Applicability assessment of a stent-retriever thrombectomy finite-element model

An acute ischaemic stroke appears when a blood clot blocks the blood flow in a cerebral artery. Intra-arterial thrombectomy, a mini-invasive procedure based on stent technology, is a mechanical available treatment to extract the clot and restore the blood circulation. After stent deployment, the clo...

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Veröffentlicht in:Interface focus 2021-02, Vol.11 (1), p.20190123-20190123
Hauptverfasser: Luraghi, Giulia, Rodriguez Matas, Jose Felix, Dubini, Gabriele, Berti, Francesca, Bridio, Sara, Duffy, Sharon, Dwivedi, Anushree, McCarthy, Ray, Fereidoonnezhad, Behrooz, McGarry, Patrick, Majoie, Charles B L M, Migliavacca, Francesco
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Sprache:eng
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Zusammenfassung:An acute ischaemic stroke appears when a blood clot blocks the blood flow in a cerebral artery. Intra-arterial thrombectomy, a mini-invasive procedure based on stent technology, is a mechanical available treatment to extract the clot and restore the blood circulation. After stent deployment, the clot, trapped in the stent struts, is pulled along with the stent towards a receiving catheter. Recent clinical trials have confirmed the effectiveness and safety of mechanical thrombectomy. However, the procedure requires further investigation. The aim of this study is the development of a numerical finite-element-based model of the thrombectomy procedure. thrombectomy tests are performed in different vessel geometries and one simulation for each test is carried out to verify the accuracy and reliability of the proposed numerical model. The results of the simulations confirm the efficacy of the model to replicate all the experimental setups. Clot stress and strain fields from the numerical analysis, which vary depending on the geometric features of the vessel, could be used to evaluate the possible fragmentation of the clot during the procedure. The proposed / comparison aims at assessing the applicability of the numerical model and at providing validation evidence for the specific thrombectomy outcomes prediction.
ISSN:2042-8898
2042-8901
DOI:10.1098/rsfs.2019.0123