Haemodynamic optimisation of a dialysis graft design using a global optimisation approach.

arteriovenous grafts computational fluid dynamics geometric optimisation polynomial chaos expansion sensitivity analysis

Journal

International journal for numerical methods in biomedical engineering
ISSN: 2040-7947
Titre abrégé: Int J Numer Method Biomed Eng
Pays: England
ID NLM: 101530293

Informations de publication

Date de publication:
02 2021
Historique:
received: 17 04 2020
revised: 14 10 2020
accepted: 18 11 2020
pubmed: 30 11 2020
medline: 26 11 2021
entrez: 29 11 2020
Statut: ppublish

Résumé

Disturbed flow and the resulting non-physiological wall shear stress (WSS) at the graft-vein anastomosis play an important role in arteriovenous graft (AVG) patency loss. Modifying graft geometry with helical features is a popular approach to minimise the occurrence of detrimental haemodynamics and to potentially increase graft longevity. Haemodynamic optimisation of AVGs typically requires many computationally expensive computational fluid dynamics (CFD) simulations to evaluate haemodynamic performance of different graft designs. In this study, we aimed to develop a haemodynamically optimised AVG by using an efficient meta-modelling approach. A training dataset containing CFD evaluations of 103 graft designs with helical features was used to develop computationally low-cost meta-models for haemodynamic metrics related to graft dysfunction. During optimisation, the meta-models replaced CFD simulations that were otherwise needed to evaluate the haemodynamic performance of possible graft designs. After optimisation, haemodynamic performance of the optimised graft design was verified using a CFD simulation. The obtained optimised graft design contained both a helical graft centreline and helical ridge. Using the optimised design, the magnitude of flow disturbances and the size of the anastomotic areas exposed to non-physiological WSS was successfully reduced compared to a regular straight graft. Our meta-modelling approach allowed to reduce the total number of CFD model evaluations required for our design optimisation by approximately a factor 2000. The applied efficient meta-modelling technique was successful in identifying an optimal, helical graft design at relatively low computational costs. Future studies should evaluate the in vivo benefits of the developed graft design.

Identifiants

pubmed: 33249781
doi: 10.1002/cnm.3423
pmc: PMC7900962
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

e3423

Informations de copyright

© 2020 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.

Références

Adv Chronic Kidney Dis. 2015 Nov;22(6):431-7
pubmed: 26524947
Sci Rep. 2017 May 12;7(1):1865
pubmed: 28500311
Med Biol Eng Comput. 2008 Nov;46(11):1097-112
pubmed: 19002516
PLoS One. 2016 Nov 18;11(11):e0165892
pubmed: 27861485
Int J Numer Method Biomed Eng. 2021 Feb;37(2):e3423
pubmed: 33249781
J Biomech Eng. 2016 Dec 1;138(12):
pubmed: 27636531
Cardiovasc Eng Technol. 2017 Sep;8(3):280-294
pubmed: 28527110
JAMA. 1999 Dec 1;282(21):2035-42
pubmed: 10591386
J Biomech. 2013 Jan 18;46(2):345-53
pubmed: 23159095
Comput Med Imaging Graph. 2002 Jul-Aug;26(4):227-35
pubmed: 12074917
J Vasc Access. 2016 Mar;17 Suppl 1:S85-90
pubmed: 26951913
Kidney Int. 2001 Jun;59(6):2325-34
pubmed: 11380837
J R Soc Interface. 2005 Jun 22;2(3):261-6
pubmed: 16849184
Lancet. 1991 Nov 30;338(8779):1360-1
pubmed: 1682738
J Biomech Eng. 1996 Feb;118(1):74-82
pubmed: 8833077
Am J Physiol Heart Circ Physiol. 2009 Jul;297(1):H163-70
pubmed: 19429823
Eur J Vasc Endovasc Surg. 2007 Apr;33(4):472-5
pubmed: 17161962
Circ Res. 1968 Feb;22(2):165-97
pubmed: 5639037
ASAIO J. 2009 May-Jun;55(3):192-9
pubmed: 19318918
Ann Vasc Surg. 2012 Nov;26(8):1093-9
pubmed: 22682930
J Biomech. 2012 Sep 21;45(14):2398-404
pubmed: 22854207
J R Soc Interface. 2018 Sep 26;15(146):
pubmed: 30257924

Auteurs

Sjeng Quicken (S)

Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.
Eindhoven University of Technology, Department of Biomedical Engineering, Eindhoven, Netherlands.

Tammo Delhaas (T)

Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.

Barend M E Mees (BME)

Department of Vascular Surgery, Maastricht University Medical Centre, Maastricht, the Netherlands.

Wouter Huberts (W)

Department of Biomedical Engineering, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.
Eindhoven University of Technology, Department of Biomedical Engineering, Eindhoven, Netherlands.

Articles similaires

Humans Meta-Analysis as Topic Sample Size Models, Statistical Computer Simulation
Humans Algorithms Software Artificial Intelligence Computer Simulation
Humans Robotic Surgical Procedures Clinical Competence Male Female

A computational model for bacteriophage ϕX174 gene expression.

Alexis M Hill, Tanvi A Ingle, Claus O Wilke
1.00
Gene Expression Regulation, Viral Promoter Regions, Genetic Bacteriophage phi X 174 Computer Simulation Models, Genetic

Classifications MeSH