OBJECTIVES: Adequacy of 16-20mm extracardiac conduits for adolescent Fontan patients remains unknown. This study aims to evaluate conduit adequacy using the inferior vena cava (IVC)-conduit velocity mismatch factor along the respiratory cycle. METHODS: Real-time 2D flow MRI was prospectively acquired in 50 extracardiac (16-20mm conduits) Fontan patients (mean age 16.9 ± 4.5 years) at the subhepatic IVC, conduit and superior vena cava. Hepatic venous flow was determined by subtracting IVC flow from conduit flow. The cross-sectional area (CSA) was reported for each vessel. Mean flow and velocity was calculated during the average respiratory cycle, inspiration and expiration. The IVC-conduit velocity mismatch factor was determined as follows: Vconduit/VIVC, where V is the mean velocity. RESULTS: Median conduit CSA and IVC CSA were 221 mm2 (Q1-Q3 201-255) and 244 mm2 (Q1-Q3 203-265), respectively. From the IVC towards the conduit, flow rates increased significantly due to the entry of hepatic venous flow (IVC 1.9, Q1-Q3 1.5-2.2) versus conduit (3.3, Q1-Q3 2.5-4.0 l/min, P < 0.001). Consequently, mean velocity significantly increased (IVC 12 (Q1-Q3 11-14 cm/s) versus conduit 25 (Q1-Q3 17-31 cm/s), P < 0.001), resulting in a median IVC-conduit velocity mismatch of 1.8 (Q1-Q3 1.5-2.4), further augmenting during inspiration (median 2.3, Q1-Q3 1.8-3.0). IVC-conduit mismatch was inversely related to measured conduit size and positively correlated with conduit flow. The normalized IVC-conduit velocity mismatch factor during expiration and the entire respiratory cycle correlated with peak VO2 (r = -0.37, P = 0.014 and r = -0.31, P = 0.04, respectively). CONCLUSIONS: Important blood flow accelerations are observed from the IVC towards the conduit in adolescent Fontan patients, which is related to peak VO2. This study, therefore, raises concerns that implanted 16-20mm conduits have become undersized for older Fontan patients and future studies should clarify its effect on long-term outcome.

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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.

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Background: The Fontan procedure is the last of three stages of congenital heart surgery to treat children born with a single ventricle heart defect. In these patients, a balanced hepatic blood flow distribution (HFD) towards both lungs is important, since a lack of “hepatic factor” has been associated with the formation of pulmonary arteriovenous malformations (PAVMs). With imaging modalities and computational fluid dynamics (CFD), the hepatic blood flow distribution can be studied. Recent CFD studies indirectly quantify HFD to both lungs by tracking ‘hepatic flow’ particles that are uniformly seeded in the Fontan tunnel and analyzing the distribution of these particles towards both lungs (conventional approach). However, this approach is based on the unvalidated assumption that there is a uniform distribution of hepatic blood flow in the Fontan tunnel. Aside from CFD modeling, previous clinical imaging studies showed that respiration has a tremendous impact on the hepatic blood flow in Fontan patients; however, these studies only used Doppler Ultrasound because the resolution of real-time phase-contrast magnetic imaging resonance (PC-MRI) is not yet good enough for direct hepatic flow quantification. Objectives: this study aimed to investigate the distribution of hepatic blood flow in the Fontan tunnel using CFD simulations. Another objective was to quantify the HFD towards both lungs using particle tracking directly from the inlets of the hepatic veins (novel approach) and compare these HFD results to the conventional approach. Furthermore, we performed an in-depth flow analysis and developed a new method to indirectly quantify the hepatic flow in the hepatic veins and the respiratory effects on it using real-time PC-MRI. Methods: Unsteady CFD modeling was used to assess the mixing of hepatic blood flow within the Fontan tunnel and the different HFD quantification methods. Therefore, we created three-dimensional reconstructions of the patient-derived Fontan anatomies based on MRI imaging that included the geometry of the hepatic veins in the computational fluid domain. We created two types of CFD models: 1. CFD models that only included the cardiac effects on blood flow, and 2. CFD models that considered both the cardiac and respiratory effects on blood flow. For the in-depth flow analysis using real-time PC-MRI, we first measured the blood flow in the Fontan tunnel, just above the entrance of the hepatic veins. Second, we derived the IVC blood flow below the hepatic veins. By subtracting these flows, we indirectly quantified the hepatic blood flow. Results and conclusion: The main findings were that hepatic blood flow was non-uniformly distributed within the Fontan tunnel and substantial differences in HFD between the conventional approach and novel approach were found in both types of CFD models that either ignored or considered respiration. Additionally, we showed that it was feasible to indirectly measure hepatic blood flow in Fontan patients while using real-time PC-MRI. These derived flow parameters extracted from real-time PC-MRI acquisitions confirmed what previously has been described that the hepatic blood flow in Fontan patients was heavily influenced by respiration.