Patient-Specific Modeling of the Cardiovascular System (eBook)

Technology-Driven Personalized Medicine

Roy C.P. Kerckhoffs (Herausgeber)

eBook Download: PDF

2010 | 2010
XXI, 240 Seiten
Springer New York (Verlag)
978-1-4419-6691-9 (ISBN)

Infos

Peter Hunter Computational physiology for the cardiovascular system is entering a new and exciting phase of clinical application. Biophysically based models of the human heart and circulation, based on patient-specific anatomy but also informed by po- lation atlases and incorporating a great deal of mechanistic understanding at the cell, tissue, and organ levels, offer the prospect of evidence-based diagnosis and treatment of cardiovascular disease. The clinical value of patient-specific modeling is well illustrated in application areas where model-based interpretation of clinical images allows a more precise analysis of disease processes than can otherwise be achieved. For example, Chap. 6 in this volume, by Speelman et al. , deals with the very difficult problem of trying to predict whether and when an abdominal aortic aneurysm might burst. This requires automated segmentation of the vascular geometry from magnetic re- nance images and finite element analysis of wall stress using large deformation elasticity theory applied to the geometric model created from the segmentation. The time-varying normal and shear stress acting on the arterial wall is estimated from the arterial pressure and flow distributions. Thrombus formation is identified as a potentially important contributor to changed material properties of the arterial wall. Understanding how the wall adapts and remodels its material properties in the face of changes in both the stress loading and blood constituents associated with infl- matory processes (IL6, CRP, MMPs, etc.

Inhalt

Patient Specific Modelingof the Cardiovascular System 3
Foreword 5
Preface 9
References 12
Contents 15
Contributors 17
Chapter 1: Integrating State-of-the-Art Computational Modeling with Clinical Practice: The Promise of Numerical Methods 23
1.1 Introduction 23
1.2 Imaging Methods Used in Patient-Specific Modeling 24
1.2.1 Echocardiography 24
1.2.2 Computed Tomography 24
1.2.3 Nuclear Imaging 25
1.2.4 Magnetic Resonance Imaging 25
1.2.5 Use of Imaging Data 25
1.3 Current Use of Patient-Specific Models in Cardiac Electrophysiology 26
1.3.1 Overview of Modeling During Invasive Electrophysiology Study and Ablation 26
1.3.2 Current Application of Computer Modeling in Atrial Arrhythmias 27
1.3.2.1 Atrial Fibrillation 27
1.3.2.2 Atypical Atrial Flutter and Focal Atrial Tachycardia 29
1.3.3 Current Application of Computer Modeling in Ventricular Arrhythmias 30
1.3.3.1 Premature Ventricular Contractions and Ventricular Tachycardia 30
1.3.3.2 Ventricular Fibrillation 31
1.3.4 Application in Remote Catheter Manipulation 32
1.3.5 Application in Cardiac Resynchronization Therapy 32
1.3.6 Application in Sudden Cardiac Death 32
1.4 Future Applications of Computer Modeling in Clinical Cardiac Electrophysiology 33
1.4.1 Atrial Arrhythmias 34
1.4.2 Ventricular Arrhythmias 34
1.4.3 Resynchronization Therapy and Congestive Heart Failure 34
1.5 Conclusion 35
References 36
Chapter 2: Patient-Specific Modeling of Cardiovascular Dynamics with a Major Role for Adaptation 42
2.1 Introduction 42
2.2 Cardiovascular Forward Models 45
2.3 Integration to a Comprehensive Circulatory System 47
2.4 Adaptation Rules 49
2.5 Examples of Patient-Specific Modeling 52
2.5.1 Reference State 52
2.5.2 Non-invasively Obtained LV Pump Function and Myofiber Function 53
2.5.3 Complete Pressure–Volume Loop of the Left Ventricle 56
2.5.4 Delay of the LV Activation in Left Bundle Branch Block 56
2.6 Discussion 58
References 60
Chapter 3: Patient-Specific Modeling of Structure and Function of Cardiac Cells 63
3.1 Introduction 63
3.2 Cardiac Cells 64
3.3 Cardiovascular Diseases and Cellular Phenotype 65
3.4 Imaging of Cardiac Cells 67
3.5 Modeling of Cardiac Cells 69
3.5.1 Functional Modeling 69
3.5.1.1 Development and Implementation of Functional Models 69
3.5.1.2 Models of Cardiac Cells 69
3.5.2 Structural Modeling 72
3.5.2.1 Development of Structural Models 72
3.5.2.2 Image Processing 73
3.5.2.3 Model Representation 75
3.6 Clinical Perspective 76
References 77
Chapter 4: Studies of Therapeutic Strategies for Atrial Fibrillation Based on a Biophysical Model of the Human Atria 82
4.1 Introduction 82
4.2 Computer Modeling of AF 83
4.2.1 Biophysical Model of Human Atria 84
4.2.1.1 Atrial Geometry 85
4.2.1.2 Electrical Propagation in Atrial Tissue 85
4.2.1.3 Atrial Cellular Model 85
4.2.2 Modeling Different Types of AF 86
4.2.2.1 Multiple Wavelet AF 86
4.2.2.2 Meandering Wavelet AF 86
4.2.2.3 Heterogeneities 87
4.2.2.4 Focal AF 87
4.2.3 Link to Clinical Data 87
4.3 Therapeutic Strategies for AF 88
4.3.1 Modeling AF Therapies 88
4.3.1.1 AF Database 88
4.4 Spontaneous Termination of AF 89
4.4.1 Simulation of Spontaneously Terminated Episodes 89
4.4.2 Temporal Scales of Termination 90
4.4.3 Spatial Scales of Termination 91
4.5 Ablation of AF 91
4.6 Pacing of AF 93
4.6.1 Pacing Protocol and Assessment of AF Capture 93
4.6.2 AF Pacing Results 94
4.7 Conclusion 96
References 96
Chapter 5: Patient-Specific Modeling for Critical Care 99
5.1 Introduction 99
5.2 Examples of Patient-Specific Modeling in Critical Care 100
5.2.1 Hemodynamic Models 100
5.2.1.1 Cardiac Output Estimation 102
5.2.1.2 Simulating Response to Traumatic Brain Injury 103
5.2.2 Models of Glucose and Insulin Dynamics 104
5.2.2.1 Controlling Blood Glucose Levels 104
5.3 Current Challenges 105
5.3.1 Clinical Validation 106
5.3.2 Timely Tuning Methods 106
5.3.3 Variability in Patient Anatomy, Physiology and Clinical Scenario 107
5.3.4 Model Interoperability 108
5.4 Vision for the Future 110
References 111
Chapter 6: Biomechanical Analysis of Abdominal Aortic Aneurysms 113
6.1 Abdominal Aortic Aneurysm 113
6.2 AAA Risk Stratification 114
6.3 AAA Biomechanical Analysis 115
6.3.1 Wall Stress Reproducibility 116
6.3.2 Initial Stress 118
6.3.3 Intraluminal Thrombus 118
6.3.4 Material Properties 120
6.3.5 Future Directions 121
6.4 Clinical Application 122
6.5 Scope and Limitations 123
6.6 Clinical Perspectives 125
6.7 Conclusion 125
References 125
Chapter 7: The Cardiac Atlas Project: Towards a Map of the Heart 130
7.1 Introduction 130
7.2 Cardiovascular Magnetic Resonance Imaging 131
7.3 Mapping Shape and Motion 132
7.4 Population Models 134
7.4.1 Parametric Distribution Models 134
7.4.2 Clinical Functional Modes 135
7.5 Data Fusion 136
7.6 The CAP Databases 138
7.6.1 Production Database (CCB) 138
7.6.2 Research Database 139
7.7 The CAP Client 140
7.8 CAP Data Access 142
7.8.1 Upload and Deidentification 142
7.8.2 Ownership and Control of Data Use 142
7.8.3 Protocols for Users 143
7.8.4 Informed Consent and Institutional Review Board Approval 143
7.9 Conclusions and Future Work 144
7.9.1 Grid Enabling 144
7.9.2 Ontologies 144
References 145
Chapter 8: In Vivo Myocardial Material Properties and Stress Distributions in Normal and Failing Human Hearts 147
8.1 Introduction 147
8.2 Left Ventricular Diastolic Function 149
8.2.1 Methodology for Model Generation and Strain Calculation in the Left Ventricle 149
8.2.2 Left Ventricular Myofiber Stress Distributions in a Normal Human Subject and a Patient with Diastolic Heart Failure 151
8.3 A Computationally Efficient Formal Optimization of Regional Myocardial Contractility 154
References 158
Chapter 9: Modeling of Whole-Heart Electrophysiology and Mechanics: Toward Patient-Specific Simulations 161
9.1 Introduction 161
9.2 Image Segmentation 162
9.2.1 Suspension Medium Removal 163
9.2.2 Level Set Segmentation 163
9.2.3 Segmentation of Ventricles 164
9.2.4 Infarct Segmentation 164
9.3 Electrical Mesh Generation 164
9.4 Mechanical Mesh Generation 166
9.5 Modeling of Electrophysiology: General Aspects 167
9.6 Modeling of Electromechanics: General Aspects 168
9.7 Cardiac Electrophysiology Modeling Example: Ventricular Tachycardia in the Infarcted Canine Heart 169
9.8 Cardiac Electromechanics Modeling Example: Electromechanical Delay in the Normal Canine Heart 171
9.9 On the Road to Patient-Specific Modeling 173
9.9.1 Processing Pipeline for Estimating Patient-Specific Fiber Orientations 174
9.9.2 Reconstruction of Patient Heart Geometry 174
9.9.3 Deformation of Atlas Heart Geometry 175
9.9.4 Deformation of Atlas Fiber Orientations 177
9.9.5 Pipeline Validation 178
9.10 Conclusion 178
References 178
Chapter 10: Personalized Computational Models of the Heart for Cardiac Resynchronization Therapy 182
10.1 Introduction 182
10.2 Clinical Context, Data Acquisition, and Fusion 184
10.3 Personalized Anatomy 186
10.4 Personalized Electrophysiology 187
10.5 Personalized Electromechanical Models 188
10.5.1 Personalized Kinematics 189
10.5.2 Personalized Mechanics 191
10.6 Prediction of the Acute Effects of Pacing on Left Ventricular Pressure 192
10.7 Conclusion 193
References 194
Chapter 11: Patient-Specific Modeling of Hypoxic Response and Microvasculature Dynamics 198
11.1 Introduction 198
11.2 Hypoxic Response in Disease 200
11.3 Hypoxic Response and Oxygen Sensing Models 202
11.3.1 Blood Flow and Oxygen Transport 203
11.3.2 NO and Vasodilation 203
11.3.3 Hypoxia-Inducible Factor 1: The Hypoxia Transcription Factor 204
11.3.3.1 Therapeutic Modulation of Cofactors in the HIF1 Pathway 204
11.3.3.2 Effects of Chronic Hypoxia at the Molecular Level 205
11.3.3.3 Reactive Oxygen Species Effect in the Hypoxic Response Signaling Pathway 205
11.3.3.4 HIF1 Intracellular Signaling Leading to VEGF Expression Changes 207
11.3.4 Cell-Level and Integrated, Multiscale Angiogenesis Models 208
11.4 Modeling Individual Variability 209
11.5 Discussion and Conclusions: Integrating and Validating Inter- and Intra-patient Variation on Multiple Scales 211
References 211
Chapter 12: A Computational Framework for Patient-Specific Multi-Scale Cardiac Modeling 217
12.1 Introduction 217
12.2 Multi-Scale Framework of Cardiac Modeling 218
12.3 Input Data Pipeline for Patient-Specific Multi-Scale Cardiac Modeling 219
12.3.1 Ventricular Anatomy and Fiber Architecture 219
12.3.2 Hemodynamics 220
12.3.3 Electrophysiology 221
12.4 Software Architecture 221
12.5 Database Server 221
12.6 Solver Client 224
12.7 Model Editors 225
12.8 Solver Server 225
12.9 Imaging and Fitting Modules 227
12.10 Mesh Module 228
12.11 Biomechanics 229
12.12 Electrophysiology Module 230
12.13 Fully Coupled Electromechanics Models 231
12.14 Plug-in Applications 232
12.15 Computational Requirements 233
12.16 Limitations 234
References 235
Appendix: Mathematical Modeling Language Code for the Hemodynamic Model in Fig..5.1b 238
Biography 242
Index 243

Produkt-Details

• Erscheint lt. Verlag: 3.9.2010
• Zusatzinfo: XXI, 240 p.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik
• Themenwelt: Medizinische Fachgebiete ► Innere Medizin ► Kardiologie / Angiologie
• Themenwelt: Medizin / Pharmazie ► Physiotherapie / Ergotherapie ► Orthopädie
• Themenwelt: Studium ► 1. Studienabschnitt (Vorklinik) ► Biochemie / Molekularbiologie
• Themenwelt: Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie
• Themenwelt: Technik ► Bauwesen
• Themenwelt: Technik ► Medizintechnik
• Schlagworte: Calculus • Cardiovascular • Computational Biology • Computed tomography (CT) • Diagnosis • heart • Kerckhoffs • Modeling • Numerical Methods • Physiology • Surgery
• ISBN-10: 1-4419-6691-9 / 1441966919
• ISBN-13: 978-1-4419-6691-9 / 9781441966919