Dynamic finite-strain modelling of the human left ventricle in health and disease using an immersed boundary-finite element method

Detailed models of the biomechanics of the heart are important both for developing improved interventions for patients with heart disease and also for patient risk stratification and treatment planning. For instance, stress distributions in the heart affect cardiac remodelling, but such distributions are not presently accessible in patients. Biomechanical models of the heart offer detailed three-dimensional deformation, stress and strain fields that can supplement conventional clinical data. In this work, we introduce dynamic computational models of the human left ventricle (LV) that are derived from clinical imaging data obtained from a healthy subject and from a patient with a myocardial infarction (MI). Both models incorporate a detailed invariant-based orthotropic description of the passive elasticity of the ventricular myocardium along with a detailed biophysical model of active tension generation in the ventricular muscle. These constitutive models are employed within a dynamic simulation framework that accounts for the inertia of the ventricular muscle and the blood that is based on an immersed boundary (IB) method with a finite element description of the structural mechanics. The geometry of the models is based on data obtained non-invasively by cardiac magnetic resonance (CMR). CMR imaging data are also used to estimate the parameters of the passive and active constitutive models, which are determined so that the simulated end-diastolic and end-systolic volumes agree with the corresponding volumes determined from the CMR imaging studies. Using these models, we simulate LV dynamics from enddiastole to end-systole. The results of our simulations are shown to be in good agreement with subject-specific CMR-derived strain measurements and also with earlier clinical studies on human LV strain distributions.

[1]  Lik Chuan Lee,et al.  First evidence of depressed contractility in the border zone of a human myocardial infarction. , 2012, The Annals of thoracic surgery.

[2]  J. Guccione,et al.  MRI-based finite-element analysis of left ventricular aneurysm. , 2005, American journal of physiology. Heart and circulatory physiology.

[3]  D. H. Campen,et al.  Optimization of Cardiac Fiber Orientation for Homogeneous Fiber Strain During Ejection , 1999, Annals of Biomedical Engineering.

[4]  Godfrey L. Smith,et al.  Mapping of Epicardial Activation in a Rabbit Model of Chronic Myocardial Infarction: , 2007, Journal of cardiovascular electrophysiology.

[5]  L. Heltai,et al.  On the hyper-elastic formulation of the immersed boundary method , 2008 .

[6]  C. Peskin,et al.  Implicit second-order immersed boundary methods with boundary mass , 2008 .

[7]  Andrew D McCulloch,et al.  Laminar fiber architecture and three-dimensional systolic mechanics in canine ventricular myocardium. , 1999, American journal of physiology. Heart and circulatory physiology.

[8]  Boyce E. Griffith,et al.  Parallel and Adaptive Simulation of Cardiac Fluid Dynamics , 2009 .

[9]  Boyce E. Griffith,et al.  An accurate and efficient method for the incompressible Navier-Stokes equations using the projection method as a preconditioner , 2009, J. Comput. Phys..

[10]  McQueenDavid,et al.  Shared-Memory Parallel Vector Implementation of the Immersed Boundary Method for the Computation of Blood Flow in the Beating Mammalian Heart , 1997 .

[11]  C. Peskin,et al.  Heart Simulation by an Immersed Boundary Method with Formal Second-order Accuracy and Reduced Numerical Viscosity , 2001 .

[12]  Yongsam Kim,et al.  Penalty immersed boundary method for an elastic boundary with mass , 2007 .

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

[14]  Lucy T. Zhang,et al.  Immersed finite element method , 2004 .

[15]  R S Reneman,et al.  Porous medium finite element model of the beating left ventricle. , 1992, The American journal of physiology.

[16]  L. Heltai,et al.  Variational implementation of immersed finite element methods , 2011, 1110.2063.

[17]  David Gavaghan,et al.  Comparison of Rule-Based and DTMRI-Derived Fibre Architecture in a Whole Rat Ventricular Computational Model , 2009, FIMH.

[18]  J M Guccione,et al.  Mechanism underlying mechanical dysfunction in the border zone of left ventricular aneurysm: a finite element model study. , 2001, The Annals of thoracic surgery.

[19]  Adarsh Krishnamurthy,et al.  Patient-specific models of cardiac biomechanics , 2013, J. Comput. Phys..

[20]  P. Hunter,et al.  A quantitative analysis of cardiac myocyte relaxation: a simulation study. , 2006, Biophysical journal.

[21]  William Gropp,et al.  Efficient Management of Parallelism in Object-Oriented Numerical Software Libraries , 1997, SciTools.

[22]  Guillaume Houzeaux,et al.  What a Difference in Biomechanics Cardiac Fiber Makes , 2012, STACOM.

[23]  Jeroen J. Bax,et al.  Time course of global left ventricular strain after acute myocardial infarction. , 2010, European heart journal.

[24]  Andrew D. McCulloch,et al.  Effect of Laminar Orthotropic Myofiber Architecture on Regional Stress and Strain in the Canine Left Ventricle , 2000 .

[25]  A. McCulloch,et al.  Finite element stress analysis of left ventricular mechanics in the beating dog heart. , 1995, Journal of biomechanics.

[26]  David Saloner,et al.  Regional left ventricular myocardial contractility and stress in a finite element model of posterobasal myocardial infarction. , 2011, Journal of biomechanical engineering.

[27]  Roy C. P. Kerckhoffs,et al.  Coupling of a 3D Finite Element Model of Cardiac Ventricular Mechanics to Lumped Systems Models of the Systemic and Pulmonic Circulation , 2006, Annals of Biomedical Engineering.

[28]  R S Reneman,et al.  Dependence of local left ventricular wall mechanics on myocardial fiber orientation: a model study. , 1992, Journal of biomechanics.

[29]  Ellen Kuhl,et al.  A novel method for quantifying the in-vivo mechanical effect of material injected into a myocardial infarction. , 2011, The Annals of thoracic surgery.

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

[31]  Boyce E. Griffith,et al.  Quasi-static image-based immersed boundary-finite element model of left ventricle under diastolic loading , 2014, International journal for numerical methods in biomedical engineering.

[32]  Jack Lee,et al.  Myocardial transversely isotropic material parameter estimation from in-silico measurements based on a reduced-order unscented Kalman filter. , 2011, Journal of the mechanical behavior of biomedical materials.

[33]  David Farrell,et al.  Immersed finite element method and its applications to biological systems. , 2006, Computer methods in applied mechanics and engineering.

[34]  Alistair A. Young,et al.  Modelling passive diastolic mechanics with quantitative MRI of cardiac structure and function , 2009, Medical Image Anal..

[35]  Scott R. Kohn,et al.  Managing application complexity in the SAMRAI object‐oriented framework , 2002, Concurr. Comput. Pract. Exp..

[36]  Maxime Sermesant,et al.  Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges , 2015, Lecture Notes in Computer Science.

[37]  P. Hunter,et al.  Computational Mechanics of the Heart , 2000 .

[38]  A. McCulloch,et al.  Passive material properties of intact ventricular myocardium determined from a cylindrical model. , 1991, Journal of biomechanical engineering.

[39]  L. Ge,et al.  The Benefit of Enhanced Contractility in the Infarct Borderzone: A Virtual Experiment , 2012, Front. Physio..

[40]  C. Peskin,et al.  Modelling cardiac fluid dynamics and diastolic function , 2001, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[41]  T J Brady,et al.  Myocardial fiber shortening in humans: initial results of MR imaging. , 2000, Radiology.

[42]  Timothy G Reese,et al.  Diffusion tensor MRI of myocardial fibers and sheets: Correspondence with visible cut‐face texture , 2003, Journal of magnetic resonance imaging : JMRI.

[43]  Toshiaki Hisada,et al.  Multiphysics simulation of left ventricular filling dynamics using fluid-structure interaction finite element method. , 2004, Biophysical journal.

[44]  Reza Razavi,et al.  Personalized Computational Models of the Heart for Cardiac Resynchronization Therapy , 2010 .

[45]  Yongsam Kim,et al.  On various techniques for computer simulation of boundaries with mass , 2003 .

[46]  Daniel Rueckert,et al.  An Automatic Data Assimilation Framework for Patient-Specific Myocardial Mechanical Parameter Estimation , 2011, FIMH.

[47]  C. Liang,et al.  Effect of bending rigidity in a dynamic model of a polyurethane prosthetic mitral valve , 2012, Biomechanics and modeling in mechanobiology.

[48]  G Plank,et al.  Biophysical Modeling to Simulate the Response to Multisite Left Ventricular Stimulation Using a Quadripolar Pacing Lead , 2012, Pacing and clinical electrophysiology : PACE.

[49]  Luca Heltai,et al.  Benchmarking the immersed finite element method for fluid-structure interaction problems , 2013, Comput. Math. Appl..

[50]  E. McVeigh,et al.  Three-dimensional systolic strain patterns in the normal human left ventricle: characterization with tagged MR imaging. , 2000, Radiology.

[51]  I. LeGrice,et al.  Shear properties of passive ventricular myocardium. , 2002, American journal of physiology. Heart and circulatory physiology.

[52]  Charles S. Peskin,et al.  Shared-Memory Parallel Vector Implementation of the Immersed Boundary Method for the Computation of Blood Flow in the Beating Mammalian Heart , 2004, The Journal of Supercomputing.

[53]  Tammo Delhaas,et al.  Determinants of left ventricular shear strain. , 2009, American journal of physiology. Heart and circulatory physiology.

[54]  David Saloner,et al.  A computationally efficient formal optimization of regional myocardial contractility in a sheep with left ventricular aneurysm. , 2009, Journal of biomechanical engineering.

[55]  Boyce E. Griffith,et al.  Image-based fluid-structure interaction model of the human mitral valve , 2013 .

[56]  C. Peskin The immersed boundary method , 2002, Acta Numerica.

[57]  Gernot Plank,et al.  Influence of myocardial fiber/sheet orientations on left ventricular mechanical contraction , 2013 .

[58]  Colin Berry,et al.  Myocardial strain estimated from standard cine MRI closely represents strain estimated from dedicated strain-encoded MRI , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[59]  Maxime Sermesant,et al.  In vivo Human 3D Cardiac Fibre Architecture: Reconstruction Using Curvilinear Interpolation of Diffusion Tensor Images , 2010, MICCAI.

[60]  R. Kerckhoffs,et al.  Patient specific modeling of the cardiovascular system , 2010 .

[61]  C. Peskin,et al.  Simulation of a Flapping Flexible Filament in a Flowing Soap Film by the Immersed Boundary Method , 2002 .

[62]  M. Pinsky,et al.  Left ventricular systolic torsion correlates global cardiac performance during dyssynchrony and cardiac resynchronization therapy. , 2011, American journal of physiology. Heart and circulatory physiology.

[63]  Donald M. Bers,et al.  Excitation-Contraction Coupling and Cardiac Contractile Force , 2001, Developments in Cardiovascular Medicine.

[64]  David Nordsletten,et al.  Modelling left ventricular function under assist device support , 2011 .

[65]  G. Plank,et al.  Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy. , 2011, Cardiovascular research.

[66]  O. Hess,et al.  Cardiac rotation and relaxation in patients with chronic heart failure , 2004, European journal of heart failure.

[67]  Nico H. L. Kuijpers,et al.  Modeling Cardiac Electromechanics and Mechanoelectrical Coupling in Dyssynchronous and Failing Hearts , 2012, Journal of Cardiovascular Translational Research.

[68]  Daniel Burkhoff,et al.  Single-beat estimation of end-diastolic pressure-volume relationship: a novel method with potential for noninvasive application. , 2006, American journal of physiology. Heart and circulatory physiology.

[69]  Manish Parashar,et al.  Advanced Computational Infrastructures for Parallel and Distributed Adaptive Applications , 2009 .

[70]  Lemuel A Moyé,et al.  Left ventricular end-diastolic pressure and risk of subsequent heart failure in patients following an acute myocardial infarction. , 2007, Congestive heart failure.

[71]  Benjamin S. Kirk,et al.  Library for Parallel Adaptive Mesh Refinement / Coarsening Simulations , 2006 .

[72]  M. Pfeffer,et al.  Ventricular Remodeling After Myocardial Infarction: Experimental Observations and Clinical Implications , 1990, Circulation.

[73]  Boyce E. Griffith,et al.  Hybrid finite difference/finite element version of the immersed boundary method , 2012 .

[74]  Tammo Delhaas,et al.  Functional Imaging and Modeling of the Heart , 2015, Lecture Notes in Computer Science.

[75]  R. Ogden,et al.  Structure‐based finite strain modelling of the human left ventricle in diastole , 2013, International journal for numerical methods in biomedical engineering.

[76]  Alistair A. Young,et al.  Changes in In Vivo Myocardial Tissue Properties Due to Heart Failure , 2013, FIMH.

[77]  A. Alwan Global status report on noncommunicable diseases 2010. , 2011 .

[78]  P. Hunter,et al.  Fluid–solid coupling for the investigation of diastolic and systolic human left ventricular function , 2011 .

[79]  Boyce E. Griffith,et al.  Simulating the fluid dynamics of natural and prosthetic heart valves using the immersed boundary method , 2009 .

[80]  C. Peskin,et al.  Fluid Dynamics of the Heart and its Valves , 1996 .

[81]  C. Peskin Flow patterns around heart valves: A numerical method , 1972 .

[82]  L. Pierard,et al.  Low-level exercise echocardiography detects contractile reserve and predicts reversible dysfunction after acute myocardial infarction: comparison with low-dose dobutamine echocardiography. , 1999, Journal of the American College of Cardiology.

[83]  Mark Potse,et al.  A Comparison of Monodomain and Bidomain Reaction-Diffusion Models for Action Potential Propagation in the Human Heart , 2006, IEEE Transactions on Biomedical Engineering.

[84]  T. J. Wang,et al.  A modified Holzapfel-Ogden law for a residually stressed finite strain model of the human left ventricle in diastole , 2014, Biomechanics and modeling in mechanobiology.

[85]  Gerhard A Holzapfel,et al.  Constitutive modelling of passive myocardium: a structurally based framework for material characterization , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[86]  Roy C. P. Kerckhoffs,et al.  Effects of biventricular pacing and scar size in a computational model of the failing heart with left bundle branch block , 2009, Medical Image Anal..

[87]  Roy C. P. Kerckhoffs,et al.  Patient-specific modeling of dyssynchronous heart failure: a case study. , 2011, Progress in biophysics and molecular biology.

[88]  Boyce E. Griffith,et al.  Immersed Boundary Method for Variable Viscosity and Variable Density Problems Using Fast Constant-Coefficient Linear Solvers I: Numerical Method and Results , 2013, SIAM J. Sci. Comput..

[89]  Boyce E. Griffith,et al.  Immersed boundary model of aortic heart valve dynamics with physiological driving and loading conditions , 2012, International journal for numerical methods in biomedical engineering.

[90]  Reza Razavi,et al.  Functional Imaging and Modeling of the Heart , 2019, Lecture Notes in Computer Science.

[91]  Colin Berry,et al.  Left ventricular strain and its pattern estimated from cine CMR and validation with DENSE , 2014, Physics in medicine and biology.

[92]  P. Hunter,et al.  Modelling the mechanical properties of cardiac muscle. , 1998, Progress in biophysics and molecular biology.

[93]  Lucy T. Zhang Immersed finite element method for fluid-structure interactions , 2007 .

[94]  A. McCulloch,et al.  Modelling cardiac mechanical properties in three dimensions , 2001, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[95]  Boyce E. Griffith,et al.  Constructing a patient-specific model heart from ct data , 2015 .

[96]  W Grossman,et al.  Cardiac hypertrophy: useful adaptation or pathologic process? , 1980, The American journal of medicine.