Patient‐specific CFD modelling in the thoracic aorta with PC‐MRI–based boundary conditions: A least‐square three‐element Windkessel approach

Rodrigo M. Romarowski; Adrien Lefieux; Simone Morganti; Alessandro Veneziani; Ferdinando Auricchio

doi:10.1002/cnm.3134

journal article Aug 30, 2018

Patient‐specific CFD modelling in the thoracic aorta with PC‐MRI–based boundary conditions: A least‐square three‐element Windkessel approach

Rodrigo M. Romarowski

Adrien Lefieux Simone Morganti Alessandro Veneziani Ferdinando Auricchio

International Journal for Numerical Methods in Biomedical Engineering Vol. 34 No. 11 · Wiley

View at Publisher Save 10.1002/cnm.3134

Abstract

AbstractThe increasing use of computational fluid dynamics for simulating blood flow in clinics demands the identification of appropriate patient‐specific boundary conditions for the customization of the mathematical models. These conditions should ideally be retrieved from measurements. However, finite resolution of devices as well as other practical/ethical reasons prevent the construction of complete data sets necessary to make the mathematical problems well posed. Available data need to be completed by modelling assumptions, whose impact on the final solution has to be carefully addressed. Focusing on aortic vascular districts and related pathologies, we present here a method for efficiently and robustly prescribing phase contrast MRI–based patient‐specific data as boundary conditions at the domain of interest. In particular, for the outlets, the basic idea is to obtain pressure conditions from an appropriate elaboration of available flow rates on the basis of a 3D/0D dimensionally heterogeneous modelling. The key point is that the parameters are obtained by a constrained optimization procedure. The rationale is that pressure conditions have a reduced impact on the numerical solution compared with velocity conditions, yielding a simulation framework less exposed to noise and inconsistency of the data, as well as to the arbitrariness of the underlying modelling assumptions. Numerical results confirm the reliability of the approach in comparison with other patient‐specific approaches adopted in the literature.

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References

55

[1]

10.1007/3-540-45468-3_54

[2]

10.1016/j.medengphy.2010.10.011

[3]

Patient-specific isogeometric fluid–structure interaction analysis of thoracic aortic blood flow due to implantation of the Jarvik 2000 left ventricular assist device

Y. Bazilevs, J.R. Gohean, T.J.R. Hughes et al.

Computer Methods in Applied Mechanics and Engineer... 10.1016/j.cma.2009.04.015

[4]

10.1016/j.medengphy.2005.06.008

[5]

10.1007/s00466-014-0976-6

[6]

10.1007/978-88-470-1152-6_4

[7]

10.1098/rsif.2016.0073

[8]

10.1137/060672005

[9]

10.1016/j.cma.2009.10.017

[10]

Geometric multiscale modeling of the cardiovascular system, between theory and practice

A. Quarteroni, A. Veneziani, C. Vergara

Computer Methods in Applied Mechanics and Engineer... 10.1016/j.cma.2016.01.007

[11]

10.1137/s003614290038296x

[12]

10.1002/fld.843

[13]

10.1016/j.cma.2006.09.011

[14]

10.1016/j.jbiomech.2011.11.041

[15]

10.1007/s10439-008-9609-6

[16]

10.1016/j.jbiomech.2012.10.012

[17]

10.1007/s10439-011-0431-1

[18]

10.1016/j.jbiomech.2017.06.005

[19]

10.1016/j.jvs.2015.02.048

[20]

10.1016/j.ejvs.2017.06.012

[21]

10.1002/cnm.1476

[22]

10.1152/ajpheart.1987.252.6.h1275

[23]

10.1583/14-4778mr.1

[24]

10.1115/1.1574332

[25]

10.1115/1.2895548

[26]

10.1007/s11517-008-0420-1

[27]

10.1002/cnm.2568

[28]

10.1007/s10439-018-2012-z

[29]

10.1016/0045-7825(90)90116-4

[30]

10.1007/978-88-470-1152-6_11

[31]

10.1137/1.9781611974546

[32]

10.1007/s10915-011-9547-6

[33]

10.1051/m2an/2012056

[34]

10.1002/(sici)1097-0363(19960315)22:5<325::aid-fld307>3.0.co;2-y

[35]

Frank O "Die grundform des arteriellen pulses" Z Biol (1899)

[36]

10.1152/ajpheart.1999.276.1.h81

[37]

10.1007/s11517-008-0359-2

[38]

10.1002/cnm.2598

[39]

10.1016/0021-9290(69)90024-4

[40]

Alastruey J "Lumped parameter outflow models for 1‐D blood flow simulations: effect on pulse waves and parameter estimation" Commun Comput Phys (2008)

[41]

Quantification of Hemodynamics in Abdominal Aortic Aneurysms During Rest and Exercise Using Magnetic Resonance Imaging and Computational Fluid Dynamics

Andrea S. Les, Shawn C. Shadden, C. Alberto Figueroa et al.

Annals of Biomedical Engineering 10.1007/s10439-010-9949-x

[42]

10.1152/ajpregu.1991.261.1.r126

[43]

10.1152/ajpheart.1995.268.4.h1540

[44]

10.1152/ajpheart.1999.276.2.h424

[45]

An algorithm for the machine calculation of complex Fourier series

James W. Cooley, John W. Tukey

Mathematics of Computation 10.1090/s0025-5718-1965-0178586-1

[46]

10.1042/cs1030007

[47]

10.1161/strokeaha.107.510677

[48]

10.1152/ajpheart.00411.2005

[49]

Nichols W (2011)

[50]

10.1080/10255842.2017.1334770

Showing 50 of 55 references

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Metrics

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Citations

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References

Details

Published: Aug 30, 2018
Vol/Issue: 34(11)
License: View

Authors

R

Rodrigo M. Romarowski

3D and Computer Simulation Laboratory IRCCS Policlinico San Donato San Donato Milanese Italy

A

Adrien Lefieux

Division of Cardiology Emory University Atlanta Georgia; Department of Mathematics and Computer Science Emory University Atlanta Georgia

S

Simone Morganti

Department of Electrical, Computer, and Biomedical Engineering University of Pavia Pavia Italy

A

Alessandro Veneziani

Department of Mathematics and Computer Science Emory University Atlanta Georgia

F

Ferdinando Auricchio

Department of Civil Engineering and Architecture University of Pavia Pavia Italy

Funding

Division of Mathematical Sciences Award: 1620406

Fondazione Cariplo Award: 2013-1779

Cite This Article

Rodrigo M. Romarowski, Adrien Lefieux, Simone Morganti, et al. (2018). Patient‐specific CFD modelling in the thoracic aorta with PC‐MRI–based boundary conditions: A least‐square three‐element Windkessel approach. International Journal for Numerical Methods in Biomedical Engineering, 34(11). https://doi.org/10.1002/cnm.3134

Patient‐specific CFD modelling in the thoracic aorta with PC‐MRI–based boundary conditions: A least‐square three‐element Windkessel approach

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