Evaluating the Haemodynamic Performance of Endografts for Complex Aortic Arch Repair.

branched stent-graft computational fluid dynamics haemodynamic thoracic endovascular aortic repair

Journal

Bioengineering (Basel, Switzerland)
ISSN: 2306-5354
Titre abrégé: Bioengineering (Basel)
Pays: Switzerland
ID NLM: 101676056

Informations de publication

Date de publication:
18 Oct 2022
Historique:
received: 07 09 2022
revised: 09 10 2022
accepted: 12 10 2022
entrez: 27 10 2022
pubmed: 28 10 2022
medline: 28 10 2022
Statut: epublish

Résumé

Thoracic endovascular aortic repair (TEVAR) of aortic aneurysms and dissections involving the arch has evolved over the last two decades. Compared to conventional surgical methods, endovascular repair offers a less invasive treatment option with lower risk and faster recovery. Endografts used in TEVAR vary in design depending on the procedure and application. Novel endografts (e.g., branched stent-graft) were developed to ensure perfusion of blood to the supra-aortic vessels, but their haemodynamic performance and long-term durability have not been adequately studied. This review focuses on the use of computational modelling to study haemodynamics in commercially available endografts designed for complex aortic arch repair. First, we summarise the currently adopted workflow for computational fluid dynamics (CFD) modelling, including geometry reconstruction, boundary conditions, flow models, and haemodynamic metrics of interest. This is followed by a review of recently (2010-present) published CFD studies on complex aortic arch repair, using both idealized and patient-specific models. Finally, we introduce some of the promising techniques that can be potentially applied to predict post-operative outcomes.

Identifiants

pubmed: 36290541
pii: bioengineering9100573
doi: 10.3390/bioengineering9100573
pmc: PMC9598215
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Subventions

Organisme : Engineering and Physical Sciences Research Council
ID : EP/R513052/1

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Auteurs

Sampad Sengupta (S)

Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.

Yu Zhu (Y)

Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.

Mohamad Hamady (M)

Department of Surgery & Cancer, Imperial College London, St. Mary's Campus, London W2 1NY, UK.

Xiao Yun Xu (XY)

Department of Chemical Engineering, Imperial College London, South Kensington Campus, London SW7 2AZ, UK.

Classifications MeSH