Application of Patient-Specific Computational Fluid Dynamics in Coronary and Intra-Cardiac Flow Simulations: Challenges and Opportunities

The emergence of new cardiac diagnostics and therapeutics of the heart has given rise to the challenging field of virtual design and testing of technologies in a patient-specific environment. Given the recent advances in medical imaging, computational power and mathematical algorithms, patient-specific cardiac models can be produced from cardiac images faster, and more efficiently than ever before. The emergence of patient-specific computational fluid dynamics (CFD) has paved the way for the new field of computer-aided diagnostics. This article provides a review of CFD methods, challenges and opportunities in coronary and intra-cardiac flow simulations. It includes a review of market products and clinical trials. Key components of patient-specific CFD are covered briefly which include image segmentation, geometry reconstruction, mesh generation, fluid-structure interaction, and solver techniques.

[1]  Charles A. Taylor,et al.  Morphometry-Based Impedance Boundary Conditions for Patient-Specific Modeling of Blood Flow in Pulmonary Arteries , 2007, Annals of Biomedical Engineering.

[2]  A J Tajik,et al.  Evaluation of diastolic filling of left ventricle in health and disease: Doppler echocardiography is the clinician's Rosetta Stone. , 1997, Journal of the American College of Cardiology.

[3]  D. Comaniciu,et al.  A machine-learning approach for computation of fractional flow reserve from coronary computed tomography. , 2016, Journal of applied physiology.

[4]  Liang Zhong,et al.  Three-Dimensional Tricuspid Annular Motion Analysis from Cardiac Magnetic Resonance Feature-Tracking , 2016, Annals of Biomedical Engineering.

[5]  A. Marsden,et al.  An integrated approach to patient-specific predictive modeling for single ventricle heart palliation , 2014, Computer methods in biomechanics and biomedical engineering.

[6]  Defeng Wang,et al.  Computational medical imaging and hemodynamics framework for functional analysis and assessment of cardiovascular structures , 2017, BioMedical Engineering OnLine.

[7]  Charles A. Taylor,et al.  Uncertainty quantification in coronary blood flow simulations: Impact of geometry, boundary conditions and blood viscosity. , 2016, Journal of biomechanics.

[8]  Alison L. Marsden,et al.  Patient-Specific Multiscale Modeling of Blood Flow for Coronary Artery Bypass Graft Surgery , 2012, Annals of Biomedical Engineering.

[9]  P. Kolh,et al.  A multi-scale cardiovascular system model can account for the load-dependence of the end-systolic pressure-volume relationship , 2013, Biomedical engineering online.

[10]  Udo Hoffmann,et al.  Noninvasive FFR Derived From Coronary CT Angiography: Management and Outcomes in the PROMISE Trial. , 2017, JACC. Cardiovascular imaging.

[11]  A. D. Gosman,et al.  Computational Flow Modeling of the Left Ventricle Based on In Vivo MRI Data: Initial Experience , 2001, Annals of Biomedical Engineering.

[12]  P. Serruys,et al.  Strain distribution over plaques in human coronary arteries relates to shear stress. , 2008, American journal of physiology. Heart and circulatory physiology.

[13]  Michail I. Papafaklis,et al.  Prediction of Progression of Coronary Artery Disease and Clinical Outcomes Using Vascular Profiling of Endothelial Shear Stress and Arterial Plaque Characteristics: The PREDICTION Study , 2012, Circulation.

[14]  F. Nicoud,et al.  Image-Based Simulations Show Important Flow Fluctuations in a Normal Left Ventricle: What Could be the Implications? , 2016, Annals of Biomedical Engineering.

[15]  A. Iskandrian,et al.  Risk assessment using single-photon emission computed tomographic technetium-99m sestamibi imaging. , 1998, Journal of the American College of Cardiology.

[16]  Gianni Pedrizzetti,et al.  Asymptotic Model of Fluid–Tissue Interaction for Mitral Valve Dynamics , 2014, Cardiovascular Engineering and Technology.

[17]  Maxime Sermesant,et al.  In vivo human cardiac fibre architecture estimation using shape-based diffusion tensor processing , 2013, Medical Image Anal..

[18]  Charles A. Taylor,et al.  A Computational Framework for Fluid-Solid-Growth Modeling in Cardiovascular Simulations. , 2009, Computer methods in applied mechanics and engineering.

[19]  Erik J. Bekkers,et al.  Multiscale Vascular Surface Model Generation From Medical Imaging Data Using Hierarchical Features , 2008, IEEE Transactions on Medical Imaging.

[20]  Liang Zhong,et al.  Fluid-dynamics modelling of the human left ventricle with dynamic mesh for normal and myocardial infarction: Preliminary study , 2012, Comput. Biol. Medicine.

[21]  Peter J Hunter,et al.  Modeling total heart function. , 2003, Annual review of biomedical engineering.

[22]  D. Comaniciu,et al.  Patient-specific modelling of whole heart anatomy, dynamics and haemodynamics from four-dimensional cardiac CT images , 2011, Interface Focus.

[23]  William Wijns,et al.  Fractional flow reserve calculation from 3-dimensional quantitative coronary angiography and TIMI frame count: a fast computer model to quantify the functional significance of moderately obstructed coronary arteries. , 2014, JACC. Cardiovascular interventions.

[24]  Liang Zhong,et al.  Simplified Models of Non-Invasive Fractional Flow Reserve Based on CT Images , 2016, PloS one.

[25]  Jan Vierendeels,et al.  Patient-specific CFD models for intraventricular flow analysis from 3D ultrasound imaging: Comparison of three clinical cases. , 2017, Journal of biomechanics.

[26]  Liang Zhong,et al.  Left ventricular regional wall curvedness and wall stress in patients with ischemic dilated cardiomyopathy. , 2009, American journal of physiology. Heart and circulatory physiology.

[27]  D. Ku,et al.  Pulsatile Flow and Atherosclerosis in the Human Carotid Bifurcation: Positive Correlation between Plaque Location and Low and Oscillating Shear Stress , 1985, Arteriosclerosis.

[28]  Michael Markl,et al.  MRI-Based CFD Analysis of Flow in a Human Left Ventricle: Methodology and Application to a Healthy Heart , 2009, Annals of Biomedical Engineering.

[29]  Karol Miller,et al.  From Finite Element Meshes to Clouds of Points: A Review of Methods for Generation of Computational Biomechanics Models for Patient-Specific Applications , 2015, Annals of Biomedical Engineering.

[30]  Michael I. Miller,et al.  Image-Based Estimation of Ventricular Fiber Orientations for Personalized Modeling of Cardiac Electrophysiology , 2012, IEEE Transactions on Medical Imaging.

[31]  Liang Zhong,et al.  Numerical simulation of patient-specific left ventricular model with both mitral and aortic valves by FSI approach , 2014, Comput. Methods Programs Biomed..

[32]  Shengshou Hu,et al.  Diagnostic Accuracy of Angiography-Based Quantitative Flow Ratio Measurements for Online Assessment of Coronary Stenosis. , 2017, Journal of the American College of Cardiology.

[33]  Liang Zhong,et al.  Hemodynamic analysis of patient‐specific coronary artery tree , 2015, International journal for numerical methods in biomedical engineering.

[34]  B L Langille,et al.  Reductions in arterial diameter produced by chronic decreases in blood flow are endothelium-dependent. , 1986, Science.

[35]  L. Chua,et al.  Perspective on CFD studies of coronary artery disease lesions and hemodynamics: A review , 2014, International journal for numerical methods in biomedical engineering.

[36]  D N Firmin,et al.  Subject-specific computational simulation of left ventricular flow based on magnetic resonance imaging , 2008, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

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

[38]  Jeanette P. Schmidt,et al.  The Simbios National Center: Systems Biology in Motion , 2008, Proceedings of the IEEE.

[39]  A. Hazel,et al.  Spatial comparison between wall shear stress measures and porcine arterial endothelial permeability. , 2004, American journal of physiology. Heart and circulatory physiology.

[40]  D. Ku,et al.  Mechanical Factors in the Pathogenesis, Localization and Evolution of Atherosclerotic Plaques , 1989 .

[41]  Thomas Redel,et al.  Tetrahedral vs. polyhedral mesh size evaluation on flow velocity and wall shear stress for cerebral hemodynamic simulation , 2011, Computer methods in biomechanics and biomedical engineering.

[42]  Leo Grady,et al.  Impact of geometric uncertainty on hemodynamic simulations using machine learning , 2015 .

[43]  Nasser Fatouraee,et al.  The impact of valve simplifications on left ventricular hemodynamics in a three dimensional simulation based on in vivo MRI data. , 2016, Journal of biomechanics.

[44]  H. Suga,et al.  Assessment of systolic and diastolic ventricular properties via pressure-volume analysis: a guide for clinical, translational, and basic researchers. , 2005, American journal of physiology. Heart and circulatory physiology.

[45]  Xavier Trosseille,et al.  Comparison of Tetrahedral and Hexahedral Meshes for Organ Finite Element Modelling: AnApplication to Kidney Impact , 2007 .

[46]  Vinh-Tan Nguyen,et al.  A semi-automated method for patient-specific computational flow modelling of left ventricles , 2015, Computer methods in biomechanics and biomedical engineering.

[47]  Atam P. Dhawan,et al.  3-D reconstruction of coronary arteries , 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[48]  H. Alkadhi,et al.  Radiation dose of cardiac dual-source CT: the effect of tailoring the protocol to patient-specific parameters. , 2008, European journal of radiology.

[49]  Emil N. Holck,et al.  Evaluation of Coronary Artery Stenosis by Quantitative Flow Ratio During Invasive Coronary Angiography , 2018, Circulation. Cardiovascular imaging.

[50]  J D Humphrey,et al.  A finite element‐based constrained mixture implementation for arterial growth, remodeling, and adaptation: Theory and numerical verification , 2013, International journal for numerical methods in biomedical engineering.

[51]  Charles A. Taylor,et al.  Feasibility and diagnostic performance of fractional flow reserve measurement derived from coronary computed tomography angiography in real clinical practice , 2017, The International Journal of Cardiovascular Imaging.

[52]  Guang-Zhong Yang,et al.  Progress Towards Patient-Specific Computational Flow Modeling of the Left Heart via Combination of Magnetic Resonance Imaging with Computational Fluid Dynamics , 2004, Annals of Biomedical Engineering.

[53]  Ahmed Hassanein,et al.  Multiphase hemodynamic simulation of pulsatile flow in a coronary artery. , 2006, Journal of biomechanics.

[54]  L. Zhong,et al.  Three‐dimensional CFD/MRI modeling reveals that ventricular surgical restoration improves ventricular function by modifying intraventricular blood flow , 2014, International journal for numerical methods in biomedical engineering.

[55]  J. Reiber,et al.  Diagnostic Accuracy of Fast Computational Approaches to Derive Fractional Flow Reserve From Diagnostic Coronary Angiography: The International Multicenter FAVOR Pilot Study. , 2016, JACC. Cardiovascular interventions.

[56]  J. Gunn,et al.  Computational fluid dynamics modelling in cardiovascular medicine , 2015, Heart.

[57]  Liang Zhong,et al.  Two-dimensional intraventricular flow pattern visualization using the image-based computational fluid dynamics , 2017, Computer methods in biomechanics and biomedical engineering.

[58]  Jürgen Hennig,et al.  Fluid-dynamic modeling of the human left ventricle: methodology and application to surgical ventricular reconstruction. , 2009, The Annals of thoracic surgery.

[59]  Petter Dyverfeldt,et al.  Quantification of presystolic blood flow organization and energetics in the human left ventricle. , 2011, American journal of physiology. Heart and circulatory physiology.

[60]  Dalin Tang,et al.  Correlations of coronary plaque wall thickness with wall pressure and wall pressure gradient: a representative case study , 2012, Biomedical engineering online.

[61]  Naomi C. Chesler,et al.  Cardiac Tissue Structure, Properties, and Performance: A Materials Science Perspective , 2014, Annals of Biomedical Engineering.

[62]  J Belinha,et al.  Meshless Methods: The Future of Computational BiomechanicalSimulation , 2016 .

[63]  Michail I. Papafaklis,et al.  Association of endothelial shear stress with plaque thickness in a real three-dimensional left main coronary artery bifurcation model. , 2007, International journal of cardiology.

[64]  Michael J Pencina,et al.  Diagnostic accuracy of fractional flow reserve from anatomic CT angiography. , 2012, JAMA.

[65]  Claudio Chiastra,et al.  Biomechanical Modeling to Improve Coronary Artery Bifurcation Stenting: Expert Review Document on Techniques and Clinical Implementation. , 2015, JACC. Cardiovascular interventions.

[66]  G. Pedrizzetti,et al.  Three dimensional numerical assessment of the right ventricular flow using 4D echocardiography boundary data , 2012 .

[67]  Patricia V Lawford,et al.  Virtual fractional flow reserve from coronary angiography: modeling the significance of coronary lesions: results from the VIRTU-1 (VIRTUal Fractional Flow Reserve From Coronary Angiography) study. , 2013, JACC. Cardiovascular interventions.

[68]  L. Zhong,et al.  Age and gender-specific changes in left ventricular systolic function in human volunteers. , 2014, International journal of cardiology.

[69]  Guang-Zhong Yang,et al.  MR Image-Based Geometric and Hemodynamic Investigation of the Right Coronary Artery with Dynamic Vessel Motion , 2010, Annals of Biomedical Engineering.

[70]  S. Keevil,et al.  Selecting a CT scanner for cardiac imaging: the heart of the matter. , 2016, The British journal of radiology.

[71]  K. Gould,et al.  Is discordance of coronary flow reserve and fractional flow reserve due to methodology or clinically relevant coronary pathophysiology? , 2012, JACC. Cardiovascular imaging.

[72]  R. Schroter,et al.  Arterial Wall Shear and Distribution of Early Atheroma in Man , 1969, Nature.

[73]  Y. Cho,et al.  Effects of the non-Newtonian viscosity of blood on flows in a diseased arterial vessel. Part 1: Steady flows. , 1991, Biorheology.

[74]  Effects of the Non-Newtonian Viscosity of Blood on Flow Field in a Constricted Artery with a Porous Plaque , 2015 .

[75]  Alejandro F. Frangi,et al.  Numerical simulation of blood flow in the left ventricle and aortic sinus using magnetic resonance imaging and computational fluid dynamics , 2014, Computer methods in biomechanics and biomedical engineering.

[76]  Elías Cueto,et al.  On the employ of meshless methods in biomechanics , 2005 .

[77]  Laurent Younes,et al.  Hemodynamics in the Left Atrium and Its Effect on Ventricular Flow Patterns. , 2015, Journal of biomechanical engineering.

[78]  Alfio Quarteroni,et al.  Integrated Heart—Coupling multiscale and multiphysics models for the simulation of the cardiac function , 2017 .

[79]  Alison L. Marsden,et al.  A stochastic collocation method for uncertainty quantification and propagation in cardiovascular simulations. , 2011, Journal of biomechanical engineering.

[80]  I. Meredith,et al.  Noninvasive CT-Derived FFR Based on Structural and Fluid Analysis: A Comparison With Invasive FFR for Detection of Functionally Significant Stenosis. , 2017, JACC. Cardiovascular imaging.

[81]  T. Böhlke,et al.  Partitioned Fluid–Solid Coupling for Cardiovascular Blood Flow , 2010, Annals of Biomedical Engineering.

[82]  H. Bøtker,et al.  Rationale and design of the HeartFlowNXT (HeartFlow analysis of coronary blood flow using CT angiography: NeXt sTeps) study. , 2013, Journal of cardiovascular computed tomography.

[83]  Liang-Yu Lin,et al.  Towards patient-specific cardiovascular modeling system using the immersed boundary technique , 2011, Biomedical engineering online.

[84]  J. Ohayon,et al.  Unsteady blood flow and mass transfer of a human left coronary artery bifurcation: FSI vs. CFD , 2012 .

[85]  J. Tarbell,et al.  Computational simulation of flow in the end-to-end anastomosis of a rigid graft and a compliant artery. , 1996, ASAIO journal.

[86]  M. H. Friedman,et al.  Influence of curvature dynamics on pulsatile coronary artery flow in a realistic bifurcation model. , 2004, Journal of biomechanics.

[87]  I. Marusic,et al.  Advances in three-dimensional coronary imaging and computational fluid dynamics: is virtual fractional flow reserve more than just a pretty picture? , 2015, Coronary artery disease.

[88]  H. Howie Huang,et al.  Computational modeling of cardiac hemodynamics: Current status and future outlook , 2016, J. Comput. Phys..

[89]  R. Kuzo,et al.  Coronary computed tomographic angiography: current and future uses. , 2007, Heart and metabolism : management of the coronary patient.

[90]  F. Bauer,et al.  Effect of the ellipsoid shape of the left ventricular outflow tract on the echocardiographic assessment of aortic valve area in aortic stenosis. , 2014, Journal of cardiovascular computed tomography.

[91]  Franck Nicoud,et al.  Image-based large-eddy simulation in a realistic left heart , 2014 .

[92]  Ulrich Steinseifer,et al.  FDA Benchmark Medical Device Flow Models for CFD Validation , 2017, ASAIO journal.

[93]  Vartan Kurtcuoglu,et al.  Choosing the optimal wall shear parameter for the prediction of plaque location-A patient-specific computational study in human right coronary arteries. , 2010, Atherosclerosis.

[94]  Jung Hee Seo,et al.  Effect of diastolic flow patterns on the function of the left ventricle , 2013 .

[95]  Guang-Zhong Yang,et al.  Stress phase angle depicts differences in coronary artery hemodynamics due to changes in flow and geometry after percutaneous coronary intervention. , 2009, American journal of physiology. Heart and circulatory physiology.

[96]  Karol Miller,et al.  Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration. , 2010, Progress in biophysics and molecular biology.

[97]  Xiaohua Zhang,et al.  A simple technique to improve computational efficiency of meshless methods , 2012 .

[98]  Vicente Grau,et al.  3D reconstruction of coronary arteries from 2D angiographic projections using non-uniform rational basis splines (NURBS) for accurate modelling of coronary stenoses , 2018, PloS one.

[99]  Hiroshi Ito,et al.  Diagnostic performance of noninvasive fractional flow reserve derived from coronary computed tomography angiography in suspected coronary artery disease: the NXT trial (Analysis of Coronary Blood Flow Using CT Angiography: Next Steps). , 2014, Journal of the American College of Cardiology.

[100]  Habib Samady,et al.  Association of Coronary Wall Shear Stress With Atherosclerotic Plaque Burden, Composition, and Distribution in Patients With Coronary Artery Disease , 2012, Journal of the American Heart Association.

[101]  Charles A. Taylor,et al.  A coupled momentum method for modeling blood flow in three-dimensional deformable arteries , 2006 .

[102]  D. L. Fry Acute Vascular Endothelial Changes Associated with Increased Blood Velocity Gradients , 1968, Circulation research.

[103]  S. Ito,et al.  Assessment of left ventricular systolic wall motion velocity with pulsed tissue Doppler imaging: comparison with peak dP/dt of the left ventricular pressure curve. , 1998, Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography.

[104]  Olivier Pironneau,et al.  An Energy Stable Monolithic Eulerian Fluid-Structure Numerical Scheme , 2016, 1607.08083.

[105]  R. Terkeltaub,et al.  Genetics in Arterial Calcification: Pieces of a Puzzle and Cogs in a Wheel , 2011, Circulation research.

[106]  G Plank,et al.  Image-Based Personalization of Cardiac Anatomy for Coupled Electromechanical Modeling , 2015, Annals of Biomedical Engineering.

[107]  Gianni Pedrizzetti,et al.  Left Ventricular Fluid Mechanics: The Long Way from Theoretical Models to Clinical Applications , 2014, Annals of Biomedical Engineering.

[108]  Liang Zhong,et al.  Patient-specific blood flows and vortex formations in patients with hypertrophic cardiomyopathy using computational fluid dynamics , 2014, 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES).

[109]  G. Truskey,et al.  Hemodynamic parameters and early intimal thickening in branching blood vessels. , 2001, Critical reviews in biomedical engineering.

[110]  Liang Zhong,et al.  Numerical Modeling of Intraventricular Flow during Diastole after Implantation of BMHV , 2015, PloS one.

[111]  Frédéric Hecht,et al.  An energy stable monolithic Eulerian fluid‐structure finite element method , 2017 .

[112]  Siamak N. Doost,et al.  Heart blood flow simulation: a perspective review , 2016, Biomedical engineering online.

[113]  Roland Krug,et al.  Cardiac MR imaging: current status and future direction. , 2015, Cardiovascular diagnosis and therapy.

[114]  Fotis Sotiropoulos,et al.  On the three-dimensional vortical structure of early diastolic flow in a patient-specific left ventricle. , 2012, European journal of mechanics. B, Fluids.

[115]  R. Mittal,et al.  Effect of the mitral valve on diastolic flow patterns , 2014 .

[116]  S. Kuribayashi,et al.  Cost analysis of non-invasive fractional flow reserve derived from coronary computed tomographic angiography in Japan , 2014, Cardiovascular Intervention and Therapeutics.

[117]  J Degroote,et al.  FSI simulation of asymmetric mitral valve dynamics during diastolic filling , 2012, Computer methods in biomechanics and biomedical engineering.

[118]  Liang Zhong,et al.  Right ventricular regional wall curvedness and area strain in patients with repaired tetralogy of Fallot. , 2012, American journal of physiology. Heart and circulatory physiology.

[119]  Liang Zhong,et al.  Advanced analyses of computed tomography coronary angiography can help discriminate ischemic lesions. , 2018, International journal of cardiology.

[120]  G. Kassab,et al.  Biomechanical considerations in the design of graft: the homeostasis hypothesis. , 2006, Annual review of biomedical engineering.

[121]  A. Kono,et al.  Fractional flow reserve computed from noninvasive CT angiography data: diagnostic performance of an on-site clinician-operated computational fluid dynamics algorithm. , 2015, Radiology.

[122]  A. Wahle,et al.  Effect of Endothelial Shear Stress on the Progression of Coronary Artery Disease, Vascular Remodeling, and In-Stent Restenosis in Humans: In Vivo 6-Month Follow-Up Study , 2003, Circulation.

[123]  T. Ebbers,et al.  Altered Diastolic Flow Patterns and Kinetic Energy in Subtle Left Ventricular Remodeling and Dysfunction Detected by 4D Flow MRI , 2016, PloS one.

[124]  Ellen Kuhl,et al.  A critical review, an in vivo parameter identification, and the effect of prestrain , 2013 .

[125]  Matthias Gutberlet,et al.  Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFRCT: outcome and resource impacts study , 2015, European heart journal.

[126]  A. Dunning,et al.  Diagnosis of ischemia-causing coronary stenoses by noninvasive fractional flow reserve computed from coronary computed tomographic angiograms. Results from the prospective multicenter DISCOVER-FLOW (Diagnosis of Ischemia-Causing Stenoses Obtained Via Noninvasive Fractional Flow Reserve) study. , 2011, Journal of the American College of Cardiology.

[127]  Takumi Washio,et al.  Multi-scale simulations of cardiac electrophysiology and mechanics using the University of Tokyo heart simulator. , 2012, Progress in biophysics and molecular biology.

[128]  G. Plank,et al.  A Novel Rule-Based Algorithm for Assigning Myocardial Fiber Orientation to Computational Heart Models , 2012, Annals of Biomedical Engineering.

[129]  Charles A. Taylor,et al.  Patient-Specific Modeling of Blood Flow and Pressure in Human Coronary Arteries , 2010, Annals of Biomedical Engineering.

[130]  Giorgio Galanti,et al.  Comparative numerical study on left ventricular fluid dynamics after dilated cardiomyopathy. , 2013, Journal of biomechanics.

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

[132]  Liang Zhong,et al.  Cardiac MRI based numerical modeling of left ventricular fluid dynamics with mitral valve incorporated. , 2016, Journal of biomechanics.