Multi-Modal in Vitro Experiments Mimicking the Flow Through a Mitral Heart Valve Phantom.

PURPOSE: Fluid-structure interaction (FSI) models are more commonly applied in medical research as computational power is increasing. However, understanding the accuracy of FSI models is crucial, especially in the context of heart valve disease in patient-specific models. Therefore, this study aimed to create a multi-modal benchmarking data set for cardiac-inspired FSI models, based on clinically important parameters, such as the pressure, velocity, and valve opening, with an in vitro phantom setup. METHOD: An in vitro setup was developed with a 3D-printed phantom mimicking the left heart, including a deforming mitral valve. A range of pulsatile flows were created with a computer-controlled motor-and-pump setup. Catheter pressure measurements, magnetic resonance imaging (MRI), and echocardiography (Echo) imaging were used to measure pressure and velocity in the domain. Furthermore, the valve opening was quantified based on cine MRI and Echo images. RESULT: The experimental setup, with 0.5% cycle-to-cycle variation, was successfully built and six different flow cases were investigated. Higher velocity through the mitral valve was observed for increased cardiac output. The pressure difference across the valve also followed this trend. The flow in the phantom was qualitatively assessed by the velocity profile in the ventricle and by streamlines obtained from 4D phase-contrast MRI. CONCLUSION: A multi-modal set of data for validation of FSI models has been created, based on parameters relevant for diagnosis of heart valve disease. All data is publicly available for future development of computational heart valve models.

Unravelling the mechanisms of CE-SSFP in imaging myocardium at risk: The effect of relaxation times on myocardial contrast.

PURPOSE: The aim of this study was to investigate the contrast mechanisms of Contrast-enhanced steady-state free-precession (CE-SSFP) through the utilization of Bloch simulations in an experimental porcine model and in patients with acute myocardial infarction. METHODS: Six pigs and ten patients with myocardial infarction underwent CMR and tissue characterization at 1.5 T whereas a Bloch simulation framework was utilized to simulate the CE-SSFP signal formation and compare it against the actual CE-SSFP signal acquired from the experimental porcine model and the patient population. The relaxation times of remote, salvaged, and infarcted myocardium were calculated after the injection of gadolinium, at the time of CE-SSFP acquisition. Simulations were performed using the same CE-SSFP pulse sequence as used on the scanner on a set of spins with the calculated relaxation times from the CMR scans. RESULTS: The normalized signal intensities of salvaged and infarcted myocardium obtained with simulations were lower than the corresponding normalized signal intensities obtained in vivo in pigs (p < 0.05, 134% vs 153%) and in patients (p < 0.05, 126% vs 145%). The results from simulations showed a linear relationship to the results obtained in the experimental porcine model (r2 = 0.61) and in patients (r2 = 0.69). CONCLUSION: The T1 and T2 values of remote, salvaged, and infarcted myocardium only partly explain the signal intensities in CE-SSFP images. Bloch simulations suggest that there may be more elements that contribute to the CE-SSFP contrast. Integration of other aspects of the MR experiment into the simulation model could further help to fully unravel the mechanisms of CE-SSFP.

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.