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.

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.

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.