Research output: Contribution to journal › Article › peer-review
Rational choice of modelling assumptions for simulation of blood vessel end-to-side anastomosis. / Tagiltsev, Igor I.; Parshin, Daniil V.; Shutov, Alexey V.
In: Mathematical Modelling of Natural Phenomena, Vol. 17, 20, 2022.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Rational choice of modelling assumptions for simulation of blood vessel end-to-side anastomosis
AU - Tagiltsev, Igor I.
AU - Parshin, Daniil V.
AU - Shutov, Alexey V.
N1 - Funding Information: Acknowledgements. The reported study was funded by RFBR, project number 20-31-90068. The authors are grateful to M.B. Vasil’eva from Meshalkin National Medical Research Center (Novosibirsk, Russia) for the micro-photograph of the vessel. Publisher Copyright: © 2022 The authors. Published by EDP Sciences.
PY - 2022
Y1 - 2022
N2 - Blood vessels exhibit highly nonlinear, anisotropic behaviour with numerous mechanical interactions. Since exact modelling of all involved effects would yield a computationally prohibitive procedure, a practical clinical simulation tool needs to account for a minimum threshold of relevant factors. In this study, we analyse needed modelling assumptions for a reliable simulation of the end-to-side anastomosis. The artery wall is modelled in a geometrically exact setting as a pre-stressed fibre-reinforced composite. The study focuses on the sensitivity analysis of post-anastomosis stress fields concerning the modelling assumptions. Toward that end, a set of full-scale finite element simulations is carried out for three sensitivity cases: (i) The post-operational stresses are estimated with and without taking the residual stresses into account, (ii) Different geometries of the cut in the recipient vessel are examined, (iii) The influence of errors in material stiffness identification on the post-operational stress field is estimated. The studied cases (i)-(iii) have shown a substantial impact of the considered modelling assumptions on the predictive capabilities of the simulation. Approaches to more accurate predictions of post-operational stress distribution are outlined, and a quest for more accurate experimental procedures is made. As a by-product, the occurrence of the pseudo-aneurysm is explained.
AB - Blood vessels exhibit highly nonlinear, anisotropic behaviour with numerous mechanical interactions. Since exact modelling of all involved effects would yield a computationally prohibitive procedure, a practical clinical simulation tool needs to account for a minimum threshold of relevant factors. In this study, we analyse needed modelling assumptions for a reliable simulation of the end-to-side anastomosis. The artery wall is modelled in a geometrically exact setting as a pre-stressed fibre-reinforced composite. The study focuses on the sensitivity analysis of post-anastomosis stress fields concerning the modelling assumptions. Toward that end, a set of full-scale finite element simulations is carried out for three sensitivity cases: (i) The post-operational stresses are estimated with and without taking the residual stresses into account, (ii) Different geometries of the cut in the recipient vessel are examined, (iii) The influence of errors in material stiffness identification on the post-operational stress field is estimated. The studied cases (i)-(iii) have shown a substantial impact of the considered modelling assumptions on the predictive capabilities of the simulation. Approaches to more accurate predictions of post-operational stress distribution are outlined, and a quest for more accurate experimental procedures is made. As a by-product, the occurrence of the pseudo-aneurysm is explained.
KW - Anastomosis
KW - Anisotropic hyperelasticity
KW - Cut geometry
KW - Experimental errors
KW - Residual stress
UR - http://www.scopus.com/inward/record.url?scp=85134546207&partnerID=8YFLogxK
U2 - 10.1051/mmnp/2022022
DO - 10.1051/mmnp/2022022
M3 - Article
AN - SCOPUS:85134546207
VL - 17
JO - Mathematical Modelling of Natural Phenomena
JF - Mathematical Modelling of Natural Phenomena
SN - 0973-5348
M1 - 20
ER -
ID: 36711080