scholarly journals Bioprosthetic Valve Size Selection to Optimize Aortic Valve Replacement Surgical Outcome: A Fluid-Structure Interaction Modeling Study

2021 ◽  
Vol 127 (1) ◽  
pp. 159-174
Author(s):  
Caili Li ◽  
Dalin Tang ◽  
Jing Yao ◽  
Christopher Baird ◽  
Haoliang Sun ◽  
...  
2018 ◽  
Vol 140 (12) ◽  
Author(s):  
Ram P. Ghosh ◽  
Gil Marom ◽  
Oren M. Rotman ◽  
Marvin J. Slepian ◽  
Saurabh Prabhakar ◽  
...  

Transcatheter aortic valve replacement (TAVR) has emerged as an effective alternative to conventional surgical aortic valve replacement (SAVR) in high-risk elderly patients with calcified aortic valve disease. All currently food and drug administration approved TAVR devices use tissue valves that were adapted to but not specifically designed for TAVR use. Emerging clinical evidence indicates that these valves may get damaged during crimping and deployment—leading to valvular calcification, thrombotic complications, and limited durability. This impedes the expected expansion of TAVR to lower-risk and younger patients. Viable polymeric valves have the potential to overcome such limitations. We have developed a polymeric SAVR valve, which was optimized to reduce leaflet stresses and offer a thromboresistance profile similar to that of a tissue valve. This study compares the polymeric SAVR valve's hemodynamic performance and mechanical stresses to a new version of the valve—specifically designed for TAVR. Fluid–structure interaction (FSI) models were utilized and the valves' hemodynamics, flexural stresses, strains, orifice area, and wall shear stresses (WSS) were compared. The TAVR valve had 42% larger opening area and 27% higher flow rate versus the SAVR valve, while WSS distribution and mechanical stress magnitudes were of the same order, demonstrating the enhanced performance of the TAVR valve prototype. The TAVR valve FSI simulation and Vivitro pulse duplicator experiments were compared in terms of the leaflets' kinematics and the effective orifice area. The numerical methodology presented can be further used as a predictive tool for valve design optimization for enhanced hemodynamics and durability.


Perfusion ◽  
2021 ◽  
pp. 026765912199854
Author(s):  
Mohammad Javad Ghasemi Pour ◽  
Kamran Hassani ◽  
Morteza Khayat ◽  
Shahram Etemadi Haghighi

Background and objectives: Fluid structure interaction (FSI) is defined as interaction of the structures with contacting fluids. The aortic valve experiences the interaction with blood flow in systolic phase. In this study, we have tried to predict the hemodynamics of blood flow through a normal and stenotic aortic valve in two relaxation and exercise conditions using a three-dimensional FSI method. Methods: The aorta valve was modeled as a three-dimensional geometry including a normal model and two others with 25% and 50% stenosis. The geometry of the aortic valve was extracted from CT images and the models were generated by MMIMCS software and then they were implemented in ANSYS software. The pulsatile flow rate was used for all cases and the numerical simulations were conducted based on a time-dependent domain. Results: The obtained results including the velocity, pressure, and shear stress contours in different systolic time sequences were explained and discussed. The maximum blood flow velocity in relaxation phase was obtained 1.62 m/s (normal valve), 3.78 m/s (25% stenosed valve), and 4.73 m/s (50% stenosed valve). In exercise condition, the maximum velocities are 2.86, 4.32, and 5.42 m/s respectively. The maximum blood pressure in relaxation phase was calculated 111.45 mmHg (normal), 148.66 mmHg (25% stenosed), and 164.21 mmHg (50% stenosed). However, the calculated values in exercise situation were 129.57, 163.58, and 191.26 mmHg. The validation of the predicted results was also conducted using existing literature. Conclusions: We believe that such model are useful tools for biomechanical experts. The further studies should be done using experimental data and the data are implemented on the boundary conditions for better comparison of the results.


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