Validation of fluid-structure interaction simulations of the opening phase of phantom mitral heart valves under physiologically inspired conditions.

BACKGROUND AND OBJECTIVE: Atrioventricular valve disease is a common cause of heart failure, and successful surgical or interventional outcomes are crucial. Patient-specific fluid-structure interaction (FSI) modeling may provide valuable insights into valve dynamics and guidance of valve repair strategies. However, lack of validation has kept FSI modeling from clinical implementation. Therefore, this study aims to validate FSI simulations against in vitro benchmarking data, based on clinically relevant parameters for evaluating heart valve disease. METHODS: An FSI model that mimics the left heart was developed. The domain included a deformable mitral valve of different stiffnesses run with different inlet velocities. Five different cases were simulated and compared to in vitro data based on the pressure difference across the valve, the valve opening, and the velocity in the flow domain. RESULTS: The simulations underestimate the pressure difference across the valve by 6.8-14 % compared to catheter measurements. Evaluation of the valve opening showed an underprediction of 5.4-7.3 % when compared to cine MRI, 2D Echo, and 3D Echo data. Additionally, the simulated velocity through the valve showed a 7.9-8.4 % underprediction in relation to Doppler Echo measurements. Qualitative assessment of the velocity profile in the ventricle and the streamlines of the flow in the domain showed good agreement of the flow behavior. CONCLUSIONS: Parameters relevant to the diagnosis of heart valve disease estimated by FSI simulations showed good agreement when compared to in vitro benchmarking data, with differences small enough not to affect the grading of heart valve disease. The FSI model is thus deemed good enough for further development toward patient-specific cases.

In vivo hepatic flow distribution by computational fluid dynamics can predict pulmonary flow distribution in patients with Fontan circulation.

In Fontan patients, a lung deprived of hepatic blood may develop pulmonary arterio-venous malformations (PAVMs) resulting in shunting, reduced pulmonary vascular resistance (PVR) and decreased oxygenation. To provide guidance for corrective invasive interventions, we aimed to non-invasively determine how the hepatic to pulmonary blood flow balance correlates with pulmonary flow, PVR, and with oxygen saturation. Magnetic resonance imaging (MRI) data from eighteen Fontan patients (eight females, age 3-14 years) was used to construct patient-specific computational fluid dynamics (CFD) models to calculate the hepatic to pulmonary blood flow. This was correlated with pulmonary vein flow, simulated PVR and oxygen saturation. Clinical applicability of the findings was demonstrated with an interventional patient case. The hepatic to pulmonary blood flow balance correlated with right/left pulmonary vein flow (R2 = 0.50), left/right simulated PVR (R2 = 0.47), and oxygen saturation at rest (R2 = 0.56). In the interventional patient, CFD predictions agreed with post-interventional MRI measurements and with regressions in the cohort. The balance of hepatic blood to the lungs has a continuous effect on PVR and oxygen saturation, even without PAVM diagnosis. MRI combined with CFD may help in planning of surgical and interventional designs affecting the hepatic to pulmonary blood flow balance in Fontan patients.

Comparison of 2D and 4D Flow MRI in Neonates Without General Anesthesia.

BACKGROUND: Neonates with critical congenital heart disease require early intervention. Four-dimensional (4D) flow may facilitate surgical planning and improve outcome, but accuracy and precision in neonates are unknown. PURPOSE: To 1) validate two-dimensional (2D) and 4D flow MRI in a phantom and investigate the effect of spatial and temporal resolution; 2) investigate accuracy and precision of 4D flow and internal consistency of 2D and 4D flow in neonates; and 3) compare scan time of 4D flow to multiple 2D flows. STUDY TYPE: Phantom and prospective patients. POPULATION: A total of 17 neonates with surgically corrected aortic coarctation (age 18 days [IQR 11-20]) and a three-dimensional printed neonatal aorta phantom. FIELD STRENGTH/SEQUENCE: 1.5T, 2D flow and 4D flow. ASSESSMENT: In the phantom, 2D and 4D flow volumes (ascending and descending aorta, and aortic arch vessels) with different resolutions were compared to high-resolution reference 2D flow. In neonates, 4D flow was compared to 2D flow volumes at each vessel. Internal consistency was computed as the flow volume in the ascending aorta minus the sum of flow volumes in the aortic arch vessels and descending aorta, divided by ascending aortic flow. STATISTICAL TESTS: Bland-Altman plots, Pearson correlation coefficient (r), and Student's t-tests. RESULTS: In the phantom, 2D flow differed by 0.01 ± 0.02 liter/min with 1.5 mm spatial resolution and -0.01 ± 0.02 liter/min with 0.8 mm resolution; 4D flow differed by -0.05 ± 0.02 liter/min with 2.4 mm spatial and 42 msec temporal resolution, -0.01 ± 0.02 liter/min with 1.5 mm, 42 msec resolution and -0.01 ± 0.02 liter/min with 1.5 mm, 21 msec resolution. In patients, 4D flow and 2D flow differed by -0.06 ± 0.08 liter/min. Internal consistency in patients was -11% ± 17% for 2D flow and 5% ± 13% for 4D flow. Scan time was 17.1 minutes [IQR 15.5-18.5] for 2D flow and 6.2 minutes [IQR 5.3-6.9] for 4D flow, P < 0.0001. DATA CONCLUSION: Neonatal 4D flow MRI is time efficient and can be acquired with good internal consistency without contrast agents or general anesthesia, thus potentially expanding 4D flow use to the youngest and smallest patients. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

Computational Fluid Dynamics Support for Fontan Planning in Minutes, Not Hours: The Next Step in Clinical Pre-Interventional Simulations.

Computational fluid dynamics (CFD) modeling may aid in planning of invasive interventions in Fontan patients. Clinical application of current CFD techniques is however limited by complexity and long computation times. Therefore, we validated a "lean" CFD method to magnetic resonance imaging (MRI) and an "established" CFD method, ultimately aiming to reduce complexity to enable predictive CFD during ongoing interventions. Fifteen Fontan patients underwent MRI for CFD modeling. The differences between lean and established approach, in hepatic and total flow percentage to the left pulmonary artery (%LPA), power loss and relative wall shear stress area were 1.5 ± 4.0%, -0.17 ± 1.1%, -0.055 ± 0.092 mW and 1.1 ± 1.4%. Compared with MRI, the lean and established method showed a bias in %LPA of -1.9 ± 3.4% and -1.8 ± 3.1%. Computation time was for the lean and established approach 3.0 ± 2.0 min and 7.0 ± 3.4 h, respectively. We conclude that the proposed lean method provides fast and reliable results for future CFD support during interventions.

Simulation of aortopulmonary collateral flow in Fontan patients for use in prediction of interventional outcomes.

PURPOSE: Patients with complex congenital heart disease may need to be converted to a Fontan circulation with systemic venous return surgically connected to the pulmonary circulation. These patients frequently form aortopulmonary collaterals (APC), that is arterial inflows to the pulmonary artery vascular tree. The aim of this study was to develop a method to calculate the effect of APC on the pulmonary flow distribution based on magnetic resonance imaging (MRI) measurements and computational fluid dynamics simulations in order to enable prediction of interventional outcomes in Fontan patients. METHODS: Patient-specific models of 11 patients were constructed in a 3D-design software based on MRI segmentations. APC flow was quantified as the difference between pulmonary venous flow and pulmonary artery flow, measured by MRI. A method was developed to include the modulating effect of the APC flow by calculating the patient-specific relative pulmonary vascular resistance. Simulations, including interventions with a Y-graft replacement and a stent dilatation, were validated against MRI results. RESULTS: The bias between simulated and MRI-measured fraction of blood to the left lung was 2·9 ± 5·3%. Including the effects of the APC flow in the simulation (n = 6) reduced simulation error from 9·8 ± 7·0% to 5·2 ± 6·3%. Preliminary findings in two patients show that the effect of surgical and catheter interventions could be predicted using the demonstrated methods. CONCLUSIONS: The work demonstrates a novel method to include APC flow in predictive simulations of Fontan hemodynamics. APC flow was found to have a significant contribution to the pulmonary flow distribution in Fontan patients.