Nonlinear lumped-parameter models for blood flow simulations in networks of vessels
ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 5, pp. 1579-1627

To address the issue of computational efficiency related to the modelling of blood flow in complex networks, we derive a family of nonlinear lumped-parameter models for blood flow in compliant vessels departing from a well-established one-dimensional model. These 0D models must preserve important nonlinear properties of the original 1D model: the nonlinearity of the pressure-area relation and the pressure-dependent parameters characterizing the 0D models, the resistance R and the inductance L, defined in terms of a time-dependent cross-sectional area subject to pressure changes. We introduce suitable coupling conditions to join 0D vessels through 0D junctions and construct 0D networks preserving the original 1D network topology. The newly derived nonlinear 0D models are then applied to several arterial networks and the predicted results are compared against (i) the reference 1D results, to validate the models and assess their ability to reproduce good approximations of pressure and flow waveforms in all vessels at a much lower computational cost, measured in terms of CPU time, and (ii) the linear 0D results, to evaluate the improvement gained by including certain nonlinearities in the 0D models, in terms of agreement with the 1D results.

Reçu le :
Accepté le :
Publié le :
DOI : 10.1051/m2an/2022052
Classification : 76-10, 35L65, 65M08
Keywords: Blood flow, lumped-parameter models, nonlinearity, coupling, arterial networks
@article{M2AN_2022__56_5_1579_0,
     author = {Ghitti, Beatrice and Toro, Eleuterio Francisco and M\"uller, Lucas Omar},
     title = {Nonlinear lumped-parameter models for blood flow simulations in networks of vessels},
     journal = {ESAIM: Mathematical Modelling and Numerical Analysis },
     pages = {1579--1627},
     year = {2022},
     publisher = {EDP-Sciences},
     volume = {56},
     number = {5},
     doi = {10.1051/m2an/2022052},
     mrnumber = {4454157},
     language = {en},
     url = {https://www.numdam.org/articles/10.1051/m2an/2022052/}
}
TY  - JOUR
AU  - Ghitti, Beatrice
AU  - Toro, Eleuterio Francisco
AU  - Müller, Lucas Omar
TI  - Nonlinear lumped-parameter models for blood flow simulations in networks of vessels
JO  - ESAIM: Mathematical Modelling and Numerical Analysis 
PY  - 2022
SP  - 1579
EP  - 1627
VL  - 56
IS  - 5
PB  - EDP-Sciences
UR  - https://www.numdam.org/articles/10.1051/m2an/2022052/
DO  - 10.1051/m2an/2022052
LA  - en
ID  - M2AN_2022__56_5_1579_0
ER  - 
%0 Journal Article
%A Ghitti, Beatrice
%A Toro, Eleuterio Francisco
%A Müller, Lucas Omar
%T Nonlinear lumped-parameter models for blood flow simulations in networks of vessels
%J ESAIM: Mathematical Modelling and Numerical Analysis 
%D 2022
%P 1579-1627
%V 56
%N 5
%I EDP-Sciences
%U https://www.numdam.org/articles/10.1051/m2an/2022052/
%R 10.1051/m2an/2022052
%G en
%F M2AN_2022__56_5_1579_0
Ghitti, Beatrice; Toro, Eleuterio Francisco; Müller, Lucas Omar. Nonlinear lumped-parameter models for blood flow simulations in networks of vessels. ESAIM: Mathematical Modelling and Numerical Analysis , Tome 56 (2022) no. 5, pp. 1579-1627. doi: 10.1051/m2an/2022052

[1] J. Alastruey, K. H. Parker, J. Peiró and S. J. Sherwin, Lumped parameter outflow models for 1-D blood flow simulations: effect on pulse waves and parameter estimation. Commun. Comput. Phys. 4 (2008) 317–336. | MR

[2] D. S. Berger and J. K. J. Li, Temporal relationship between left ventricular and arterial system elastances. IEEE Trans. Biomed. Eng. 39 (1992) 404–410.

[3] J. Blacher and M. E. Safar, Large-artery stiffness, hypertension and cardiovascular risk in older patients. Nat. Clinical Pract. Cardiovasc. Med. 2 (2005) 450–455.

[4] P. J. Blanco, S. M. Watanabe, E. Dari, M. A. R. Passos and R. A. Feijóo, Blood flow distribution in an anatomically detailed arterial network model: criteria and algorithms. Biomech. Model. Mechanobiol. 13 (2014) 1303–1330.

[5] P. J. Blanco, S. Watanabe, M. Passos, P. Lemos and R. A. Feijóo, An anatomically detailed arterial network model for one-dimensional computational hemodynamics. IEEE Trans. Biomed. Eng. 62 (2015) 736–53.

[6] E. Boileau, P. Nithiarasu, P. J. Blanco, L. O. Müller, F. E. Fossan, L. R. Hellevik, W. P. Donders, W. Huberts, M. Willemet and J. Alastruey, A benchmark study of numerical schemes for one-dimensional arterial blood flow modelling. Int. J. Numer. Methods Biomed. Eng. 31 (2015). | MR

[7] A. Cappello, G. Gnudi and C. Lamberti, Identification of the three-element windkessel model incorporating a pressure-dependent compliance. Ann. Biomed. Eng. 23 (2006) 164–177.

[8] K. Cruickshank, L. Riste, S. G. Anderson, J. S. Wright, G. Dunn and R. G. Gosling, Aortic pulse-wave velocity and its relationship to mortality in diabetes and glucose intolerance. Circulation 106 (2002) 2085–2090.

[9] S. Epstein, M. Willemet, P. J. Chowienczyk and J. Alastruey, Reducing the number of parameters in 1D arterial blood flow modeling: less is more for patient-specific simulations. Am. J. Physiol. Heart Circulatory Physiol. 309 (2015) H222–H234.

[10] R. Fogliardi, M. Di Donfrancesco and R. Burattini, Comparison of linear and nonlinear formulations of the three-element windkessel model. Am. J. Physiol. Heart Circulatory Physiol. 271 (1996) H2661–H2668.

[11] L. Formaggia and A. Veneziani, Reduced and multiscale models for the human cardiovascular system. Technical report, Politecnico di Milano (October, 2015.

[12] L. Formaggia, A. Quarteroni and A. Veneziani, editors. Cardiovascular Mathematics: Modeling and Simulation of the Circulatory System. MS&A: Modeling, Simulation & Applications. Vol. 1. Springer, Milano (2009). | MR | Zbl

[13] F. E. Fossan, J. Mariscal-Harana, J. Alastruey and L. R. Hellevik, Optimization of topological complexity for one-dimensional arterial blood flow models. J. R. Soc. Interface 15 (2018) 20180546.

[14] S. Fujimoto, R. Mizuno, Y. Saito and S. Nakamura, Clinical application of wave intensity for the treatment of essential hypertension. Heart Vessels 19 (2004) 19–22.

[15] Y. C. Fung, Biomechanics: Mechanical Properties of Living Tissues, 2nd edition. Springer (1993).

[16] A. Ghigo, Reduced-Order Models for Blood Flow in Networks of Large Arteries. Ph.D thesis, Université Pierre et Marie Curie, Paris (September 2017).

[17] J. K. Hale, Ordinary Differential Equations. John Wiley & Sons, Inc. (1969). | MR | Zbl

[18] A. Harten and S. Osher, Uniformly High-order accurate nonoscillatory schemes. I. SIAM J. Numer. Anal. 24 (1987) 279–309. | MR | Zbl

[19] A. Harten, B. Engquist, S. Osher and S. R. Chakravarthy, Uniformly high order accuracy essentially non-oscillatory schemes, III. J. Comput. Phys. 71 (1987) 231–303. | MR | Zbl

[20] P. J. Hunter, Numerical simulation of arterial blood flow. Master’s thesis, The University of Auckland, Auckland (1972).

[21] J. K. J. Li, T. Cui and G.M. Drzewiecki, A nonlinear model of the arterial system incorporating a pressure-dependent compliance. IEEE Trans. Biomed. Eng. 37 (1990) 673–678.

[22] K. S. Matthys, J. Alastruey, J. Peiró, A. W. Khir, P. Segers, P. R. Verdonck, K. H. Parker and S. J. Sherwin, Pulse wave propagation in a model human arterial network: assessment of 1-D numerical simulations against in vitro measurements. J. Biomech. 40 (2007) 3476–3486.

[23] V. Milišić and A. Quarteroni, Analysis of lumped parameter models for blood flow simulations and their relation with 1D models. ESAIM: Math. Model. Numer. Anal. 38 (2004) 613–632. | MR | Zbl | Numdam

[24] M. Mirramezani and S. C. Shadden, A distributed lumped parameter model of blood flow. Ann. Biomed. Eng. 48 (2020) 2870–2886.

[25] L. O. Müller and E. F. Toro, A global multiscale mathematical model for the human circulation with emphasis on the venous system. Int. J. Numer. Methods Biomed. Eng. 30 (2014) 681–725. | MR

[26] L. O. Müller and E. F. Toro, Enhanced global mathematical model for studying cerebral venous blood flow. J. Biomech. 47 (2014) 3361–3372.

[27] J. P. Murgo, N. Westerhof, J. P. Giolma and S. A. Altobelli, Aortic input impedance in normal man: relationship to pressure wave forms. Circulation 62 (1980) 105–116.

[28] J. P. Mynard, Computer modelling and wave intensity analysis of perinatal cardiovascular function and dysfunction, Ph.D. thesis, Department of Paediatrics, The University of Melbourne (August, 2011).

[29] J. P. Mynard and J. J. Smolich, One-dimensional haemodynamic modeling and wave dynamics in the entire adult circulation. Ann. Biomed. Eng. 43 (2015) 1443–1460.

[30] S. Safaei, P. J. Blanco, L. O. Müller, F. E. Fossan, L. R. Hellevik and P. J. Hunter, Bond graph model of cerebral circulation: toward clinically feasible systemic blood flow simulations. Front. Physiol. 9 (2018) 148.

[31] K. Sagawa, R. K. Lie and J. Schaefer, Translation of Otto Frank’s paper “Die Grundform des Arteriellen Pulses” Zeitschrift für Biologie 37: 483–526 (1899). J. Mol. Cell. Cardiol. 22 (1990) 253–254.

[32] M. Saito, Y. Ikenaga, M. Matsukawa, Y. Watanabe, T. Asada and P.-Y. Lagrée, One-dimensional model for propagation of a pressure wave in a model of the human arterial network: comparison of theoretical and experimental results. J. Biomech. Eng. 133 (2011) 121005.

[33] D. A. Sánchez, Ordinary Differential Equations and Stability Theory. Dover Publications, Inc. (1968). | MR | Zbl

[34] S. J. Sherwin, V. Franke, J. Peiró and K. H. Parker, One-dimensional modelling of a vascular network in space-time variables. J. Eng. Math. 47 (2003) 217–250. | MR | Zbl

[35] Y. Shi, P. Lawford and R. Hose, Review of zero-D and 1-D models of blood flow in the cardiovascular system. BioMed. Eng. OnLine 10 (2011) 33.

[36] A. Spilimbergo, E. F. Toro and L. O. Müller, One-dimensional blood flow with discontinuous properties and transport: mathematical analysis and numerical schemes. Commun. Comput. Phys. 29 (2021) 649–697. | MR

[37] E. F. Toro, Riemann Solvers and Numerical Methods for Fluid Dynamics: A Practical Introduction, 3rd edition. Springer-Verlag, Berlin Heidelberg (2009). | MR | Zbl

[38] E. F. Toro, Brain venous haemodynamics, neurological diseases and mathematical modelling: a review. Appl. Math. Comput. 272 (2016) 542–579. | MR

[39] E. F. Toro, R. C. Millington and L. A. M. Nejad, Towards very high-order godunov schemes. In: Godunov Methods: Theory and Applications, Edited Review, edited by E. F. Toro. Kluwer Academic/Plenum Publishers (2001) 905–937. | MR | Zbl

[40] M. Ursino, A mathematical model of the carotid baroregulation in pulsating conditions. IEEE Trans. Biomed. Eng. 46 (1999) 382–392.

[41] M. Ursino and C. A. Lodi, A simple mathematical model of the interaction between intracranial pressure and cerebral hemodynamics. J. Appl. Physiol. 82 (1997) 1256–1269.

[42] M. Ursino, A. Fiorenzi and E. Belardinelli, The role of pressure pulsatility in the carotid baroreflex control: a computer simulation study. Comput. Biol. Med. 26 (1996) 297–314.

[43] B. Van Leer, On the relation between the upwind-differencing schemes of Godunov, Engquist-Osher and Roe. SIAM J. Sci. Stat. Comput. 5 (1985) 1–20. | MR | Zbl | DOI

[44] N. Xiao, J. Alastruey and C. A. Figueroa, A systematic comparison between 1-D and 3-D hemodynamics in compliant arterial models. Int. J. Numer. Methods Biomed. Eng. 30 (2014) 204–231. | MR | DOI

Cité par Sources :