Literature DB >> 30190083

Numerical simulation of aneurysmal haemodynamics with calibrated porous-medium models of flow-diverting stents.

Yujie Li1, Mingzi Zhang1, David I Verrelli2, Winston Chong3, Makoto Ohta4, Yi Qian5.   

Abstract

Modelling flow-diverting (FD) stents as porous media (PM) markedly improves the efficiency of computational fluid dynamics (CFD) simulations in the study of intracranial aneurysm treatment. Nonetheless, the parameters of PM models adopted for simulations up until now were rarely calibrated to match the represented FD structure. We therefore sought to evaluate the PM parameters for a representative variety of commercially available stents, so characterising the flow-diversion behaviours of different FD devices on the market. We generated fully-resolved geometries for treatments using PED, Silk+, FRED, and dual PED stents. We then correspondingly derived the calibrated PM parameters-permeability (k) and inertial resistance factor (C2)-for each stent design from CFD simulations, to ensure the calibrated PM model has identical flow resistance to the FD stent it represents. With each of the calibrated PM models respectively deployed in two aneurysms, we studied the flow-diversion effects of these stent configurations. This work for the first time reported several sets of parameters for PM models, which is vital to address the current knowledge gap and rectify the errors in PM model simulations, thereby setting right the modelling protocol for future studies using PM models. The flow resistance parameters were strongly affected by porosity and effective thickness of the commercial stents, and thus accounted for in the PM models. Flow simulations using the PM stent models revealed differences in aneurysmal mass flowrate (MFR) and energy loss (EL) between various stent designs. This study improves the practicability of FD simulation by using calibrated PM models, providing an individualised method with improved simulation efficiency and accuracy.
Copyright © 2018 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Computational fluid dynamics; Flow-diverting stents; Haemodynamics; Intracranial aneurysms; Multi-stent treatment; Porous-medium model

Mesh:

Year:  2018        PMID: 30190083     DOI: 10.1016/j.jbiomech.2018.08.026

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  6 in total

1.  Leveraging Patient-Specific Simulated Angiograms to Characterize Cerebral Aneurysm Hemodynamics using Computational Fluid Dynamics.

Authors:  V Chivukula; R White; A Shields; J Davies; M Mokin; D R Bednarek; S Rudin; C Ionita
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2022-04-04

2.  Cerebral aneurysm flow diverter modeled as a thin inhomogeneous porous medium in hemodynamic simulations.

Authors:  Armin Abdehkakha; Adam L Hammond; Tatsat R Patel; Adnan H Siddiqui; Gary F Dargush; Hui Meng
Journal:  Comput Biol Med       Date:  2021-10-28       Impact factor: 6.698

3.  Computational Fluid Dynamics Using a Porous Media Setting Predicts Outcome after Flow-Diverter Treatment.

Authors:  M Beppu; M Tsuji; F Ishida; M Shirakawa; H Suzuki; S Yoshimura
Journal:  AJNR Am J Neuroradiol       Date:  2020-10-01       Impact factor: 3.825

4.  Endothelial Cell Distribution After Flow Exposure With Two Stent Struts Placed in Different Angles.

Authors:  Zi Wang; Narendra Kurnia Putra; Hitomi Anzai; Makoto Ohta
Journal:  Front Physiol       Date:  2022-01-13       Impact factor: 4.566

5.  Numerical Assessment of the Risk of Abnormal Endothelialization for Diverter Devices: Clinical Data Driven Numerical Study.

Authors:  Denis Tikhvinskii; Julia Kuianova; Dmitrii Kislitsin; Kirill Orlov; Anton Gorbatykh; Daniil Parshin
Journal:  J Pers Med       Date:  2022-04-18

6.  Implementation of computer simulation to assess flow diversion treatment outcomes: systematic review and meta-analysis.

Authors:  Mingzi Zhang; Simon Tupin; Hitomi Anzai; Yutaro Kohata; Masaaki Shojima; Kosuke Suzuki; Yoshihiro Okamoto; Katsuhiro Tanaka; Takanobu Yagi; Soichiro Fujimura; Makoto Ohta
Journal:  J Neurointerv Surg       Date:  2020-10-23       Impact factor: 5.836

  6 in total

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