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.

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.

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.