.03] and the anterior side of the proximal aortic arch [356 mPa (305–367 mPa) vs 493 mPa (390–586 mPa); P < 0.001].CONCLUSIONSFD and decreased wall shear stress seem to be associated with significant growth of AA dilatation at the 1-year follow-up. Thus, 4D flow MRI might be useful in assessing risk for AA diameter growth in patients with a tricuspid aortic valve.

Bicuspid aortic valve fusion length correlates with maximum aortic diameter and heamodynamic abnormalities: a 4D flow CMR study

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Guala A. received funding from the Spanish Ministry of Science, Innovation and Universities. Background Bicuspid aortic valve (BAV), a congenital heart defect, is associated with ascending aorta dilation, possibly via alteration of aortic blood flow [1]. In BAV abnormal flow condition have been associated with aortic extracellular matrix dysregulation and elastic fiber degeneration [2]. Current morphological classification of BAV patients with aortic valve with a single fusion between two adjacent leaflets does not allow for risk stratification. Purpose This research work tested whether the extent of fusion between leaflets is related to AAo diameter and flow alterations. Methods Ninety BAV patients free from moderate and severe aortic valve disease and with no previous aortic or aortic valve surgery or replacement were prospectively enrolled. A comprehensive magnetic resonance protocol comprised a stack of double-oblique 2D balanced steady-state free-precession (bSSFP) cine CMR of the aortic valve, which was used to measure the length of the fusion between leaflets, a cine CMR at the level of the pulmonary bifurcation to assess aortic diameter and 4D flow MRI sequence to assess flow characteristics and regional stiffness [3]. Jet angle and flow radial displacement, quantifying the extent of flow eccentricity, and systolic flow reversal ratio (SFRR), assessing the relative amount of backward flow during systole, were computed at 8 equidistant planes in the ascending aorta and 4 equidistant planes in the aortic arch [4]. A two-tailed p-value &amp;lt; 0.05 was considered statistically significant. Results The length of leaflet fusion varied widely (median 7.7 mm, inter-quartile range [5.5; 10.2]), Table 1). In bivariate analysis, fusion length was also associated to ascending aortic diameter (R = 0.391, p &amp;lt; 0.001), age (R = 0.313, p = 0.005) and body surface area (R = 0.396, p &amp;lt; 0.001). It was also positively related to flow abnormalities: like displacement in the proximal and distal ascending aorta, jet angle in the mid ascending aorta, and SFRR in the ascending aorta and the aortic arch (see Figure 1). The association between fusion length and ascending aorta diameter persisted in multivariate analysis after correction for age (p = 0.006). Conclusions Bicuspid aortic valve fusion extent varies greatly and it is associated with aortic diameter, possibly through flow alterations. Prospective longitudinal studies are needed to establish whether fusion length may allow for risk stratification in bicuspid aortic valve patients.

Abnormal aortic hemodynamics at predilection sites for dissection in patients with Marfan Syndrome: a 4D flow study

Abstract Funding Acknowledgements Type of funding sources: Private grant(s) and/or Sponsorship. Main funding source(s): AMC Foundation Horstingstuit Foundation Introduction Patients with Marfan syndrome (MFS) may develop aneurysmatic dilatation and dissection of the aorta with a consequence of sudden death at relatively young age. We performed an aortic 4D flow MRI analysis, providing a comprehensive quantification and visualization of abnormal aortic velocity and wall shear stress (WSS) magnitude and direction with recently developed techniques (1,2). We hypothesize that abnormal hemodynamics are found at predilection sites for aortic dissection in MFS patients. Methods This prospective study included 56 MFS patients and 25 healthy subjects as controls. Aortic 4D flow MRI was performed on a 3T Philips Ingenia system (Best, Netherlands). The aorta was manually segmented on time-averaged phase contrast MR angiogram images (phase contrast images multiplied by absolute velocity) by thresholding, watershed, and manual voxel in-/exclusion. The segmentations were used to mask the velocities, calculate WSS, and co-registration for quantification of abnormal hemodynamics (3). Abnormally elevated velocity and WSS were defined as higher than the three-dimensional 95% confidence interval as determined in the control group. Abnormally directed velocity and WSS were defined as vector angle differences higher than 120°. The aorta was subdivided in six regions of interest (ROIs) for total multiple linear regression with age, aortic diameter, and blood pressure characteristics. Independent predictors were defined as characteristics that were significant in the total model. Significance was defined as p &amp;lt; 0.05 with Bonferonni correction. The 3D-maps with abnormal hemodynamics were co-registered and added to create 3D-maps that show the incidence of abnormal hemodynamics. Results Figure 1 shows examples of maps with abnormal velocity and WSS magnitude and direction respectively. Ascending elevated velocity was associated with age, aortic diameter and blood pressure characteristics, whereas elevated WSS was associated with blood pressure characteristics only. No independent predictors were found for abnormally directed hemodynamics. Figure 2 shows the incidence maps for abnormally elevated velocity and abnormally directed WSS in two patients. The maximum incidence for elevated velocity and WSS were 32% and 20%, respectively, and found in the ascending aorta. The maxima for abnormally directed velocity and WSS were 18% and 39%, respectively, and found in the inner proximal descending aorta. Conclusion Altered aortic geometry and wall properties in MFS patients cause detectable hemodynamic effects in 30% of our cohort at known predilection sites for aortic dissection in MFS patients: the ascending aorta and proximal descending aorta. Independent measures of altered hemodynamics could possibly indicate individual patients at risk for aortic dissection.

Six-year serial follow-up with aortic 4D flow cardiovascular magnetic resonance in a patient with bicuspid aortic valve.

Six-year serial follow-up with aortic 4D flow cardiovascular magnetic resonance in a patient with bicuspid aortic valve.

Accelerated aortic 4D flow MRI with wave-CAIPI.

The aim of this study was to investigate the acceleration potential of wave-CAIPI (controlled aliasing in parallel imaging) for 4D flow MRI, provided that image quality and precision of flow parameters are maintained. The 4D flow MRIs with acceleration factor R = 2 were performed on 10 healthy volunteers, using both wave-CAIPI and standard Cartesian/2D-CAIPI sampling for reference. In addition, 1 patient with known aortic valve stenosis was examined. The flow rate ( ), net flow ( ), peak velocity , and net average through-plane velocity ( ) were calculated in eight analysis planes in the ascending and descending aorta. The acquisitions were retrospectively undersampled (R = 6), and deviations of flow parameters and hemodynamic flow patterns were evaluated. Flow parameters measured with an undersampled wave-CAIPI trajectory showed considerably smaller deviations to the references than the 2D-CAIPI images. For , the mean absolute differences were cm/s versus cm/s; for , the mean absolute differences were ml versus ml for wave-CAIPI versus 2D-CAIPI, respectively. Noise calculations indicate that the 2D-CAIPI sampling exhibits a higher average noise level than the wave-CAIPI technique. Qualitative discrepancies in hemodynamic flow patterns, visualized through streamlines, particle traces and flow velocity vectors, could be reduced by using the undersampled wave-CAIPI trajectory. Use of wave-CAIPI instead of 2D-CAIPI sampling in retrospectively 6-fold accelerated 4D flow MRI enhances the precision of flow parameters. The acquisition time of 4D flow measurements could be reduced by a factor of 3, with minimal differences in flow parameters.

5D Flow MRI: A Fully Self-gated, Free-running Framework for Cardiac and Respiratory Motion-resolved 3D Hemodynamics.

To implement, validate, and apply a self-gated free-running whole-heart five-dimensional (5D) flow MRI framework to evaluate respiration-driven effects on three-dimensional (3D) hemodynamics in a clinical setting. In this prospective study, a free-running five-dimensional (5D) flow sequence was implemented with 3D radial sampling, self-gating, and a compressed-sensing reconstruction. The 5D flow was evaluated in a pulsatile phantom and adult participants with aortic and/or valvular disease who were enrolled between May and August 2019. Conventional twofold-accelerated four-dimensional (4D) flow of the thoracic aorta with navigator gating was performed as a reference comparison. Continuous parameters were evaluated for parameter normality and were compared between conventional 4D flow and 5D flow using a signed-rank or two-tailed paired t test. Differences between respiratory states were evaluated using a repeated-measure analysis of variance or a nonparametric Friedman test. A total of 20 adult participants (mean age, 49 years ± 17 [standard deviation]; 18 men and two women) were included. In vitro 5D flow results showed excellent agreement with conventional 4D flow-derived values (peak and net flow, <7% difference over all quantified planes). Whole-heart 5D flow data were collected in all participants in 7.65 minutes ± 0.35 (acceleration rate = 36.0-76.9) versus 9.88 minutes ± 3.17 for conventional aortic 4D flow. In vivo, 5D flow demonstrated moderate agreement with conventional 4D flow but demonstrated overestimation in net flow and peak velocity (up to 26% and 12%, respectively) in the ascending aorta and underestimation (<12%) in the arch and descending aorta. Respiratory-resolved analyses of caval veins showed significantly increased net and peak flow in the inferior vena cava in end inspiration compared with end expiration, and the opposite trend was shown in the superior vena cava. A free-running 5D flow MRI framework consistently captured cardiac and respiratory motion-resolved 3D hemodynamics in less than 8 minutes. Supplemental material is available for this article. © RSNA, 2020.

Highly accelerated aortic 4D flow MRI using compressed sensing: Performance at different acceleration factors in patients with aortic disease.

To systematically assess the feasibility and performance of a highly accelerated compressed sensing (CS) 4D flow MRI framework at three different acceleration factors (R) for the quantification of aortic flow dynamics and wall shear stress (WSS) in patients with aortic disease. Twenty patients with aortic disease (58 ± 15 y old; 19 M) underwent four 4D flow scans: one conventional (GRAPPA, R = 2) and three CS 4D flows with R = 5.7, 7.7, and 10.2. All scans were acquired with otherwise equivalent imaging parameters on a 1.5T scanner. Peak-systolic velocity (Vmax ), peak flow (Qmax ), and net flow (Qnet ) were quantified at the ascending aorta (AAo), arch, and descending aorta (DAo). WSS was calculated at six regions within the AAo and arch. Mean scan times for the conventional and CS 4D flows with R = 5.7, 7.7, and 10.2 were 9:58 ± 2:58 min, 3:40 ± 1:19 min, 2:50 ± 0:56 min, and 2:05 ± 0:42 min, respectively. Vmax , Qmax , and Qnet were significantly underestimated by all CS protocols (underestimation ≤ -7%, -9%, and -10% by CS, R = 5.7, 7.7, and 10.2, respectively). WSS measurements showed the highest underestimation by all CS protocols (underestimation ≤ -9%, -12%, and -14% by CS, R = 5.7, 7.7, and 10.2). Highly accelerated aortic CS 4D flow at R = 5.7, 7.7, and 10.2 showed moderate agreement with the conventional 4D flow, despite systematically underestimating various hemodynamic parameters. The shortened scan time may enable the clinical translation of CS 4D flow, although potential hemodynamic underestimation should be considered when interpreting the results.

Investigation of Aortic Wall Thickness, Stiffness and Flow Reversal in Patients With Cryptogenic Stroke: A 4D Flow MRI Study.

Stroke etiology is undetermined in approximately one-sixth to one-third of patients. The presence of aortic flow reversal and plaques in the descending aorta (DAo) has been identified as a potential retrograde embolic mechanism. To assess the relationships between aortic stiffness, wall thickness, and flow reversal in patients with cryptogenic stroke and healthy controls. Prospective. Twenty one patients with cryptogenic stroke and proven DAo plaques (69 ± 9 years, 43% female), 18 age-matched controls (age: 65 ± 8 years, 61% female), and 14 younger controls (36 ± 9 years, 57% female). 1.5T; 4D flow MRI and 3D dark blood T1 -weighted turbo spin echo MRI of the aorta. Noncontrast aortic 4D flow MRI to measure 3D flow dynamics and 3D dark blood aortic wall MRI to assess wall thickness. 4D flow MRI analysis included automated quantification of aortic stiffness by pulse wave velocity (PWV) and voxelwise mapping of the flow reversal fraction (FRF). Analysis of variance (ANOVA) or Kruskal-Wallis tests, Student's unpaired t-tests or Wilcoxon rank-sum tests, regression analysis. Aortic PWV and FRF were statistically higher in patients (8.9 ± 1.7 m/s, 18.4 ± 7.7%) than younger controls (5.3 ± 0.8 m/s, P < 0.0167; 8.5 ± 2.9%, P < 0.0167), but not age-matched controls (8.2 ± 1.6 m/s, P = 0.22; 15.6 ± 5.8%, P = 0.22). Maximum aortic wall thickness was higher in patients (3.1 ± 0.7 mm) than younger controls (2.2 ± 0.2 mm, P < 0.0167) and age-matched controls (2.7 ± 0.5 mm) (P < 0.0167). For all subjects, positive relationships were found between PWV and age (R2 = 0.71, P < 0.05), aortic wall thickness (R2 = 0.20, P < 0.05), and FRF (R2 = 0.47, P < 0.05). Patients demonstrated relationships between PWV and FRF in the ascending aorta (R2 = 0.32, P < 0.05) and arch (R2 = 0.24, P < 0.05). This study showed the utility of 4D flow MRI for evaluating aortic PWV and voxelwise flow reversal. Positive relationships between aortic PWV, wall thickness, and flow reversal support the hypothesis that aortic stiffness is involved in this retrograde embolic mechanism. 2 TECHNICAL EFFICACY STAGE: 1.

Four-dimensional Flow Magnetic Resonance Imaging Quantification of Blood Flow in Bicuspid Aortic Valve.

Four-dimensional (D) flow magnetic resonance imaging (MRI) is limited by time-consuming and nonstandardized data analysis. We aimed to test the efficiency and interobserver reproducibility of a dedicated 4D flow MRI analysis workflow. Thirty retrospectively identified patients with bicuspid aortic valve (BAV, age=47.8±11.8 y, 9 male) and 30 healthy controls (age=48.8±12.5 y, 21 male) underwent Aortic 4D flow MRI using 1.5 and 3 T MRI systems. Two independent readers performed 4D flow analysis on a dedicated workstation including preprocessing, aorta segmentation, and placement of four 2D planes throughout the aorta for quantification of net flow, peak velocity, and regurgitant fraction. 3D flow visualization using streamlines was used to grade aortic valve outflow jets and extent of helical flow. 4D flow analysis workflow time for both observers: 5.0±1.4 minutes per case (range=3 to 10 min). Valve outflow jets and flow derangement was visible in all 30 BAV patients (both observers). Net flow, peak velocity, and regurgitant fraction was significantly elevated in BAV patients compared with controls except for regurgitant fraction in plane 4 (91.1±29.7 vs. 62.6±19.6 mL/s, 37.1% difference; 121.7±49.7 vs. 90.9±26.4 cm/s, 28.9% difference; 9.3±10.1% vs. 2.0±3.4%, 128.0% difference, respectively; P<0.001). Excellent intraclass correlation coefficient agreement for net flow: 0.979, peak velocity: 0.931, and regurgitant fraction: 0.928. Our study demonstrates the potential of an efficient data analysis workflow to perform standardized 4D flow MRI processing in under 10 minutes and with good-to-excellent reproducibility for flow and velocity quantification in the thoracic aorta.

Fully automated 3D aortic segmentation of 4D flow MRI for hemodynamic analysis using deep learning

To generate fully automated and fast 4D-flow MRI-based 3D segmentations of the aorta using deep learning for reproducible quantification of aortic flow, peak velocity, and dimensions. A total of 1018 subjects with aortic 4D-flow MRI (528 with bicuspid aortic valve, 376 with tricuspid aortic valve and aortic dilation, 114 healthy controls) comprised the data set. A convolutional neural network was trained to generate 3D aortic segmentations from 4D-flow data. Manual segmentations served as the ground truth (N = 499 training, N = 101 validation, N = 418 testing). Dice scores, Hausdorff distance, and average symmetrical surface distance were calculated to assess performance. Aortic flow, peak velocity, and lumen dimensions were quantified at the ascending, arch, and descending aorta and compared using Bland-Altman analysis. Interobserver variability of manual analysis was assessed on a subset of 40. Convolutional neural network segmentation required 0.438 ± 0.355 seconds versus 630 ± 254 seconds for manual analysis and demonstrated excellent performance with a median Dice score of 0.951 (0.930-0.966), Hausdorff distance of 2.80 (2.13-4.35), and average symmetrical surface distance of 0.176 (0.119-0.290). Excellent agreement was found for flow, peak velocity, and dimensions with low bias and limits of agreement less than 10% difference versus manual analysis. For aortic volume, limits of agreement were moderate within 16.3%. Interobserver variability (median Dice score: 0.950; Hausdorff distance: 2.45; and average symmetrical surface distance: 0.145) and convolutional neural network-based analysis (median Dice score: 0.953-0.959; Hausdorff distance: 2.24-2.91; and average symmetrical surface distance: 0.145-1.98 to observers) demonstrated similar reproducibility. Deep learning enabled fast and automated 3D aortic segmentation from 4D-flow MRI, demonstrating its potential for efficient clinical workflows. Future studies should investigate its utility for other vasculature and multivendor applications.

Impact of age, sex, and global function on normal aortic hemodynamics.

To examine the effects of age, sex, and left ventricular global function on velocity, helicity, and 3D wall shear stress (3D-WSS) in the aorta of N=100 healthy controls. Fifty female and 50 male volunteers with no history of cardiovascular disease, with 10 volunteers per age group (18-30, 31-40, 41-50, 51-60, and 61-80 years) underwent aortic 4D-flow MRI. Quantification of systolic aortic peak velocity, helicity, and 3D-WSS distribution and the calculation of age group-averaged peak systolic velocity and 3D-WSS maps ("atlases") were computed. Age-related and sex-related changes in peak velocity, helicity, and 3D-WSS were computed and correlated with standard metrics of left ventricular function derived from short-axis cine MRI. No significant differences were found in peak systolic velocity or 3D-WSS based on sex except for the 18- to 30-year-old group (males 8% higher velocity volume and 3D-WSS surface area). Between successively older groups, systolic velocity decreased (13%, <1%, 7%, and 55% of the aorta volume) and 3D-WSS decreased (21%, 2%, 30%, and 62% of the aorta surface area). Mean velocity, mean 3D-3D-WSS, and median helicity increased with cardiac output (r=0.27-0.43, all P<.01), and mean velocity and 3D-WSS decreased with increasing diameter (r>0.35, P<.001). Arch and descending aorta systolic mean velocity, mean 3D-WSS, and median helicity increased with normalized left ventricular volumes: end diastolic volume (r=0.31-0.37, P<.01), end systolic volume (r=0.27-0.35, P<.01), and stroke volume (r=0.28-0.35, P<.01). Healthy aortic hemodynamics are dependent on subject age, and correlate with vessel diameter and cardiac function.