UID:
almahu_9949602276602882
Format:
1 online resource (398 pages)
Edition:
1st ed.
ISBN:
9783030212933
Note:
Intro -- Preface to Computation Human Models and Brain Modeling: EMBC 2018 -- Contents -- Part I: Human Body Models for Non-invasive Stimulation -- Chapter 1: SimNIBS 2.1: A Comprehensive Pipeline for Individualized Electric Field Modelling for Transcranial Brain Stimulation -- 1.1 Introduction -- 1.2 Overview of the SimNIBS Workflow -- 1.2.1 Structural Magnetic Resonance Imaging Scans -- 1.2.2 Volume Conductor Modelling -- 1.2.3 Simulation Setup -- 1.2.4 Finite Element Method Calculations -- 1.2.5 Mapping Fields -- 1.3 Practical Examples and Use Cases -- 1.3.1 Hello SimNIBS: How to Process a Single Subject -- Generating the Volume Conductor Model -- Setting Up a Simulation -- Visualizing Fields -- 1.3.2 Advanced Usage: Group Analysis -- Head Meshing -- Write a Python or MATLAB Script -- Visualizing Results -- 1.4 The Accuracy of Automatic EEG Positioning -- 1.5 Conclusion -- References -- Chapter 2: Finite Element Modelling Framework for Electroconvulsive Therapy and Other Transcranial Stimulations -- 2.1 Introduction -- 2.2 Methods -- 2.2.1 Image Pre-processing -- Bias Field Correction -- Image Registration -- Image Segmentation -- Manual Segmentation -- Surface Smoothing -- Cortical Structure Labelling -- Challenges and Tips in Segmentation -- 2.2.2 White Matter Anisotropy -- 2.2.3 FE Meshing -- 2.2.4 Physics and Property Settings -- Tissue Conductivity -- Electrode Placement -- Other Boundary Conditions -- Numerical Solver Settings -- 2.3 Simulation Results -- 2.3.1 Electric Feld for Three ECT Electrode Configurations -- 2.4 Discussion -- 2.4.1 Model Extensions -- Subject-Specific Tissue Conductivity -- 2.5 Conclusion -- References -- Chapter 3: Estimates of Peak Electric Fields Induced by Transcranial Magnetic Stimulation in Pregnant Women as Patients or Operators Using an FEM Full-Body Model -- 3.1 Introduction -- 3.2 Methods and Materials.
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3.2.1 Existing Computational Models of a Pregnant Woman -- 3.2.2 Construction of FEM (CAD) Full-Body Pregnant Woman Model and Model Topology -- 3.2.3 Tissue Properties -- 3.3 Study Design -- 3.3.1 TMS Coil -- 3.3.2 Pulse Form and Duration -- 3.3.3 Coil Current -- 3.3.4 Coil Positions -- 3.3.5 Accidental Coil Discharge -- 3.3.6 Frequency-Domain Computations -- 3.3.7 Time-Domain Computations -- 3.3.8 Finding Maximum Peak Current Density/Electric Field Strength in Individual Tissues -- 3.4 Results: Pregnant Patient -- 3.4.1 Qualitative Behavior of Induced Currents in the Body of a Pregnant Patient at Different Frequencies (Pulse Durations) -- 3.4.2 Quantitative Results for Maximum Peak Electric Field at One SMT Unit -- 3.4.3 Comparison with the Recommended Safe Value of Electric Field -- 3.4.4 Observations from the Quantitative Solution -- 3.4.5 Comparison with Upper Analytical Estimate for Electric Fields/Eddy Currents -- 3.4.6 Using the Analytical Estimate for Predicting Maximum Fields for Different Patients -- 3.5 Results: Pregnant Operator and Accidental Coil Discharge -- 3.5.1 Quantitative Results for Maximum Peak Electric Field at One SMT Unit -- 3.5.2 Accidental Coil Discharge -- 3.6 Conclusion -- Japanese Virtual Model (JVM) Finite-Element Model Version 1.1 (6 months) -- References -- Chapter 4: Electric Field Modeling for Transcranial Magnetic Stimulation and Electroconvulsive Therapy -- 4.1 Introduction -- 4.2 Modeling Methods -- 4.2.1 ECT Modeling -- 4.2.2 rTMS Modeling -- 4.2.3 sTMS Modeling -- 4.3 Results -- 4.3.1 Electric Field Induced by ECT -- 4.3.2 Electric Field Induced by rTMS -- 4.3.3 Electric Field Induced by sTMS -- 4.4 Discussion -- 4.5 Conclusion -- References -- Chapter 5: Design and Analysis of a Whole-Body Noncontact Electromagnetic Subthreshold Stimulation Device with Field Modulation Targeting Nonspecific Neuropathic Pain.
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5.1 Introduction -- 5.2 Materials and Methods -- 5.2.1 Suprathreshold Versus Subthreshold Stimulation -- 5.2.2 Concept of the Magnetic Stimulator. Two-Dimensional Analytical Solution for Solenoidal E-Field -- 5.2.3 Three-Dimensional Coil Resonator Design. Solenoidal E-Field -- 5.2.4 Solenoidal Electric Field Distribution with and without a Simple Conducting Object -- 5.2.5 Contribution of Unpaired Electric Charges -- 5.2.6 Power Amplifier/Driver -- 5.2.7 Coupling and Matching the Power Amplifier to the Resonating Coil -- 5.2.8 Tuning Procedure -- 5.2.9 Coil Assembly, Device Setup, and Operation -- 5.2.10 Quality Factor of the Resonator and the Magnetic Field Strength -- 5.3 Device Safety Estimates -- 5.3.1 Peripheral Nervous System (PNS) Stimulation Threshold -- 5.3.2 Specific Absorption Rate (SAR) -- 5.3.3 Method of Analysis -- 5.3.4 Electric Field Levels -- 5.3.5 SAR Levels -- 5.4 Discussion -- 5.4.1 Efficacy of Stimulation -- 5.4.2 Integrated Effect of Stimulation -- 5.4.3 Operation as an EMAT -- 5.4.4 Variation of Resonant Frequency -- 5.5 Conclusion -- Appendix A: Derivation of Eq. (5.7) and Coil Q -- References -- Part II: Tumor Treating Fields (TTFs) -- Chapter 6: Simulating the Effect of 200 kHz AC Electric Fields on Tumour Cell Structures to Uncover the Mechanism of a Cancer Therapy -- 6.1 Introduction -- 6.2 Overview of the Models -- 6.2.1 Why Computer Modelling? -- 6.2.2 Axiomatizing the Underlying Systems Level -- 6.3 Clues to the Mechanisms Are Constraints on the Models -- 6.4 Candidates for TTFields Mechanisms -- 6.5 Disruption Metrics Derived from Signal-to-Noise Ratio -- 6.6 Models and Results -- 6.6.1 MT Resonance -- Electromechanical Model -- 6.6.2 MT Conductivity -- MT as a Multi-Layered Cable -- 6.6.3 C-Termini State Disruption -- Model Calibration -- 6.6.4 Kinesin Walk Diffusion Hypothesis -- 6.7 Conclusion -- References.
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Chapter 7: Investigating the Connection Between Tumor-Treating Fields Distribution in the Brain and Glioblastoma Patient Outcomes. A Simulation-Based Study Utilizing a Novel Model Creation Technique -- 7.1 Introduction -- 7.2 Methods -- 7.2.1 MRI Data Used for the Study -- 7.2.2 Image Preprocessing -- 7.2.3 MRI Full Head Completion -- 7.2.4 High-Resolution Reconstruction -- 7.2.5 Background Noise Reduction -- 7.2.6 Patient Model Creation -- 7.2.7 Placement of Transducer Arrays on the Model -- Automatic Identification of Landmarks and Determination of the Array Positions -- Positioning of Anchor Points to Assist with Array Placement -- Finding the Center of All Disks in an Array -- Creating Cylinders Representing the Ceramic Disks and the Medical Gel -- 7.2.8 Simulations -- 7.2.9 Analysis -- 7.3 Results -- 7.4 Discussion and Conclusion -- References -- Chapter 8: Insights from Computer Modeling: Analysis of Physical Characteristics of Glioblastoma in Patients Treated with Tumor-Treating Fields -- 8.1 Introduction -- 8.2 TTFields Is Another Treatment Modality from the Electromagnetic Spectrum -- 8.3 Quantifying Electric Field Delivery in the Brain -- 8.4 Clinical Outcome from TTFields Treatment -- 8.5 Conclusion -- References -- Chapter 9: Advanced Multiparametric Imaging for Response Assessment to Tumor-Treating Fields in Patients with Glioblastoma -- 9.1 Introduction -- 9.2 Tumor-Treating Fields: Scientific Basis -- 9.3 Tumor-Treating Fields: Clinical Application in GBM Patients -- 9.4 Tumor-Treating Fields: Advanced Neuroimaging Techniques -- 9.5 Tumor-Treating Fields: Initial Experience -- 9.6 Conclusion -- References -- Chapter 10: Estimation of TTFields Intensity and Anisotropy with Singular Value Decomposition: A New and Comprehensive Method for Dosimetry of TTFields -- 10.1 Introduction.
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10.2 Preparation of Computational Models and Calculation of the Electrical Field -- 10.2.1 Laplace's Equation: The Electro-quasistatic Approximation of Maxwell's Equations -- 10.2.2 The Finite Element Framework for TTFields -- 10.2.3 Creation of Personalized Head Models -- 10.2.4 Placement of Transducer Arrays -- 10.2.5 Assignment of Tissue Conductivity -- 10.3 Dosimetry of TTFields -- 10.3.1 The Problem -- 10.3.2 The Basic Framework -- 10.3.3 Estimation of the TTFields Intensity -- 10.3.4 Estimating the Spatial Correlation of TTFields Using the Fractional Anisotropy (FA) Measure -- 10.3.5 Step-by-Step Framework for Calculation of FA and Eavr -- 10.4 Results from Example Calculations -- 10.4.1 Topographical Distributions of FA and Eavr -- 10.4.2 Variations in FA and Eavr for Different Array Layouts -- 10.4.3 Optimization of the TTFields Activation Cycle to Reduce Unwanted Field Anisotropy -- 10.5 Summary -- References -- Chapter 11: The Bioelectric Circuitry of the Cell -- 11.1 Introduction -- 11.2 Ion Channel Conduction Effects -- 11.3 Actin Filament Conductivity -- 11.4 Microtubule Conductivity -- 11.5 Conclusions -- References -- Part III: Electromagnetic Safety -- Chapter 12: Brain Haemorrhage Detection Through SVM Classification of Electrical Impedance Tomography Measurements -- 12.1 Introduction -- 12.2 Technologies -- 12.2.1 Electrical Impedance Tomography -- 12.2.2 Support Vector Machine (SVM) Classifiers -- 12.2.3 Computational Modelling Techniques -- 12.3 SVM Applied to Raw EIT Measurement Frames with Analysis of the Effect of Individual Variables on SVM Performance -- 12.3.1 The Effect of Noise -- 12.3.2 Effect of Bleed Location -- 12.3.3 Effect of Bleed Size -- 12.3.4 Effect of Electrode Positioning -- 12.3.5 Effect of Normal Variation in Between-Patient Anatomy -- 12.4 SVM Applied to EIT Processed Measurement Frames.
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12.4.1 Radial Basis Function Kernel Compared to Linear Kernel.
Additional Edition:
Print version: Makarov, Sergey Brain and Human Body Modeling Cham : Springer International Publishing AG,c2019 ISBN 9783030212926
Language:
English
Keywords:
Electronic books.
