In-silico Analysis of In-stent Restenosis Prediction of Stented Renal Artery
In-stent restenosis (ISR) is a common complication after renal artery stenting, and stent design may influence the formation of ISR. This study aims to predict the effect of stent design on the risk of ISR formation after renal artery stenting. Using computer-aided design, a simplified renal artery...
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| 主要な著者: | , , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Universiti Teknologi MARA (UiTM), Malaysia
2024
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| 主題: | |
| オンライン･アクセス: | http://ir.unimas.my/id/eprint/46724/1/2.JMECHE-2023-0210.pdf http://ir.unimas.my/id/eprint/46724/ https://jmeche.uitm.edu.my/browse-journals/special-issues/special-issue-2024-vol-13/ https://doi.org/10.24191/jmeche.v13i1.3754 |
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| 要約: | In-stent restenosis (ISR) is a common complication after renal artery stenting, and stent design may influence the formation of ISR. This study aims to predict the effect of stent design on the risk of ISR formation after renal artery stenting. Using computer-aided design, a simplified renal artery model was modelled and later assembled with stents similar to commercial stents. Computational Fluid Mechanics (CFD) analysis was employed to simulate the blood flow in these stented models. Stent 1 exhibited superior hemodynamic performance with minimal low Wall Shear Stress (WSS) exposure in the stented region. Additionally, the study found that the thinnest Stent 1 was the most effective in reducing the risk of ISR formation. Thus, stent strut configuration with large spacing may reduce ISR risk, with the thinnest Stent 1 design showed promising performance in mitigating ISR. Hence, it is worth further investigation. |
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