Abstract
The 2nd CFD Challenge Predicting Patient-Specific Hemodynamics at Rest and Stress through an Aortic Coarctation provides patient-specific flow and pressure data. In this work, a multiscale 0D-3D strategy is tested to match the given data. The 3D outlet boundary conditions for the supra-aortic vessels are represented by three-element Windkessel models. In order to estimate the Windkessel parameters at these outlets, a 0D lumped parameter model for the full aorta is considered. The parameters in such a 0D model are estimated by a sequential estimation method, the unscented Kalman filter. The filtering approach estimates the parameters such that the results of the 0D model closely match the measured data: flow waveforms in the ascending and diaphragmatic aorta, mean flow rates in the supra-aortic vessels, and the pressure waveform in the ascending aorta. Information from the 3D model is taken into account in the full 0D model. This process is repeated for the two separate cases of rest and stress conditions to estimate separate sets of parameters for the two physiological states. Results such as the pressure gradient across the coarctation, comparison with target values and more detailed time or spatial variations are presented. Modelling choices and assumptions about how the data are interpreted are then discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Pennati, G., Corsini, C., Cosentino, D., Hsia, T.-Y., Luisi, V., Dubini, G., Migliavacca, F.: Boundary conditions of patient-specific fluid dynamics modelling of cavopulmonary connections: possible adaptation of pulmonary resistances results in a critical issue for a virtual surgical planning. J. R. Soc. Interface 1(3), 297–307 (2011)
Spilker, R.L., Taylor, C.A.: Tuning multidomain hemodynamic simulations to match physiological measurements. Ann. Biomed. Eng. 38(8), 26351748 (2010)
Troianowski, G., Taylor, C.A., Feinstein, J., Vignon-Clementel, I.E.: Three-dimensional simulations in glenn patients: clinically based boundary conditions, hemodynamic results and sensitivity to input data. J. of Biomech. Engrg. 133(11), 111006 (2011)
Ismail, M., Wall, W.A., Gee, M.G.: Adoint-Based Inverse Analysis of Windkessel Parameters for Patient-Specific Vascular Models. J. of Comp. Physics 244, 113170 (2013)
Milišić, V., Quarteroni, A.: Analysis of lumped parameter models for blood flow simulations and their relation with 1D models. ESAIM-Math. Model. Num. 38, 613–632 (2004)
Bertoglio, C., Moireau, P., Gerbeau, J.-F.: Sequential parameter estimation for fluid–structure problems: Application to hemodynamics. Int. J. Num. Methods in Biomed. Engrg. 28(4), 434–455 (2012)
Lassila, T., Manzoni, A., Quarteroni, A., Gianluigi, G.: A reduced computational and geometrical framework for inverse problems in hemodynamics. Int. J. Num. Methods in Biomed. Engrg. 29(7), 2040–7947 (2013)
Loseille, A., Löhner, R.: Adaptive anisotropic simulations in Aerodynamics. In: 48th AIAA Aerospace Sciences Meeting, AIAA 2010-169, Olando, FL, USA (2010), http://www-roc.inria.fr/gamma/Adrien.Loseille/index.php?page=softwares
Julier, S., Uhlmann, J., Durrant-Whyte, H.F.: A new approach for filtering nonlinear systems. In: American Control Conference, pp. 1628–1632 (1995)
Pham, D.T., Verron, J., Roubeaud, M.C.: A singular evolutive extended Kalman filter for data assimilation in oceanography. J. Marine Syst. 16(3-4), 323–340 (1998)
Moireau, P., Chapelle, D.: Reduced-order Unscented Kalman Filtering with application to parameter identification in large-dimensional systems. ESAIM Contr. Optim. Ca. 17, 380–405 (2011)
Chapelle, D., Fragu, M., Mallet, V., Moireau, P.: Fundamental principles of data assimilation underlying the Verdandi library: applications to biophysical model personalization within euHeart. Med. Biol. Eng. Comput. 1 (2013), http://verdandi.sourceforge.net/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Pant, S., Fabrèges, B., Gerbeau, JF., Vignon-Clementel, I.E. (2014). A Multiscale Filtering-Based Parameter Estimation Method for Patient-Specific Coarctation Simulations in Rest and Exercise. In: Camara, O., Mansi, T., Pop, M., Rhode, K., Sermesant, M., Young, A. (eds) Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges. STACOM 2013. Lecture Notes in Computer Science, vol 8330. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54268-8_12
Download citation
DOI: https://doi.org/10.1007/978-3-642-54268-8_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-54267-1
Online ISBN: 978-3-642-54268-8
eBook Packages: Computer ScienceComputer Science (R0)