[Biological and Medical Physics, Biomedical Engineering] Biomechanics of the Brain ||

Chapter 1: Introduction References Chapter 2: Introduction to Brain Anatomy 2.1 Introduction 2.2 Structural (Gross) Neuroanatomy 2.2.1 Brain Parcellation 2.2.2 Cortical Areas 2.2.2.1 Lateral Surface 2.2.2.2 Medial Surface 2.2.2.3 Inferior Surface 2.2.3 Deep Gray Nuclei 2.2.4 Ventricular System 2.2.5 Sectional Neuroanatomy 2.2.6 Main Stereotactic Target Structures 2.2.7 Functional Areas 2.3 Vascular Neuroanatomy 2.3.1 Arterial System 2.3.1.1 Parcellation of Arterial System 2.3.1.2 Anterior Cerebral Artery 2.3.1.3 Middle Cerebral Artery 2.3.1.4 Posterior Cerebral Artery 2.3.1.5 Circle of Willis 2.3.2 Venous System 2.3.2.1 Parcellation of Venous System 2.3.2.2 Dural sinuses 2.3.2.3 Cerebral Veins 2.3.3 Vascular Variants 2.4 Connectional Neuroanatomy 2.4.1 Commissural Tracts 2.4.2 Association Tracts 2.4.3 Projection Tracts 2.5 Summary References Neuroanatomy Textbooks Print Brain Atlases Electronic Brain Atlases Others Chapter 3: Introduction to Brain Imaging 3.1 Structural and Functional Brain Imaging: A Comparative Overview of Techniques 3.1.1 Magnetic Resonance Imaging-Based Brain Imaging Techniques 3.1.1.1 Magnetic Resonance Imaging 3.1.1.2 Functional Magnetic Resonance Imaging (fMRI) 3.1.1.3 Diffusion Tensor Imaging 3.1.2 Electrophysiological Brain Imaging Techniques 3.1.2.1 Electroencephalography and Magnetoencephalography 3.1.3 Multimodal Imaging 3.1.3.1 Simultaneous fMRI and EEG 3.2 Clinical Applications of Brain Imaging for Image-Guided Neurosurgery in Epilepsy and Brain Tumor Patients 3.2.1 Structural MRI 3.2.2 Presurgical fMRI Mapping 3.2.2.1 Functional Mapping of Sensory and Motor Systems 3.2.2.2 Functional Mapping of Cognitive Systems 3.2.2.3 Measuring Language and Memory Hemispheric Lateralization 3.2.2.4 Resting State fMRI 3.2.2.5 Functional Mapping in Patients with Malignant Brain Tumors 3.2.3 Presurgical DTI Mapping 3.2.4 EEG and MEG Mapping 3.3 Summary and Conclusions References Chapter 4: Brain Tissue Mechanical Properties 4.1 Introduction 4.2 Shear Properties of Brain Tissue 4.2.1 Linear Viscoelastic Properties 4.2.1.1 Oscillatory Loading 4.2.1.2 Relaxation 4.2.1.3 Other Measurements 4.2.2 Non-linear Viscoelastic Properties 4.2.2.1 Oscillatory Response 4.2.2.2 Relaxation 4.2.2.3 Constant Loading Rate 4.2.2.4 Other Test Types 4.3 Compressive Properties of Brain Tissue 4.4 Tensile Properties of Brain Tissue 4.5 Constitutive Models for Brain Tissue 4.6 Discussion 4.6.1 Mechanical Characteristics of Brain Tissue 4.6.2 Methodological Considerations 4.7 Future Directions 4.8 Conclusions References Chapter 5: Modeling of the Brain for Injury Simulation and Prevention 5.1 Introduction 5.2 Essentials of a Finite Element Head Model 5.2.1 Selection of Anatomical Features 5.2.2 FE Mesh Quality 5.2.3 Numerical Convergence and Hourglass Energy 5.2.4 Boundary Conditions 5.2.5 Types of Injury To Be Simulated 5.3 Validation of Simulation Results 5.4 Revamp FE Modeling of Human Head 5.5 Conclusions References Chapter 6: Biomechanical Modeling of the Brain for Computer-Assisted Neurosurgery 6.1 Introduction 6.1.1 Neurosurgical Simulation for Operation Planning, Surgeon Training and Skill Assessment 6.1.2 Image Registration in Image-Guided Neurosurgery 6.2 Biomechanics of the Brain-Modelling Issues 6.2.1 Geometry 6.2.2 Boundary Conditions 6.2.3 Loading 6.2.4 Models of Mechanical Properties of Brain Tissue 6.2.5 Model Validation 6.3 Application Example: Computer Simulation of the Brain Shift 6.3.1 Generation of Computational Grids: From Medical Images to Finite Element Meshes 6.3.2 Loading, Boundary Conditions and Brain Tissue Constitutive Model 6.3.3 Results and Validation 6.3.4 Discussion 6.4 Conclusions References Chapter 7: Dynamics of Cerebrospinal Fluid: From Theoretical Models to Clinical Applications 7.1 Introduction 7.2 Physiology and Pathophysiology 7.3 Model of CSF Circulation 7.4 Infusion Test 7.5 Overnight ICP Monitoring 7.6 Compensatory Parameters Derived from the Infusion Test and ICP Monitoring 7.6.1 R CSF & P b 7.6.2 Elastance Coefficient (or Elasticity) 7.6.3 Pressure–Volume Curve and Its Hysteresis 7.6.4 ICP Waveform Components 7.6.5 Derived Parameters, RAP Index 7.7 Pulsatile Flow of CSF: Phase Contrast MRI Perspective 7.8 Pulsatile CSF Flow-Basic Models 7.9 Methodology of Phase Contrast MRI 7.10 Clinical Applications 7.10.1 Differentiation Between Brain Atrophy and Normal Pressure Hydrocephalus 7.10.2 Noncommunicating and Acute Communicating Hydrocephalus 7.10.3 Testing of CSF Dynamics in Shunted Patients 7.10.4 Phase-Coded MRI in Clinical Practice 7.11 Conclusion References Chapter 8: Computational Fluid Dynamics for the Assessment of Cerebrospinal Fluid Flow and Its Coupling with Cerebral Blood Flow 8.1 Introduction 8.2 Procedural Steps in CFD Modeling of CSF Dynamics 8.2.1 Obtaining the Model Domain 8.2.2 Spatial Discretization 8.2.3 Obtaining Boundary Conditions 8.2.4 Calculating the Flow 8.3 Existing CFD Models 8.3.1 Ventricular Space 8.3.2 Subarachnoid Space 8.3.2.1 Spinal Subarachnoid Space 8.3.2.2 Cranial Subarachnoid Space 8.3.3 Perivascular Space 8.4 Conclusion References Chapter 9: Algorithms for Computational Biomechanics of the Brain 9.1 Introduction 9.2 Algorithms for Injury Simulation 9.3 Algorithms for Surgery Simulation 9.4 Algorithms for Neurosurgery Modeling 9.4.1 Dynamic Relaxation Algorithm 9.4.1.1 Dynamic Relaxation Algorithm: Maximum Eigenvalue A m and Mass Matrix 9.4.1.2 Dynamic Relaxation Algorithm: Estimation of the Minimum Eigenvalue A 0 9.4.1.3 Dynamic Relaxation Algorithm: Termination Criteria 9.5 Element Formulation for Finite Element Algorithms for Surgery Simulation and Neurosurgery Modeling 9.5.1 Volumetric Locking 9.5.2 Stability of Under-Integrated Hexahedral Elements; Hourglassing 9.6 Modeling of the Brain–Skull Interactions for Image-Guided Neurosurgery: Efficient Finite Sliding Contact Algorithm 9.7 Alternatives to Finite Element Method for Image-Guided Neurosurgery and Surgery Simulation: Meshless Algorithms 9.7.1 Meshless Total Lagrangian Explicit Dynamics (MTLED): Algorithm Description 9.8 Real-Time Computations without Supercomputers: Increasing Computation Speed Through Algorithm Implementation on Graphics Processing Unit (GPU) 9.9 Algorithm Verification 9.9.1 Hourglass Control 9.9.2 Volumetric Locking 9.9.3 Dynamic Relaxation: Steady-State Computation 9.9.4 Brain–Skull Interface: Contact Algorithm 9.9.5 Meshless Total Lagrangian Explicit Dynamics (MTLED) Algorithm 9.10 Conclusions References Index The mechanical properties of living tissues continue to be the major topic of biomechanical investigations. Most researchers have investigated load-bearing tissues, such as bones, ligaments, muscles and other components of the musculoskeletal system, blood vessels (and blood), lungs, skin and hair. Until recently, very soft tissues of organs whose role has little or nothing to do with transmitting mechanical loads have been outside the scope of the mainstream biomechanical research. These "(Bneglected" organs include the liver, kidneys, prostate and other abdominal organs, and especially the brain. Increased interest in the biomechanics of soft tissues, particularly the brain, as evidenced by the increased number of publications in this area, has motivated this effort to summarize recent developments. Biomechanics of the Brain will take the reader to the forefront of current research. Covering topics from brain anatomy and imaging to sophisticated methods of modeling brain injury and neurosurgery, to the cutting edge methods in analyzing cerebrospinal fluid and blood flow, this book is the first comprehensive reference in the field of biomechanics of the brain. Experienced biomechanics researchers as well as those new to the field will find parts of this book useful Biomechanics of the Brain will present an introduction to brain anatomy for engineers and scientists. Experimental techniques such as brain imaging and brain tissue mechanical property measurement will be discussed, as well as computational methods for neuroimage analysis and modeling of brain deformations due to impacts and neurosurgical interventions. Brain trauma between the different sexes will be analyzed. Applications will include prevention and diagnosis of traumatic injuries, such as shaken baby syndrome, neurosurgical simulation and neurosurgical guidance, as well as brain structural disease modeling for diagnosis and prognosis. This book will be the first book on brain biomechanics. It will provide a comprehensive source of information on this important field for students, researchers, and medical professionals in the fields of computer-aided neurosurgery, head injury, and basic biomechanics. With contributions from scientists at major institutions, this book presents an introduction to brain anatomy for engineers and scientists. It provides, for the first time, a comprehensive resource in the field of brain biomechanics.