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

The 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.

[1]  M. Cadioli,et al.  In Vivo Quantification of Helical Blood Flow in Human Aorta by Time-Resolved Three-Dimensional Cine Phase Contrast Magnetic Resonance Imaging , 2009, Annals of Biomedical Engineering.

[2]  N Westerhof,et al.  Beat-to-beat estimation of peripheral resistance and arterial compliance during pressure transients. , 1987, The American journal of physiology.

[3]  Peter Hansbo,et al.  A velocity pressure streamline diffusion finite element method for Navier-Stokes equations , 1990 .

[4]  David A. Steinman,et al.  From image data to computational domains , 2009 .

[5]  J. Alastruey,et al.  A systematic comparison between 1‐D and 3‐D hemodynamics in compliant arterial models , 2014, International journal for numerical methods in biomedical engineering.

[6]  C Karmonik,et al.  Elevated Wall Shear Stress in Aortic Type B Dissection May Relate to Retrograde Aortic Type A Dissection: A Computational Fluid Dynamics Pilot Study. , 2017, European journal of vascular and endovascular surgery : the official journal of the European Society for Vascular Surgery.

[7]  Charles A. Taylor,et al.  Computational fluid dynamics applied to cardiac computed tomography for noninvasive quantification of fractional flow reserve: scientific basis. , 2013, Journal of the American College of Cardiology.

[8]  F. Auricchio,et al.  Carotid artery stenting simulation: from patient-specific images to finite element analysis. , 2011, Medical engineering & physics.

[9]  Charles A. Taylor,et al.  On Coupling a Lumped Parameter Heart Model and a Three-Dimensional Finite Element Aorta Model , 2009, Annals of Biomedical Engineering.

[10]  N Westerhof,et al.  Normalized input impedance and arterial decay time over heart period are independent of animal size. , 1991, The American journal of physiology.

[11]  Philipp Beerbaum,et al.  Accuracy vs. computational time: translating aortic simulations to the clinic. , 2012, Journal of biomechanics.

[12]  Nan Xiao,et al.  On the impact of modelling assumptions in multi-scale, subject-specific models of aortic haemodynamics , 2016, Journal of The Royal Society Interface.

[13]  A Veneziani,et al.  Validation of an open source framework for the simulation of blood flow in rigid and deformable vessels , 2013, International journal for numerical methods in biomedical engineering.

[14]  Christian Vergara,et al.  Flow rate boundary problems for an incompressible fluid in deformable domains: Formulations and solution methods , 2010 .

[15]  N. Stergiopulos,et al.  Total arterial inertance as the fourth element of the windkessel model. , 1999, American journal of physiology. Heart and circulatory physiology.

[16]  Thomas J. R. Hughes,et al.  Patient-specific isogeometric fluid–structure interaction analysis of thoracic aortic blood flow due to implantation of the Jarvik 2000 left ventricular assist device , 2009 .

[17]  Christian Vergara,et al.  A New Approach to Numerical Solution of Defective Boundary Value Problems in Incompressible Fluid Dynamics , 2008, SIAM J. Numer. Anal..

[18]  K B Chandran,et al.  Flow dynamics in the human aorta. , 1993, Journal of biomechanical engineering.

[19]  Alessandro Veneziani,et al.  A Variational Data Assimilation Procedure for the Incompressible Navier-Stokes Equations in Hemodynamics , 2011, Journal of Scientific Computing.

[20]  D. Gallo,et al.  On the Use of In Vivo Measured Flow Rates as Boundary Conditions for Image-Based Hemodynamic Models of the Human Aorta: Implications for Indicators of Abnormal Flow , 2012, Annals of Biomedical Engineering.

[21]  Christian Vergara,et al.  An approximate method for solving incompressible Navier–Stokes problems with flow rate conditions , 2007 .

[22]  J. Pepper,et al.  On the choice of outlet boundary conditions for patient-specific analysis of aortic flow using computational fluid dynamics. , 2017, Journal of biomechanics.

[23]  P Croisille,et al.  Fluid- and Biomechanical Analysis of Ascending Thoracic Aorta Aneurysm with Concomitant Aortic Insufficiency , 2017, Annals of Biomedical Engineering.

[24]  Rolf Rannacher,et al.  ARTIFICIAL BOUNDARIES AND FLUX AND PRESSURE CONDITIONS FOR THE INCOMPRESSIBLE NAVIER–STOKES EQUATIONS , 1996 .

[25]  A Noordergraaf,et al.  Analog studies of the human systemic arterial tree. , 1969, Journal of biomechanics.

[26]  Peter Hansbo,et al.  A velocity-pressure streamline diffusion finite element method for the incompressible Navier-Stokes equation , 1990 .

[27]  Elizabeth A. Logsdon,et al.  Starting a Medical Technology Venture as a Young Academic Innovator or Student Entrepreneur , 2017, Annals of Biomedical Engineering.

[28]  Matts Karlsson,et al.  WALL SHEAR STRESS IN A SUBJECT SPECIFIC HUMAN AORTA - INFLUENCE OF FLUID-STRUCTURE INTERACTION , 2011 .

[29]  Alfio Quarteroni,et al.  Geometric multiscale modeling of the cardiovascular system, between theory and practice , 2016 .

[30]  David A. Steinman,et al.  An image-based modeling framework for patient-specific computational hemodynamics , 2008, Medical & Biological Engineering & Computing.

[31]  L. Wurfel Mcdonald S Blood Flow In Arteries Theoretical Experimental And Clinical Principles , 2016 .

[32]  D. Gallo,et al.  Uncertainty propagation of phase contrast-MRI derived inlet boundary conditions in computational hemodynamics models of thoracic aorta , 2017, Computer methods in biomechanics and biomedical engineering.

[33]  A. Quarteroni,et al.  Multiscale models of the vascular system , 2009 .

[34]  A. Veneziani,et al.  Uncertainty quantification for data assimilation in a steady incompressible Navier-Stokes problem , 2013 .

[35]  P Segers,et al.  Use of pulse pressure method for estimating total arterial compliance in vivo , 1999 .

[36]  S. Sherwin,et al.  Lumped parameter outflow models for 1-D blood flow simulations: Effect on pulse waves and parameter estimation , 2008 .

[37]  Michele Conti,et al.  Patient-specific analysis of post-operative aortic hemodynamics: a focus on thoracic endovascular repair (TEVAR) , 2014 .

[38]  Liqiang Zheng,et al.  Pulse Pressure and Mean Arterial Pressure in Relation to Ischemic Stroke Among Patients With Uncontrolled Hypertension in Rural Areas of China , 2008, Stroke.

[39]  C. Vergara,et al.  Flow rate defective boundary conditions in haemodynamics simulations , 2005 .

[40]  Berend E. Westerhof,et al.  The arterial Windkessel , 2009, Medical & Biological Engineering & Computing.

[41]  Robert C Gorman,et al.  Use of computational fluid dynamics studies in predicting aneurysmal degeneration of acute type B aortic dissections. , 2014, Journal of vascular surgery.

[42]  J. Tukey,et al.  An algorithm for the machine calculation of complex Fourier series , 1965 .

[43]  D Tresoldi,et al.  Mapping aortic hemodynamics using 3D cine phase contrast magnetic resonance parallel imaging: Evaluation of an anisotropic diffusion filter , 2014, Magnetic resonance in medicine.

[44]  O. Frank,et al.  Die grundform des arteriellen pulses , 1899 .

[45]  I. Meredith,et al.  Waveform dispersion, not reflection, may be the major determinant of aortic pressure wave morphology. , 2005, American journal of physiology. Heart and circulatory physiology.

[46]  Alfio Quarteroni,et al.  Numerical Treatment of Defective Boundary Conditions for the Navier-Stokes Equations , 2002, SIAM J. Numer. Anal..

[47]  P. Moireau,et al.  Sequential parameter estimation for fluid–structure problems: Application to hemodynamics , 2012, International journal for numerical methods in biomedical engineering.

[48]  D. Gallo,et al.  Inflow boundary conditions for image-based computational hemodynamics: impact of idealized versus measured velocity profiles in the human aorta. , 2013, Journal of biomechanics.

[49]  Marc Bocquet,et al.  Data Assimilation: Methods, Algorithms, and Applications , 2016 .

[50]  Don P Giddens,et al.  Effects of wall motion and compliance on flow patterns in the ascending aorta. , 2003, Journal of biomechanical engineering.

[51]  N Westerhof,et al.  Evaluation of methods for estimation of total arterial compliance. , 1995, The American journal of physiology.

[52]  Alessandro Reali,et al.  Aortic Hemodynamics after Thoracic Endovascular Aortic Repair, with Particular Attention to the Bird-Beak Configuration , 2014, Journal of endovascular therapy : an official journal of the International Society of Endovascular Specialists.

[53]  Alessandro Veneziani,et al.  Coupled Morphological–Hemodynamic Computational Analysis of Type B Aortic Dissection: A Longitudinal Study , 2018, Annals of Biomedical Engineering.

[54]  Yves Lecarpentier,et al.  Empirical estimates of mean aortic pressure: advantages, drawbacks and implications for pressure redundancy. , 2002, Clinical science.

[55]  B J B M Wolters,et al.  A patient-specific computational model of fluid-structure interaction in abdominal aortic aneurysms. , 2005, Medical engineering & physics.

[56]  Robert W. Dutton,et al.  A Software Framework for Creating Patient Specific Geometric Models from Medical Imaging Data for Simulation Based Medical Planning of Vascular Surgery , 2001, MICCAI.

[57]  Charles A. Taylor,et al.  Quantification of Hemodynamics in Abdominal Aortic Aneurysms During Rest and Exercise Using Magnetic Resonance Imaging and Computational Fluid Dynamics , 2010, Annals of Biomedical Engineering.