Background The global effect of chronic pulmonary regurgitation (PR) on right ventricular (RV) dilation and dysfunction in repaired Tetralogy of Fallot (rTOF) patients is well studied by cardiovascular magnetic resonance (CMR). However, the links between PR in the RV outflow tract (RVOT), RV dysfunction and exercise intolerance are not clarified by conventional measurements. Not all patients with RV dilation share the same intracardiac flow characteristics, now measurable by time resolved three-dimensional phase contrast imaging (4D flow). In our study, we quantified regional vorticity and energy loss in rTOF patients and correlated these parameters with RV dysfunction and exercise capacity. Methods rTOF patients with 4D flow datasets were retrospectively analyzed, including those with transannular/infundibular repair and conduit repair. Normal controls and RV dilation patients with atrial-level shunts (Qp:Qs > 1.2:1) were included for comparison. 4D flow was post-processed using IT Flow (Cardioflow, Japan). Systolic/diastolic vorticity (ω, 1/s) and viscous energy loss (VEL, mW) in the RVOT and RV inflow were measured. To characterize the relative influence of diastolic vorticity in the two regions, an RV Diastolic Vorticity Quotient (ωRVOT-Diastole/ωRV Inflow-Diastole, RV-DVQ) was calculated. Additionally, RVOT Vorticity Quotient (ωRVOT-Diastole/ωRVOT-Systole, RVOT-VQ) and RVOT Energy Quotient (VELRVOT-Diastole/VELRVOT-Systole, RVOT-EQ) was calculated. In rTOF, measurements were correlated against conventional CMR and exercise stress test results. Results 58 rTOF patients, 28 RV dilation patients and 12 controls were included. RV-DVQ, RVOT-VQ, and RVOT-EQ were highest in rTOF patients with severe PR compared to rTOF patients with non-severe PR, RV dilation and controls (p < 0.001). RV-DVQ positively correlated with RV end-diastolic volume (0.683, p < 0.001), PR fraction (0.774, p < 0.001) and negatively with RV ejection fraction (− 0.521, p = 0.003). Both RVOT-VQ, RVOT-EQ negatively correlated with VO2-max (− 0.587, p = 0.008 and − 0.617, p = 0.005) and % predicted VO2-max (− 0.678, p = 0.016 and − 0.690, p = 0.001). Conclusions In rTOF patients, vorticity and energy loss dominate the RVOT compared to tricuspid inflow, correlating with RV dysfunction and exercise intolerance. These 4D flow-based measurements may be sensitive biomarkers to guide surgical management of rTOF patients.

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Background: Postoperative outcomes of the Fontan operation have been linked to geometry of the cavopulmonary pathway, including graft shape after implantation. Computational fluid dynamics (CFD) simulations are used to explore different surgical options. The objective of this study is to perform a systematic in vitro validation for investigating the accuracy and efficiency of CFD simulation to predict Fontan hemodynamics. Methods: CFD simulations were performed to measure indexed power loss (iPL) and hepatic flow distribution (HFD) in 10 patient-specific Fontan models, with varying mesh and numerical solvers. The results were compared with a novel in vitro flow loop setup with 3D printed Fontan models. A high-resolution differential pressure sensor was used to measure the pressure drop for validating iPL predictions. Microparticles with particle filtering system were used to measure HFD. The computational time was measured for a representative Fontan model with different mesh sizes and numerical solvers. Results: When compared to in vitro setup, variations in CFD mesh sizes had significant effect on HFD ( P  =  .0002) but no significant impact on iPL ( P  =  .069). Numerical solvers had no significant impact in both iPL ( P  =  .50) and HFD ( P  =  .55). A transient solver with 0.5 mm mesh size requires computational time 100 times more than a steady solver with 2.5 mm mesh size to generate similar results. Conclusions: The predictive value of CFD for Fontan planning can be validated against an in vitro flow loop. The prediction accuracy can be affected by the mesh size, model shape complexity, and flow competition.

Background Coarctation of the aorta (CoA) is associated with decreased exercise capacity despite successful repair. Altered flow patterns have been identified due to abnormal aortic arch geometry. Our previous work demonstrated aorta size mismatch to be associated with exercise intolerance in this population. In this study, we studied aortic flow patterns during simulations of exercise in repaired CoA using 4D flow cardiovascular magnetic resonance (CMR) using aortic replicas connected to an in vitro flow pump and correlated findings with exercise stress test results to identify biomarkers of exercise intolerance. Methods Patients with CoA repair were retrospectively analyzed after CMR and exercise stress test. Each aorta was manually segmented and 3D printed. Pressure gradient measurements from ascending aorta (AAo) to descending aorta (DAo) and 4D flow CMR were performed during simulations of rest and exercise using a mock circulatory flow loop. Changes in wall shear stress (WSS) and secondary flow formation (vorticity and helicity) from rest to exercise were quantified, as well as estimated DAo Reynolds number. Parameters were correlated with percent predicted peak oxygen consumption (VO2max) and aorta size mismatch (DAAo/DDAo). Results Fifteen patients were identified (VO2max 47 to 126% predicted). Pressure gradient did not correlate with VO2max at rest or exercise. VO2max correlated positively with the change in peak vorticity (R = 0.55, p = 0.03), peak helicity (R = 0.54, p = 0.04), peak WSS in the AAo (R = 0.68, p = 0.005) and negatively with peak WSS in the DAo (R = − 0.57, p = 0.03) from rest to exercise. DAAo/DDAo correlated strongly with change in vorticity (R = − 0.38, p = 0.01), helicity (R = − 0.66, p = 0.007), and WSS in the AAo (R = − 0.73, p = 0.002) and DAo (R = 0.58, p = 0.02). Estimated DAo Reynolds number negatively correlated with VO2max for exercise (R = − 0.59, p = 0.02), but not rest (R = − 0.28, p = 0.31). Visualization of streamline patterns demonstrated more secondary flow formation in aortic arches with better exercise capacity, larger DAo, and lower Reynolds number. Conclusions There are important associations between secondary flow characteristics and exercise capacity in repaired CoA that are not captured by traditional pressure gradient, likely due to increased turbulence and inefficient flow. These 4D flow CMR parameters are a target of investigation to identify optimal aortic arch geometry and improve long term clinical outcomes after CoA repair.