Abstract
A procedure for the treatment of tricuspid regurgitation through membrane insertion has been developed recently. However, membrane optimization is required to balance treatment effectiveness with valve damage. This optimization must be performed based on hemodynamic analyses, using the computational fluid dynamics method. The objectives of this study were to analyze hemodynamic features and provide guidelines for the patient-specific optimization of membranes. We used the lattice Boltzmann method for the base blood flow solver and the immersed boundary method to analyze the interactions among the membrane, leaflet, and blood flow. Optimization was performed by the membrane’s volume and insertion angle, and the effects of the shape and surface contact angle of the membrane were observed. Among various patient-specific features, the annulus ratio, hematocrit, and age were selected as control variables. Hemodynamic features were classified as features related to treatment effectiveness, including the regurgitant volume, jet area, and pressure gradient, and those related to the valve leaflet thickening risk, including the Reynolds shear stress, turbulent kinetic energy, and vorticity magnitude. Our analysis results revealed that treatment effectiveness and leaflet damage have a tradeoff relationship; nevertheless, optimizing certain features such as the membrane shape or surface treatment can reduce damage.
Original language | English |
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Pages (from-to) | 1587-1600 |
Number of pages | 14 |
Journal | Engineering Applications of Computational Fluid Mechanics |
Volume | 16 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2022 |
Bibliographical note
Funding Information:This work was supported by Korea Medical Device Development Fund: [Grant Number KMDF_PR_20200901_0104, 9991007267], and supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A5A1022977). This work was supported by the Korea Medical Device Development Fund grant funded by the Korea government (The Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (KMDF_PR_20200901_0104, 9991007267), and supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A5A1022977).
Funding Information:
This work was supported by the Korea Medical Device Development Fund grant funded by the Korea government (The Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, the Ministry of Food and Drug Safety) (KMDF_PR_20200901_0104, 9991007267), and supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2022R1A5A1022977).
Publisher Copyright:
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
All Science Journal Classification (ASJC) codes
- Computer Science(all)
- Modelling and Simulation