Application of Patient-Specific Computational Fluid Dynamics in Coronary and Intra-Cardiac Flow Simulations: Challenges and Opportunities
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Boyang Su | Liang Zhong | Jun-Mei Zhang | Ru San Tan | John C. Allen | Ghassan S. Kassab | L. Zhong | G. Kassab | J. Allen | R. Tan | Junmei Zhang | B. Su
[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.