Weighted Least-Squares Finite Element Method for Cardiac Blood Flow Simulation with Echocardiographic Data

As both fluid flow measurement techniques and computer simulation methods continue to improve, there is a growing need for numerical simulation approaches that can assimilate experimental data into the simulation in a flexible and mathematically consistent manner. The problem of interest here is the simulation of blood flow in the left ventricle with the assimilation of experimental data provided by ultrasound imaging of microbubbles in the blood. The weighted least-squares finite element method is used because it allows data to be assimilated in a very flexible manner so that accurate measurements are more closely matched with the numerical solution than less accurate data. This approach is applied to two different test problems: a flexible flap that is displaced by a jet of fluid and blood flow in the porcine left ventricle. By adjusting how closely the simulation matches the experimental data, one can observe potential inaccuracies in the model because the simulation without experimental data differs significantly from the simulation with the data. Additionally, the assimilation of experimental data can help the simulation capture certain small effects that are present in the experiment, but not modeled directly in the simulation.

[1]  B. Jiang A least‐squares finite element method for incompressible Navier‐Stokes problems , 1992 .

[2]  Patrick M. Knupp,et al.  Fundamentals of Grid Generation , 2020 .

[3]  T. Manteuffel,et al.  First-order system least squares for second-order partial differential equations: part I , 1994 .

[4]  Rekha Ranjana Rao,et al.  A Newton-Raphson Pseudo-Solid Domain Mapping Technique for Free and Moving Boundary Problems , 1996 .

[5]  P. Bochev Analysis of Least-Squares Finite Element Methods for the Navier--Stokes Equations , 1997 .

[6]  Pavel B. Bochev,et al.  Analysis of Velocity-Flux First-Order System Least-Squares Principles for the Navier--Stokes Equations: Part I , 1998 .

[7]  Thomas A. Manteuffel,et al.  First-Order System Least Squares (FOSLS) for Convection-Diffusion Problems: Numerical Results , 1998, SIAM J. Sci. Comput..

[8]  Vipin Kumar,et al.  A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs , 1998, SIAM J. Sci. Comput..

[9]  L D Hall,et al.  Geometrical models of left ventricular contraction from MRI of the normal and spontaneously hypertensive rat heart. , 1999, Physics in medicine and biology.

[10]  C. Peskin,et al.  A three-dimensional computer model of the human heart for studying cardiac fluid dynamics , 2000, SIGGRAPH 2000.

[11]  J. Szmelter Incompressible flow and the finite element method , 2001 .

[12]  V. Barocas,et al.  Modeling passive mechanical interaction between aqueous humor and iris. , 2001, Journal of biomechanical engineering.

[13]  Robert D. Falgout,et al.  hypre: A Library of High Performance Preconditioners , 2002, International Conference on Computational Science.

[14]  R. LeVeque Finite Volume Methods for Hyperbolic Problems: Characteristics and Riemann Problems for Linear Hyperbolic Equations , 2002 .

[15]  Philippe G. Ciarlet,et al.  The finite element method for elliptic problems , 2002, Classics in applied mathematics.

[16]  Timothy J. Pedley,et al.  Mathematical modelling of arterial fluid dynamics , 2003 .

[17]  Gunnar Seemann,et al.  Mathematical Modeling of Cardiac Electro-mechanics: from protein to Organ , 2003, Int. J. Bifurc. Chaos.

[18]  Jean Hertzberg,et al.  Development and validation of echo PIV , 2004 .

[19]  Thomas A. Manteuffel,et al.  First-order system least squares (FOSLS) for coupled fluid-elastic problems , 2004 .

[20]  Thomas A. Manteuffel,et al.  On Mass-Conserving Least-Squares Methods , 2006, SIAM J. Sci. Comput..

[21]  Marek Belohlavek,et al.  Left ventricular structure and function: basic science for cardiac imaging. , 2006, Journal of the American College of Cardiology.

[22]  Arash Kheradvar,et al.  Optimal vortex formation as an index of cardiac health. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[23]  T A Manteuffel,et al.  First-order system least-squares (FOSLS) for modeling blood flow. , 2006, Medical engineering & physics.

[24]  Hairong Zheng,et al.  Real time multicomponent echo particle image velocimetry technique for opaque flow imaging , 2006 .

[25]  Boyce E. Griffith,et al.  An adaptive, formally second order accurate version of the immersed boundary method , 2007, J. Comput. Phys..

[26]  Thomas A. Manteuffel,et al.  An alternative least-squares formulation of the Navier-Stokes equations with improved mass conservation , 2007, J. Comput. Phys..

[27]  Marek Belohlavek,et al.  Left ventricular form and function revisited: applied translational science to cardiovascular ultrasound imaging. , 2007, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[28]  Marek Belohlavek,et al.  Increase in the Late Diastolic Filling Force Is Associated With Impaired Transmitral Flow Efficiency in Acute Moderate Elevation of Left Ventricular Afterload , 2009, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[29]  Charles A. Taylor,et al.  Patient-specific modeling of cardiovascular mechanics. , 2009, Annual review of biomedical engineering.

[30]  Marek Belohlavek,et al.  Impact of acute moderate elevation in left ventricular afterload on diastolic transmitral flow efficiency: analysis by vortex formation time. , 2009, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[31]  Thomas A. Manteuffel,et al.  Further results on error estimators for local refinement with first-order system least squares (FOSLS) , 2010, Numer. Linear Algebra Appl..

[32]  Thomas A. Manteuffel,et al.  Weighted least-squares finite elements based on particle imaging velocimetry data , 2010, J. Comput. Phys..

[33]  Marek Belohlavek,et al.  Impact of pericardial adhesions on diastolic function as assessed by vortex formation time, a parameter of transmitral flow efficiency , 2010, Cardiovascular ultrasound.

[34]  Marek Belohlavek,et al.  Potential role of Reynolds number in resolving Doppler- and catheter-based transvalvular gradient discrepancies in aortic stenosis. , 2011, The Journal of heart valve disease.

[35]  Marek Belohlavek,et al.  Flow Velocity Vector Fields by Ultrasound Particle Imaging Velocimetry , 2011, Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine.

[36]  L Zhong,et al.  CFD simulation of flow through heart: a perspective review , 2011, Computer methods in biomechanics and biomedical engineering.

[37]  Alexander I. Veress,et al.  Incorporation of a Left Ventricle Finite Element Model Defining Infarction Into the XCAT Imaging Phantom , 2011, IEEE Transactions on Medical Imaging.

[38]  Laura Cercenelli,et al.  Computational Finite Element Model of Cardiac Torsion , 2011, The International journal of artificial organs.