He Modeling & Imaging of Bioelectrical Activity

Principles and Applications
1. Auflage 2010
ISBN: 978-0-387-49963-5
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 322 Seiten

Reihe: Bioelectric Engineering

Over the past several decades, much progress has been made in understanding the mechanisms of electrical activity in biological tissues and systems, and for developing non-invasive functional imaging technologies to aid clinical diagnosis of dysfunction in the human body.
The book will provide full basic coverage of the fundamentals of modeling of electrical activity in various human organs, such as heart and brain. It will include details of bioelectromagnetic measurements and source imaging technologies, as well as biomedical applications. The book will review the latest trends in the field and comment on the future direction in this fast developing line of research.

Bin He, PhD., is a leading figure in the field of bioelectric engineering. An internationally recognized scientist with numerous publications, Dr. He has served as the President of the International Society of Bioelectromagnetism and as an Associate or Guest Editor for nine international journals in the field of biomedical engineering. Dr. Bin He is currently Professor of Bioengineering at the University of Minnesota.

Autoren/Hrsg.

He, Bin

Inhaltsverzeichnis

1;PREFACE;6
2;Table of Contents
;9
3;1 FROM CELLULAR ELECTROPHYSIOLOGY TO ELECTROCARDIOGRAPHY
;15
3.1;INTRODUCTION;15
3.2;1.1 THE ONE-CELL MODEL;17
3.2.1;1.1.1 VOLTAGE GATING ION CHANNEL KINETICS (HODGKIN-HUXLEY FORMAUSM)
;17
3.2.2;1.1.2 MODELING THE CARDIAC ACTION POTENTIAL;21
3.2.2.1;1.1.2.1 Classical models of the cardiac actionpotential
;22
3.2.2.2;1.1.2.2 Modern models of cardiac action potentials
;23
3.2.3;1.1.3 MODELING PATHOLOGIC ACTION POTENTIALS;24
3.2.3.1;1.1.3.1 Myocardial ischemia;25
3.2.3.2;1.1.3.2 Early afterdepolarizations (EADs) and delayed afterdepolarizations (DADs)
;28
3.2.3.3;1.1.3.3 Long-QT syndrome;29
3.3;1.2 NETWORK MODELS;31
3.3.1;1.2.1 CELL-CELL COUPLING AND LINEAR CABLE THEORY;31
3.3.2;1.2.2 MULTIDIMENSIONAL NETWORKS;32
3.3.3;1.2.3 RECONSTRUCTION OF THE LOCAL EXTRACELLULAR ELECTROGRAM (FORWARD PROBLEM)
;34
3.3.4;1.2.4 MODELING PATHOLOGY IN CELLULAR NETWORKS;37
3.3.4.1;1.2.4.1 Myocardial ischemia;38
3.3.4.2;1.2.4.2 EADs in 1D and 2D networks;39
3.3.4.3;1.2.4.3 The ionic basis of spiralwaves andfibrillation
;41
3.3.4.4;1.2.4.4 Cell-networks in Long-QT Syndrome;43
3.4;1.3 MODELING PATHOLOGY IN THREE-DIMENSIONAL AND WHOLE HEART MODELS
;43
3.4.1;1.3.1 MYOCARDIAL ISCHEMIA;45
3.4.2;1.3.2 PREEXCITATION STUDIES;45
3.4.3;1.3.3 HYPERTROPHIC CARDIOMYOPATHY;48
3.4.4;1.3.4 DRUG INTEGRATION IN THREE-DIMENSIONAL WHOLE HEART MODELS
;49
3.4.5;1.3.5 GENETIC INTEGRATION IN THREE-DIMENSIONAL WHOLE HEART MODELS
;49
3.5;1.4 DISCUSSION;50
3.6;REFERENCES;52
4;2 THE FORWARD PROBLEM OF ELECTROCARDIOGRAPHY: THEORETICAL UNDERPINNINGS AND APPLICATIONS
;57
4.1;2.1 INTRODUCTION;57
4.2;2.2 DIPOLE SOURCE REPRESENTATIONS;58
4.2.1;2.2.1 FUNDAMENTAL EQUATIONS;58
4.2.2;2.2.2 THE BIDOMAIN MYOCARDIUM;60
4.2.2.1;2.2.2.1 Equations for an Isotropic Bidomain-the Uniform Dipole Layer;61
4.2.2.2;2.2.2.2 Equations for an Anisotropic Bidomain-the Oblique Dipole Layer;64
4.3;2.3 TORSO GEOMETRYREPRESENTATIONS;67
4.4;2.4 SOLUTION METHODOLOGIES FOR THEFORWARD PROBLEM;67
4.4.1;2.4.1 SURFACE METHODS;68
4.4.1.1;2.4.1.1 Solutions from Equivalent Dipoles;68
4.4.1.2;2.4.1.2 Solutionsfrom Epicardial Potentials;71
4.4.2;2.4.2 VOLUME METHODS;72
4.4.2.1;2.4.2.1 Finite-Difference Method;72
4.4.2.2;2.4.2.2 Finite-Element Method;72
4.4.2.3;2.4.2.3 Finite-Volume Method;74
4.4.3;2.4.3 COMBINATION METHODS;75
4.5;2.5 APPUCATIONS OF THE FORWARD PROBLEM;75
4.5.1;2.5.1 COMPUTER HEART MODELS;76
4.5.1.1;2.5.1.1 Determining the Excitation Pattern of the Heart
;76
4.5.1.2;2.5.1.2 Calculating Torso and/or Epicardial Potentials
;78
4.5.2;2.5.2 EFFECTS OF TORSO CONDUCTIVITY INHOMOGENEITIES;84
4.5.3;2.5.3 DEFIBRILLATION;86
4.6;2.6 FUTURE TRENDS;89
4.7;ACKNOWLEDGMENT;89
4.8;REFERENCES;89
5;3 WHOLE HEART MODELING AND COMPUTER SIMULATION
;95
5.1;3.1 INTRODUCTION;95
5.2;3.2 METHODOLOGY IN 3D WHOLE HEART MODELING;96
5.2.1;3.2.1 HEART-TORSO GEOMETRY MODELING;96
5.2.2;3.2.2 INCLUSION OFSPECIALIZED CONDUCTION SYSTEM;97
5.2.3;3.2.3 INCORPORATING ROTATING FIBER DIRECTIONS;99
5.2.4;3.2.4 ACTIONPOTENTIALS AND ELECTROPHYSIOLOGIC PROPERTIES;103
5.2.5;3.2.5 PROPAGATION MODELS;108
5.2.5.1;3.2.5.1 Propagation model of Huygens' type
;109
5.2.5.2;3.2.5.2 Propagation of Hodgkin-Huxley type
;112
5.2.5.3;3.2.5.3 Propagation using Fitzllugh-Nagumo model;114
5.2.6;3.2.6 CARDIAC ELECTRIC SOURCES AND SURFACE ECG POTENTIALS;114
5.3;3.3 COMPUTER SIMULATIONS AND APPliCATIONS;117
5.3.1;3.3.1 SIMULATION OF THE NORMAL ELECTROCARDIOGRAM;117
5.3.2;3.3.2 SIMULATION OF ST-T WAVES IN PATHOLOGIC CONDITIONS;121
5.3.3;3.3.3 SIMULATION OF MYOCARDIAL INFARCTION;122
5.3.4;3.3.4 SIMULATION OF PACE MAPPING;124
5.3.5;3.3.5 SPIRAL WAVES-A NEW HYPOTHESIS OF VENTRICULAR FIBRILLATION
;124
5.3.6;3.3.6 SIMULATION OF ANTIARRHYTHMICDRUG EFFECT;124
5.4;3.4 DISCUSSION;125
5.5;REFERENCES;128
6;4 HEART SURFAC EELECTROCARDIOGRAPHIC INVERSE SOLUTIONS
;133
6.1;4.1 INTRODUCTION;133
6.1.1;4.1.1 THE RATIONALE FOR IMAGING CARDIAC ELECTRICAL FUNCTION;134
6.1.2;4.1.2 A HISTORICAL PERSPECTIVE;134
6.1.2.1;Microscopic: Action Potential;134
6.1.2.2;Macroscopic: Electrocardiogram;135
6.1.3;4.1.3 NOTATION AND CONVENTIONS;137
6.2;4.2 THE BASIC MODEL AND SOURCE FORMULATIONS;137
6.3;4.3 HEARTSURFACE INVERSE PROBLEMS METHODOLOGY;142
6.3.1;4.3.1 SOLUTION NONUNIQUENESS AND INSTABILITY;143
6.3.2;4.3.2 LINEAR ESTIMATIONAND REGULARIZATION;146
6.3.3;4.3.3 STOCHASTIC PROCESSES AND TIME SERIES OF INVERSE PROBLEMS;149
6.4;4.4 EPICARDIAL POTENTIAL IMAGING;152
6.4.1;4.4.1 STATISTICAL REGULARIZATION;152
6.4.2;4.4.2 TIKHONOV REGULARIZATIONAND ITS MODIFICATIONS;153
6.4.3;4.4.3 TRUNCATION SCHEMES;155
6.4.4;4.4.4 SPECIFIC CONSTRAINTS IN REGULARIZATION;156
6.4.5;4.4.5 NONLINEAR REGULARIZATIONMETHODOLOGY;157
6.4.6;4.4.6 ANAUGMENTED SOURCE FORMULATION;157
6.4.7;4.4.7 DIFFERENTMETHODS FOR REGULARIZATION PARAMETER SELECTION
;157
6.4.8;4.4.8 THE BODY SURFACE LAPLACIANAPPROACH;158
6.4.9;4.4.9 SPATIOTEMPORAL REGULARIZATION;159
6.4.10;4.4.10 RECENTIN VITRO AND IN VIVO WORK;160
6.5;4.5 ENDOCARDIAL POTENTIAL IMAGING;161
6.6;4.6 IMAGING FEATURES OF THE ACTION POTENTIAL;163
6.6.1;4.6.1 MYOCARDIAL ACTIVATION IMAGING;163
6.6.2;4.6.2 IMAGING OTHER FEATURES OF THE ACTION POTENTIAL;168
6.7;4.7 DISCUSSION;169
6.8;REFERENCES;170
7;5 THREE-DIMENSIONAL ELECTROCARDIOGRAPHIC TOMOGRAPHIC IMAGING
;175
7.1;5.1 INTRODUCTION;175
7.2;5.2 THREE-DIMENSIONAL MYOCARDIAL DIPOLE SOURCE IMAGING;176
7.2.1;5.2.1 EQUIVALENT MOVING DIPOLE MODEL;176
7.2.2;5.2.2 EQUIVALENT DIPOLE DISTRIBUTION MODEL;177
7.2.3;5.2.3 INVERSE ESTIMATION OF 3D DIPOLE DISTRIBUTION;177
7.2.4;5.2.4 NUMERICAL EXAMPLE OF 3D MYOCARDIAL DIPOLE SOURCE IMAGING
;179
7.3;5.3 THREE-DIMENSIONAL MYOCARDIAL ACTIVATION IMAGING;181
7.3.1;5.3.1 OUTLlNE OF THE HEART-MODEL BASED 3D ACTlVATION TIME IMAGING APPROACH
;181
7.3.2;5.3.2 COMPUTER HEART EXCITATION MODEL;182
7.3.3;5.3.3 PRELIMINARY CLASSIFICATION SYSTEM;183
7.3.4;5.3.4 NONLINEAR OPTIMIZATION SYSTEM;184
7.3.5;5.3.5 COMPUTER SIMULATION;185
7.3.6;5.3.6 DISCUSSION;188
7.4;5.4 THREE-DIMENSIONAL MYOCARDIAL TRANSMEMBRANE POTENTIAL IMAGING
;189
7.5;5.5 DISCUSSION;192
7.6;ACKNOWLEDGEMENT;193
7.7;REFERENCES;194
8;6 BODYSURFACE LAPLACIAN MAPPING OF BIOELECTRIC SOURCES
;197
8.1;6.1 INTRODUCTION;197
8.1.1;6.1.1 HIGH-RESOLUTION ECG AND EEG;197
8.1.2;6.1.2 BIOPHYSICAL BACKGROUND OF THE SURFACE LAPLACIAN;198
8.2;6.2 SURFACE LAPLACIAN ESTIMATION TECHNIQUES;200
8.2.1;6.2.1 LOCAL LAPLACIAN ESTIMATES;200
8.2.2;6.2.2 GLOBAL LAPLACIAN ESTIMATES;202
8.2.2.1;6.2.2.1 Spline interpolation of the surface geometry
;202
8.2.2.2;6.2.2.2 Spline interpolation of the surface potential distribution
;203
8.2.2.3;6.2.2.3 Determination of the spline parameters
;203
8.2.3;6.2.3 SURFACE LAPLACIAN BASED INVERSE PROBLEM;204
8.3;6.3 SURFACE LAPLACIAN IMAGING OF HEART ELECTRICAL ACTIVITY
;206
8.3.1;6.3.1 HIGH-RESOLUTION LAPLACIAN ECG MAPPING;206
8.3.2;6.3.2 PERFORMANCE EVALUATION OF THE SPLINE LAPLACIAN ECG;207
8.3.2.1;6.3.2.1 Effects of noise
;207
8.3.2.2;6.3.2.2 Effects of number of recording electrodes
;208
8.3.2.3;6.3.2.3 Effects of regularization
;209
8.3.2.4;6.3.2.4 Simulationin a realistic geometry heart-torso model;210
8.3.2.5;6.3.2.5 Spline Laplacian ECG mapping in Humans;211
8.3.3;6.3.3 SURFACE LAPLACIAN BASED EPICARDIAL INVERSE PROBLEM;213
8.4;6.4 SURFACE LAPLACIAN IMAGING OF BRAIN ELECTRICAL ACTIVITY
;214
8.4.1;6.4.1 HIGH-RESOLUTION LAPLACIAN EEG MAPPING;214
8.4.2;6.4.2 PERFORMANCE EVALUATION OF THE SPLINE LAPLACIAN EEG;214
8.4.2.1;6.4.2.1 Effects of noise
;214
8.4.2.2;6.4.2.2 Effects of number of recording electrodes
;215
8.4.2.3;6.4.2.3 Effects of regularization
;216
8.4.2.4;6.4.2.4 Simulation in a realistic geometry head model;218
8.4.2.5;6.4.2.5 Surface Laplacian imaging of visual evoked potential activity
;218
8.4.3;6.4.3 SURFACE LAPLACIAN BASED CORTICAL IMAGING;220
8.5;6.5 DISCUSSION;222
8.6;ACKNOWLEDGEMENT;223
8.7;REFERENCES;223
9;7 NEUROMAGNETIC SOURCE RECONSTRUCTION AND INVERSE MODELING
;227
9.1;7.1 INTRODUCTION;227
9.2;7.2 BRIEFSUMMARY OFNEUROMAGNETOMETER HARDWARE
;228
9.3;7.3 FORWARD MODELING;229
9.3.1;7.3.1 DEFINITIONS;229
9.3.2;7.3.2 ESTIMATION OF THE SENSOR LEAD FlEW;230
9.3.3;7.3.3 LOW-RANK SIGNALS AND THEIR PROPERTIES;233
9.4;7.4 SPATIAL FILTER FORMULATION AND NON-ADAPTIVE SPATIAL FILTER TECHNIQUES
;235
9.4.1;7.4.1 SPATIAL FILTER FORMULATION;235
9.4.2;7.4.2 RESOLUTION KERNEL;236
9.4.3;7.4.3 NON-ADAPTIVE SPATIAL FILTER;236
9.4.3.1;Minimum norm spatialfilter;236
9.4.3.2;Least-squares-based interpretation of the minimum-normmethods
;238
9.4.4;7.4.4 NOISE GAIN AND WEIGHT NORMALIZATION
;239
9.5;7.5 ADAPTIVE SPATIAL FILTER TECHNIQUES;240
9.5.1;7.5.1 SCALAR MINIMUM-VARIANCE-BASED BEAMFORMER TECHNIQUES;240
9.5.2;7.5.2 EXTENSION TO EIGENSPACE-PROJECTION BEAMFORMER;241
9.5.3;7.5.3 COMPARISON BETWEEN MINIMUM-VARIANCE AND EIGENSPACE BEAMFORMER TECHNIQUES
;242
9.5.4;7.5.4 VECTOR-TYPE ADAPTIVE SPATIAL FILTER;244
9.5.4.1;Problem of virtual source correlation
;244
9.5.4.2;A vector-extended minimum-variance beamformer
;244
9.5.4.3;Vector-extended Borgiotti-Kaplan beamformer;245
9.5.4.4;Extension to eigenspace-projection vector beamformer
;246
9.6;7.6 NUMERICAL EXPERIMENTS: RESOLUTION KERNEL COMPARISON BETWEENADAPTIVEAND NON-ADAPTIVE SPATIAL FILTERS
;246
9.6.1;7.6.1 RESOLUTION KERNEL FOR THE MINIMUM-NORM SPATIAL FILTER;246
9.6.2;7.6.2 RESOLUTION KERNEL FOR THE MINIMUM-VARIANCE ADAPTIVE SPATIAL FILTER
;248
9.7;7.7 NUMERICAL EXPERIMENTS: EVALUATION OF ADAPTIVE BEAMFORMER PERFORMANCE
;249
9.7.1;7.7.1 DATA GENERATION AND RECONSTRUCTION CONDITION
;249
9.7.2;7.7.2 RESULTS FROM MINIMUM-VARIANCE VECTOR BEAMFORMER;252
9.7.3;7.7.3 RESULTS FROM THE VECTOR-EXTENDED BORGIOTT/-KAPLAN BEAMFORMER
;252
9.7.4;7.7.4 RESULTS FROM THE EIGENSPACE PROJECTED VECTOR-EXTENDED BORGIOTTI- KAPLAN BEAMFORMER
;252
9.8;7.8 APPLICATION OF ADAPTIVE SPATIAL FILTER TECHNIQUE TO MEG DATA
;257
9.8.1;7.8.1 APPLICATION TO AUDITORY-SOMATOSENSORY COMBINED RESPONSE;257
9.8.2;7.8.2 APPLICATION TO SOMATOSENSORY RESPONSE: HIGH-RESOLUTION IMAGING EXPERIMENTS
;259
9.9;ACKNOWLEDGMENTS;260
9.10;REFERENCES;261
10;8 MULTIMODAL IMAGING FROM NEUROELECTROMAGNETIC AND FUNCTIONAL MAGNETIC RESONANCE RECORDINGS
;265
10.1;8.1 INTRODUCTION;265
10.2;8.2 GENERALITIES ON FUNCTIONAL MAGNETIC RESONANCE IMAGING
;266
10.2.1;8.2.1 BLOCK-DESIGN AND EVENT-RELATED fMRI;268
10.3;8.3 INVERSE TECHNIQUES;268
10.3.1;8.3.1 ACQUISITION OF VOLUME CONDUCTOR GEOMETRY;269
10.3.2;8.3.2 DIPOLELOCALIZATION TECHNIQUES;270
10.3.3;8.3.3 CORTICAL IMAGING;271
10.3.4;8.3.4 DISTRIBUTED LINEAR INVERSE ESTIMATION;273
10.4;8.4 MULTIMODAL INTEGRATION OF EEG, MEG AND FMRI DATA;275
10.4.1;8.4.1 VISIBLE AND INVISIBLE SOURCES;275
10.4.2;8.4.2 EXPERIMENTAL DESIGNAND CO-REGISTRATION ISSUES;276
10.4.2.1;8.4.2.a Experimental design;276
10.4.2.2;8.4.2.b Co-registration
;277
10.4.3;8.4.3 INTEGRATION OF EEG AND MEG DATA;277
10.4.4;8.4.4 FUNCTIONAL HEMODYNAMIC COUPLING AND INVERSE ESTIMATION OF SOURCE ACTIVITY
;281
10.4.4.1;8.4.4.a Multimodal integration of EEG/MEG and fMRI data with dipole localization techniques
;281
10.4.4.2;8.4.4.b Multimodal integration of EEG/MEG and fMRI data with distributed model by using diagonal source metric
;284
10.4.4.3;8.4.4.c Multimodal integration of EEG/MEG and fMRI data with distributed model by using full source metric
;285
10.4.4.4;8.4.4.d Application of the multimodal EEG-fMRI integration techniques to the estimation of sources of self-paced movements
;286
10.5;8.5 DISCUSSION;289
10.6;ACKNOWLEDGMENTS;290
10.7;REFERENCES;290
11;9 THE ELECTRICAL CONDUCTIVITY OF LIVING TISSUE: A PARAMETER IN THE BIOELECTRICAL INVERSE PROBLEM
;295
11.1;9.1 INTRODUCTION;295
11.1.1;9.1.1 SCOPE OF THISCHAPTER;296
11.1.2;9.1.2 AMBIGUITY OF THE EFFECTIVE CONDUCTIVITY;297
11.1.3;9.1.3 MEASURING THE EFFECTIVE CONDUCTIVITY;298
11.1.4;9.1.4 TEMPERATURE DEPENDENCE;301
11.1.5;9.1.5 FREQUENCY DEPENDENCE;301
11.1.5.1;9.1.5.1 Impact of the frequency dependence on the EEG
;303
11.2;9.2 MODELS OF HUMAN TISSUE;303
11.2.1;9.2.1 COMPOSITES OF HUMAN TISSUE;303
11.2.1.1;9.2.1.1 Cells;303
11.2.1.2;9.2.1.2 Volume fraction occupied by cells;305
11.2.1.3;9.2.1.3 The extracellular fluid
;305
11.2.2;9.2.2 CONDUCTIVITIES OF COMPOSITES OF HUMAN TISSUE;306
11.2.2.1;9.2.2.1 Effective conductivity of a sphericalcell
;307
11.2.2.2;9.2.2.2 Effective conductivity of a cylindrical cell
;308
11.2.2.3;9.2.2.3 Conductivity of extracellular fluid
;309
11.2.3;9.2.3 MAXWELL'S MIXTURE EQUATION;310
11.2.3.1;9.2.3.1 A dilute solution of spheres
;311
11.2.3.1.1;9.2.3.1.a. Blood;313
11.2.4;9.2.4 ARCHIE'S LAW;314
11.2.4.1;9.2.4.1 Ellipsoidal particles with the sameorientation
;315
11.2.4.1.1;9.2.4.1.a. Fat;315
11.2.4.1.2;9.2.4.1.b. Skeletal muscles;315
11.2.4.1.3;9.2.4.1.c. Cardiac tissue;316
11.2.4.2;9.2.4.2 Randomly orientated ellipsoidal particles
;317
11.2.4.2.1;9.2.4.2.a. Blood;318
11.2.4.3;9.2.4.3 Cells of different shape
;319
11.2.4.3.1;9.2.4.3.a. Gray matter
;319
11.2.4.4;9.2.4.4 Clustered cells;320
11.2.4.4.1;9.2.4.4.a. Blood;320
11.2.4.4.2;9.2.4.4.b. Liver;320
11.3;9.3 LAYERED STRUCTURES;321
11.3.1;9.3.1 THE SCALP;321
11.3.2;9.3.2 THE SKULL;322
11.3.3;9.3.3 A LAYER OF SKELETAL MUSCLE;324
11.4;9.4 COMPARTMENTS;325
11.4.1;9.4.1 USING IMPLANTED ELECTRODES;325
11.4.2;9.4.2 COMBINING MEASUREMENTS OF THE POTENTIAL AND THE MAGNETIC FlEW
;326
11.4.3;9.4.3 ESTIMATION OF THE EQUIVALENT CONDUCTIVITY USING IMPEDANCE TOMOGRAPHY
;326
11.5;9.5 UPPER AND LOWER BOUNDS;327
11.5.1;9.5.1 WHITE MATTER;328
11.5.2;9.5.2 THE FETUS;328
11.6;9.6 DISCUSSION;330
11.7;REFERENCES;330
12;INDEX;335