BACKGROUND: Kidney disease is the most important predictor of death in patients with a Fontan circulation, yet its clinical and hemodynamic correlates have not been well established. METHODS AND RESULTS: A total of 53 ambulatory patients with a Fontan circulation (median age, 16.2 years, 52.8% male patients) underwent advanced cardiovascular magnetic resonance assessment, including 4-dimensional flow imaging and computational fluid dynamics. Estimated glomerular filtration rate (eGFR) <90 mL/min per 1.73 m2 was observed in 20.8% and albumin-to-creatinine ratio >3 mg/mmol in 39.6%. The average eGFR decline rate was -1.83 mL/min per 1.73 m2 per year (95% CI, -2.67 to -0.99; P<0.001). Lower eGFR was associated with older age, larger body surface area at examination, longer time since Fontan procedure, and lower systemic ventricular ejection fraction. Higher albumin-to-creatinine ratio was associated with absence of fenestration at the Fontan operation, and older age and lower systemic ventricular ejection fraction at the assessment. Lower cross-sectional area of the Fontan conduit indexed to flow (r=0.32, P=0.038), higher inferior vena cava-conduit velocity mismatch factor (r=-0.35, P=0.022), higher kinetic energy indexed to flow in the total cavopulmonary connection (r=-0.59, P=0.005), and higher total cavopulmonary connection resistance (r=-0.42, P=0.005 at rest; r=-0.43, P=0.004 during exercise) were all associated with lower eGFR but not with albuminuria. CONCLUSIONS: Kidney dysfunction and albuminuria are common among clinically well adolescents and young adults with a Fontan circulation. Advanced cardiovascular magnetic resonance-derived metrics indicative of declining Fontan hemodynamics are associated with eGFR and might serve as targets to improve kidney health. Albuminuria might be driven by other factors that need further investigation.

Thoracic aortic aneurysm (TAA) is a local dilation of the thoracic aorta. Although universally used, aneurysm diameter alone is a poor predictor of major complications such as rupture. There is a need for better biomarkers for risk assessment that also reflect the aberrant flow patterns found in TAAs. Furthermore, hypertension is often present in TAA patients and may play a role in progression of aneurysm. The exact relation between TAAs and hypertension is poorly understood. This study aims to create a numerical model of hypertension in the aorta by using computational fluid dynamics. First, a normotensive state was simulated in which flow and resistance were kept unaltered. Second, a hypertensive state was modeled in which blood inflow was increased by 30%. Third, a hypertensive state was modeled in which the proximal and peripheral resistances and capacitance parameters from the three-element Windkessel boundary condition were adjusted to mimic an increase in resistance of the rest of the cardiovascular system. One patient with degenerative TAA and one healthy control were successfully simulated at hypertensive states and were extensively analyzed. Furthermore, three additional TAA patients and controls were simulated to validate our method. Hemodynamic variables such as wall shear stress, oscillatory shear index, endothelial cell activation potential (ECAP), vorticity and helicity were studied to gain more insight on the effects of hypertension on flow patterns in TAAs. By comparing a TAA patient and a control at normotensive state at peak-systole, helicity and vorticity were found to be lower in the TAA patient throughout the entire domain. No major changes in flow and flow derived quantities were observed for the TAA patient and control when resistance was increased. When flow rate was increased, regions with high ECAP values were found to reduce in TAA patients in the aneurysm region which could reduce the risk of thrombogenesis. Thus, it may be important to assess cardiac output in patients with TAA.

There is a pressing need to establish novel biomarkers to predict the progression of thoracic aortic aneurysm (TAA) dilatation. Aside from hemodynamics, the roles of oxygen (O₂) and nitric oxide (NO) in TAA pathogenesis are potentially significant. As such, it is imperative to comprehend the relationship between aneurysm presence and species distribution in both the lumen and aortic wall. Given the limitations of existing imaging methods, we propose the use of patient-specific computational fluid dynamics (CFD) to explore this relationship. We have performed CFD simulations of O₂ and NO mass transfer in the lumen and aortic wall for two cases: a healthy control (HC) and a patient with TAA, both acquired using 4D-flow magnetic resonance imaging (MRI). The mass transfer of O₂ was based on active transport by hemoglobin, while the local variations of the wall shear stress (WSS) drove NO production. Comparing hemodynamic properties, the time-averaged WSS was considerably lower for TAA, while the oscillatory shear index and endothelial cell activation potential were notably elevated. O₂ and NO showed a non-uniform distribution within the lumen and an inverse correlation between the two species. We identified several locations of hypoxic regions for both cases due to lumen-side mass transfer limitations. In the wall, NO varied spatially, with a clear distinction between TAA and HC. In conclusion, the hemodynamics and mass transfer of NO in the aorta exhibit the potential to serve as a diagnostic biomarker for TAA. Furthermore, hypoxia may provide additional insights into the onset of other aortic pathologies.

Purpose: Intraventricular blood flow dynamics are associated with cardiac function. Accurate, noninvasive, and easy assessments of hemodynamic quantities (such as velocity, vortex, and pressure) could be an important addition to the clinical diagnosis and treatment of heart diseases. However, the complex time-varying flow brings many challenges to the existing noninvasive image-based hemodynamic assessments. The development of reliable techniques and analysis tools is essential for the application of hemodynamic biomarkers in clinical practice. Methods: In this study, a time-resolved particle tracking method, Shake-the-Box, was applied to reconstruct the flow in a realistic left ventricle (LV) silicone model with biological valves. Based on the obtained velocity, 4D pressure field was calculated using a Poisson equation-based pressure solver. Furthermore, flow analysis by proper orthogonal decomposition (POD) of the 4D velocity field has been performed. Results: As a result of the Shake-the-Box algorithm, we have extracted: (i) particle positions, (ii) particle tracks, and finally, (iii) 4D velocity fields. From the latter, the temporal evolution of the 3D pressure field during the full cardiac cycle was obtained. The obtained maximal pressure difference extracted along the base-to-apex was about 2.7 mmHg, which is in good agreement with those reported in vivo. The POD analysis results showed a clear picture of different scale of vortices in the pulsatile LV flow, together with their time-varying information and corresponding kinetic energy content. To reconstruct 95% of the kinetic energy of the LV flow, only the first six POD modes would be required, leading to significant data reduction. Conclusions: This work demonstrated Shake-the-Box is a promising technique to accurately reconstruct the left ventricle flow field in vitro. The good spatial and temporal resolutions of the velocity measurements enabled a 4D reconstruction of the pressure field in the left ventricle. The application of POD analysis showed its potential in reducing the complexity of the high-resolution left ventricle flow measurements. For future work, image analysis, multi-modality flow assessments, and the development of new flow-derived biomarkers can benefit from fast and data-reducing POD analysis.

Fontan patients require a balanced hepatic blood flow distribution (HFD) to prevent pulmonary arteriovenous malformations. Currently, HFD is quantified by tracking Fontan conduit flow, assuming hepatic venous (HV) flow to be uniformly distributed within the Fontan conduit. However, this assumption may be unvalid leading to inaccuracies in HFD quantification with potential clinical impact. The aim of this study was to (i) assess the mixing of HV flow and inferior vena caval (IVC) flow within the Fontan conduit and (ii) quantify HFD by directly tracking HV flow and quantitatively comparing results with the conventional approach. Patient-specific, time-resolved computational fluid dynamic models of 15 total cavopulmonary connections were generated, including the HV and subhepatic IVC. Mixing of HV and IVC flow, on a scale between 0 (no mixing) and 1 (perfect mixing), was assessed at the caudal and cranial Fontan conduit. HFD was quantified by tracking particles from the caudal (HFDcaudal conduit) and cranial (HFDcranial conduit) conduit and from the hepatic veins (HFDHV). HV flow was non-uniformly distributed at both the caudal (mean mixing 0.66 ± 0.13) and cranial (mean 0.79 ± 0.11) level within the Fontan conduit. On a cohort level, differences in HFD between methods were significant but small; HFDHV (51.0 ± 20.6%) versus HFDcaudal conduit (48.2 ± 21.9%, p = 0.033) or HFDcranial conduit (48.0 ± 21.9%, p = 0.044). However, individual absolute differences of 8.2-14.9% in HFD were observed in 4/15 patients. HV flow is non-uniformly distributed within the Fontan conduit. Substantial individual inaccuracies in HFD quantification were observed in a subset of patients with potential clinical impact.

Aortic aneurysm is associated with aberrant blood flow and wall shear stress (WSS). This can be studied by coupling magnetic resonance imaging (MRI) with computational fluid dynamics (CFD). For patient-specific simulations, extra attention should be given to the variation in segmentation of the MRI data-set and its effect on WSS. We performed CFD simulations of blood flow in the aorta for ten different volunteers and provided corresponding WSS distributions. The aorta of each volunteer was segmented four times. The same inlet and outlet boundary conditions were applied for all segmentation variations of each volunteer. Steady-state CFD simulations were performed with inlet flow based on phase-contrast MRI during peak systole. We show that the commonly used comparison of mean and maximal values of WSS, based on CFD in the different segments of the thoracic aorta, yields good to excellent correlation (0.78–0.95) for rescan and moderate to excellent correlation (0.64–1.00) for intra- and interobserver reproducibility. However, the effect of geometrical variations is higher for the voxel-to-voxel comparison of WSS. With this analysis method, the correlation for different segments of the whole aorta is poor to moderate (0.43–0.66) for rescan and poor to good (0.48–0.73) for intra- and interobserver reproducibility. Therefore, we advise being critical about the CFD results based on the MRI segmentations to avoid possible misinterpretation. While the global values of WSS are similar for different modalities, the variation of results is high when considering the local distributions.

Objectives Degenerative thoracic aortic aneurysm (TAA) patients are known to be at risk of life-threatening acute aortic events. Guidelines recommend preemptive surgery at diameters of greater than 55 mm, although many patients with small aneurysms show only mild growth rates and more than half of complications occur in aneurysms below this threshold. Thus, assessment of hemodynamics using 4-dimensional flow magnetic resonance has been of interest to obtain more insights in aneurysm development. Nonetheless, the role of aberrant flow patterns in TAA patients is not yet fully understood. Materials and Methods A total of 25 TAA patients and 22 controls underwent time-resolved 3-dimensional phase contrast magnetic resonance imaging with 3-directional velocity encoding (ie, 4-dimensional flow magnetic resonance imaging). Hemodynamic parameters such as vorticity, helicity, and wall shear stress (WSS) were calculated from velocity data in 3 anatomical segments of the ascending aorta (root, proximal, and distal). Regional WSS distribution was assessed for the full cardiac cycle. Results Flow vorticity and helicity were significantly lower for TAA patients in all segments. The proximal ascending aorta showed a significant increase in peak WSS in the outer curvature in TAA patients, whereas WSS values at the inner curvature were significantly lower as compared with controls. Furthermore, positive WSS gradients from sinotubular junction to midascending aorta were most prominent in the outer curvature, whereas from midascending aorta to brachiocephalic trunk, the outer curvature showed negative WSS gradients in the TAA group. Controls solely showed a positive gradient at the inner curvature for both segments. Conclusions Degenerative TAA patients show a decrease in flow vorticity and helicity, which is likely to cause perturbations in physiological flow patterns. The subsequent differing distribution of WSS might be a contributor to vessel wall remodeling and aneurysm formation.

Purpose: To assess errors associated with EPI-accelerated intracardiac 4D flow MRI (4DEPI) with EPI factor 5, compared with non-EPI gradient echo (4DGRE). Methods: Three 3T MRI experiments were performed comparing 4DEPI to 4DGRE: steady flow through straight tubes, pulsatile flow in a left-ventricle phantom, and intracardiac flow in 10 healthy volunteers. For each experiment, 4DEPI was repeated with readout and blip phase-encoding gradient in different orientations, parallel or perpendicular to the flow direction. In vitro flow rates were compared with timed volumetric collection. In the left-ventricle phantom and in vivo, voxel-based speed and spatio-temporal median speed were compared between sequences, as well as mitral and aortic transvalvular net forward volume. Results: In steady-flow phantoms, the flow rate error was largest (12%) for high velocity (>2 m/s) with 4DEPI readout gradient parallel to the flow. Voxel-based speed and median speed in the left-ventricle phantom were ≤5.5% different between sequences. In vivo, mean net forward volume inconsistency was largest (6.4 ± 8.5%) for 4DEPI with nonblip phase-encoding gradient parallel to the main flow. The difference in median speed for 4DEPI versus 4DGRE was largest (9%) when the 4DEPI readout gradient was parallel to the flow. Conclusions: Velocity and flow rate are inaccurate for 4DEPI with EPI factor 5 when flow is parallel to the readout or blip phase-encoding gradient. However, mean differences in flow rate, voxel-based speed, and spatio-temporal median speed were acceptable (≤10%) when comparing 4DEPI to 4DGRE for intracardiac flow in healthy volunteers.

In this study, we analyzed turbulent flows through a phantom (a 180^∘ bend with narrowing) at peak systole and a patient-specific coarctation of the aorta (CoA), with a pulsating flow, using magnetic resonance imaging (MRI) and computational fluid dynamics (CFD). For MRI, a 4D-flow MRI is performed using a 3T scanner. For CFD, the standard k- ϵ, shear stress transport k- ω, and Reynolds stress (RSM) models are applied. A good agreement between measured and simulated velocity is obtained for the phantom, especially for CFD with RSM. The wall shear stress (WSS) shows significant differences between CFD and MRI in absolute values, due to the limited near-wall resolution of MRI. However, normalized WSS shows qualitatively very similar distributions of the local values between MRI and CFD. Finally, a direct comparison between in vivo 4D-flow MRI and CFD with the RSM turbulence model is performed in the CoA. MRI can properly identify regions with locally elevated or suppressed WSS. If the exact values of the WSS are necessary, CFD is the preferred method. For future applications, we recommend the use of the combined MRI/CFD method for analysis and evaluation of the local flow patterns and WSS in the aorta.

Mitral valve (MV) leaflets affect the formation, growth, and decay of vortices in the left ventricle (LV) during diastolic filling. The shape and motion of MV leaflets are simplified in most studies due to computational restrictions. In this study, we present a newly developed mathematical method to model the dynamic movement of valve leaflets and annulus, which is based on in vivo data obtained with magnetic resonance imaging (MRI). In the present method, we solve a boundary value problem where the MV surface is initially unknown. The resultant MV shapes are included in a dynamic motion model of the LV to assess the change of intraventricular flow patterns. To estimate the effects of the MV on left intraventricular flow, a LV model without MV leaflets was also simulated for comparison. Our study showed that the presence of the MV and the shape of its leaflets significantly altered the formation and evolution of vortex structures in the LV. The various MV leaflet shapes accelerate the transvalvular flow distinctly, leading to different formation and development of vortex structures.

Left ventricular flow is intrinsically complex, three-dimensional and unsteady. Its features are susceptible to cardiovascular pathology and treatment, in particular to surgical interventions involving the valves (mitral valve replacement). To improve our understanding of intraventricular fluid mechanics and the impact of various types of prosthetic valves thereon, we have developed a custom-designed versatile left ventricular phantom with anatomically realistic moving left ventricular membrane. A biological, a tilting disc and a bileaflet valve (in two different orientations) were mounted in the mitral position and tested under the same settings. To investigate 3D flow within the phantom, a four-view tomographic particle image velocimetry setup has been implemented. The results compare side-by-side the evolution of the 3D flow topology, vortical structures and kinetic energy in the left ventricle domain during the cardiac cycle. Except for the tilting disc valve, all tested prosthetic valves induced a crossed flow path, where the outflow crosses the inflow path, passing under the mitral valve. The biological valve shows a strong jet with a peak velocity about twice as high compared to all mechanical heart valves, which makes it easier to penetrate deeply into the cavity. Accordingly, the peak kinetic energy in the left ventricle in case of the biological valve is about four times higher than the mechanical heart valves. We conclude that the tomographic particle imaging velocimetry setup provides a useful ground truth measurement of flow features and allows a comparison of the effects of different valve types on left ventricular flow patterns.

Background: Aortic pulse wave velocity (PWV) is an indicator of aortic stiffness and is used as a predictor of adverse cardiovascular events. PWV can be non-invasively assessed using magnetic resonance imaging (MRI). PWV computation requires two components, the length of the aortic arch and the time taken for the systolic pressure wave to travel through the aortic arch. The aortic length is calculated using a multi-slice 3D scan and the transit time is computed using a 2D velocity encoded MRI (VE) scan. In this study we present and evaluate an automatic method to quantify the aortic pulse wave velocity using a large population-based cohort. Methods: For this study 212 subjects were retrospectively selected from a large multi-center heart-brain connection cohort. For each subject a multi-slice 3D scan of the aorta was acquired in an oblique-sagittal plane and a 2D VE scan acquired in a transverse plane cutting through the proximal ascending and descending aorta. PWV was calculated in three stages: (i) a multi-atlas-based segmentation method was developed to segment the aortic arch from the multi-slice 3D scan and subsequently estimate the length of the proximal aorta, (ii) an algorithm that delineates the proximal ascending and descending aorta from the time-resolved 2D VE scan and subsequently obtains the velocity-time flow curves was also developed, and (iii) automatic methods that can compute the transit time from the velocity-time flow curves were implemented and investigated. Finally the PWV was obtained by combining the aortic length and the transit time. Results: Quantitative evaluation with respect to the length of the aortic arch as well as the computed PWV were performend by comparing the results of the novel automatic method to those obtained manually. The mean absolute difference in aortic length obtained automatically as compared to those obtained manually was 3.3 ± 2.8 mm (p < 0.05), the manual inter-observer variability on a subset of 45 scans was 3.4 ± 3.4 mm (p = 0.49). Bland-Altman analysis between the automataic method and the manual methods showed a bias of 0.0 (-5.0,5.0) m/s for the foot-to-foot approach, -0.1 (-1.2, 1.1) and -0.2 (-2.6, 2.1) m/s for the half-max and the cross-correlation methods, respectively. Conclusion: We proposed and evaluated a fully automatic method to calculate the PWV on a large set of multi-center MRI scans. It was observed that the overall results obtained had very good agreement with manual analysis. Our proposed automatic method would be very beneficial for large population based studies, where manual analysis requires a lot of manpower.

Purpose: To study the feasibility of high-frame-rate (HFR) contrast material-enhanced (CE) ultrasound particle image velocimetry (PIV), or echo PIV, in the abdominal aorta. Materials and Methods: Fifteen healthy participants (six men; median age, 23 years [age range, 18-34 years]; median body mass index, 20.3 kg/m² [range, 17.3-24.9 kg/m²]) underwent HFR CE US. US microbubbles were injected at incremental doses (0.25, 0.5, 0.75, and 1.5 mL), with each dose followed by US measurement to determine the optimal dosage. Different US mechanical index values were evaluated (0.09, 0.06, 0.03, and 0.01) in a diverging wave acquisition scheme. PIV analysis was performed via pairwise cross-correlation of all captured images. Participants also underwent phase-contrast MRI. The echo PIV and phase-contrast MRI velocity profiles were compared via calculation of similarity index and relative difference in peak velocity. Results: Visualization of the aortic bifurcation with HFR CE US was successful in all participants. Optimal echo PIV results were achieved with the lowest contrast agent dose of 0.25 mL in combination with the lowest mechanical indexes (0.01 or 0.03). Substantial bubble destruction occurred at higher mechanical indexes (>0.06). Flow patterns were qualitatively similar in the echo PIV and MR images. The echo PIV and MRI velocity profiles showed good agreement (similarity index, 0.98 and 0.99; difference in peak velocity, 8.5% and 17.0% in temporal and spatial profiles, respectively). Conclusion: Quantification of blood ow in the human abdominal aorta with US particle image velocimetry (echo PIV) is feasible. Use of echo PIV has potential in the clinical evaluation of aortic disease.