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E-raamat: Multiscale Biomechanical Modeling of the Brain

Edited by (CAVS Chair Professor, Department of Mechanical Engineering, Mississippi State University, USA), Edited by (Deputy Project Scientist, NASA HRP Cross-Cutting Computational Modeling Project, Universities Space Research Association, USA)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 27-Oct-2021
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128181454
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Multiscale Biomechanical Modeling of the BrainSuurem pilt
  • Formaat: PDF+DRM
  • Ilmumisaeg: 27-Oct-2021
  • Kirjastus: Academic Press Inc
  • Keel: eng
  • ISBN-13: 9780128181454
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Multiscale Biomechanical Modeling of the Brain discusses the constitutive modeling of the brain at various length scales (nanoscale, microscale, mesoscale, macroscale and structural scale). In each scale, the book describes the state-of-the- experimental and computational tools used to quantify critical deformational information at each length scale. Then, at the structural scale, several user-based constitutive material models are presented, along with real-world boundary value problems. Lastly, design and optimization concepts are presented for use in occupant-centric design frameworks. This book is useful for both academia and industry applications that cover basic science aspects or applied research in head and brain protection.

The multiscale approach to this topic is unique, and not found in other books. It includes meticulously selected materials that aim to connect the mechanistic analysis of the brain tissue at size scales ranging from subcellular to organ levels.

  • Presents concepts in a theoretical and thermodynamic framework for each length scale
  • Teaches readers not only how to use an existing multiscale model for each brain but also how to develop a new multiscale model
  • Takes an integrated experimental-computational approach and gives structured multiscale coverage of the problems
Contributors xi
Preface xiii
Chapter 1 The multiscale nature of the brain and traumatic brain injury
7(20)
M.A. Murphy
A. Vo
1.1 Introduction
1(1)
1.2 The brain's multiscale structure
2(11)
1.2.1 Gross anatomy
3(5)
1.2.2 Microanatomy
8(5)
1.3 The multiscale nature of TBI
13(8)
1.3.1 Multiscale injury mechanisms
14(1)
1.3.2 Types of injury
15(1)
1.3.3 Examples of injuries
16(1)
1.3.4 Neurobehavioral sequelae
17(1)
1.3.5 TBI research methods
18(3)
1.4 Summary
21(6)
References
21(6)
Chapter 2 Introduction to multiscale modeling of the human brain
27(12)
Raj K. Prabhu
Mark F. Horstemeyer
2.1 Introduction
27(1)
2.2 Constitutive modeling of the brain
27(5)
2.3 Brain tissue experiments used for constitutive modeling calibration
32(1)
2.4 Modeling summary of upcoming chapters in the book
33(1)
2.5 Summary
34(5)
References
34(5)
Chapter 3 Density functional theory and bridging to classical interatomic force fields
39(14)
D. Dickel
S. Mun
M. Baskes
S. Gwaltney
Raj K. Prabhu
Mark F. Horstemeyer
3.1 Introduction
39(3)
3.1.1 Why quantum mechanics?
39(2)
3.1.2 Physical chemistry of biomechanical systems
41(1)
3.2 Density functional theory
42(1)
3.3 Downscaling requirements of classical force field atomistic models
43(3)
3.3.1 Upscaling properties
44(2)
3.4 Sample atomistic force fields formalism and development of an interatomic potential for hydrocarbons
46(4)
3.4.1 MEAMBO
46(1)
3.4.2 Calibration of the MEAMBO potential
47(1)
3.4.3 Parameterization of the interatomic potential
48(1)
3.4.4 Validation of the interatomic force fields
49(1)
3.5 Summary
50(3)
References
51(2)
Chapter 4 Modeling nanoscale cellular structures using molecular dynamics
53(24)
M.A. Murphy
Mark F. Horstemeyer
Raj K. Prabhu
4.1 Introduction
53(4)
4.2 Methods
57(12)
4.2.1 Molecular dynamics simulation method
57(1)
4.2.2 Atomic force fields
57(2)
4.2.3 Simulation ensembles of atoms
59(1)
4.2.4 Boundary conditions
60(3)
4.2.5 Current simulation details
63(1)
4.2.6 Molecular dynamics analysis methods for the phospholipid bilayer (neuron membrane)
64(5)
4.3 Results and discussion for the phospholipid bilayer (neuron membrane)
69(3)
4.3.1 Stress-strain and damage response
70(1)
4.3.2 Membrane failure limit diagram
70(2)
4.4 Summary
72(5)
Acknowledgments
73(1)
References
73(4)
Chapter 5 Microscale mechanical modeling of brain neuron(s) and axon(s)
77(8)
Mark F. Horstemeyer
A. Bakhtiarydavijani
Raj K. Prabhu
5.1 Introduction
77(1)
5.2 Modeling microscale neurons
78(3)
5.2.1 Modeling neurons
79(2)
5.2.2 Modeling mechanical behavior of axons
81(1)
5.3 Summary and future
81(4)
References
82(3)
Chapter 6 Mesoscale finite element modeling of brain structural heterogeneities and geometrical complexities
85(18)
A. Bakhtiarydavijani
R. Miralami
A. Dobbins
Mark F. Horstemeyer
Raj K. Prabhu
6.1 Introduction
85(2)
6.1.1 Modeling length scale
86(1)
6.2 Methods
87(6)
6.2.1 Computational methods for properties
87(5)
6.2.2 Model validation and boundary conditions
92(1)
6.3 Results and discussion
93(7)
6.3.1 Geometrical complexities
94(6)
6.4 Summary
100(3)
References
101(2)
Chapter 7 Modeling mesoscale anatomical structures in macroscale brain finite element models
103(16)
T. Wu
J.S. Giudice
A. Alshareef
M.B. Panzer
7.1 Introduction
103(1)
7.2 Macroscale brain finite element model
103(2)
7.3 Mesoscale anatomical structures and imaging techniques
105(2)
7.4 The importance of structural anisotropy in macroscale models of TBI
107(1)
7.5 Material-based method
108(1)
7.6 Structure-based method
109(1)
7.7 Summary and future perspectives
110(9)
References
113(6)
Chapter 8 A macroscale mechano-physiological internal state variable (MPISV) model for neuronal membrane damage with subscale microstructural effects
119(20)
A. Bakhtiarydavijani
M.A. Murphy
Raj K. Prabhu
T.R. Fonville
Mark F. Horstemeyer
8.1 Introduction
119(2)
8.1.1 Definitions
120(1)
8.2 Membrane disruption
121(1)
8.3 Development of damage evolution equation
122(4)
8.3.1 Pore number density rate
123(2)
8.3.2 Pore growth rate
125(1)
8.3.3 Pore resealing
126(1)
8.4 Garnering data from molecular dynamics simulations
126(1)
8.5 Calibration of the mechano-physiological internal state variable damage rate equations
127(1)
8.6 Sensitivity analysis of damage model at this length scale
128(1)
8.7 Comparison of model with cell culture studies
129(4)
8.8 Discussion
133(2)
8.9 Summary
135(4)
References
135(4)
Chapter 9 MRE-based modeling of head trauma
139(14)
Amit Madhukar
Martin Ostoja-Starzewski
9.1 Introduction
139(1)
9.2 Model formulation
140(4)
9.2.1 MRE acquisition and inversion
140(1)
9.2.2 Finite element mesh generation
141(2)
9.2.3 Material properties
143(1)
9.2.4 Experimental verification
144(1)
9.3 Results and discussion
144(6)
9.4 Conclusion
150(3)
References
150(3)
Chapter 10 Robust concept exploration of driver's side vehicular impacts for human-centric crashworthiness
153(24)
A.B. Nellippallil
P.R. Berthelson
L. Peterson
Raj K. Prabhu
10.1 Frame of reference
153(2)
10.2 Problem definition
155(1)
10.3 Adapted CEF for robust concept exploration
156(2)
10.4 Head and neck injury criteria-based robust design of vehicular impacts
158(13)
10.4.1 Clarification of design task-Step A
158(1)
10.4.2 Design of experiments-Step B
159(1)
10.4.3 Finite element car crash simulations for predicting injury response-Step C
160(2)
10.4.4 Building surrogate models-Step D
162(2)
10.4.5 Formulation of robust design cDSP-Step E
164(4)
10.4.6 Formulating the design scenarios, exercising the cDSP and exploration of solution space-Step E
168(3)
10.5 Future: correlate human brain injury to vehicular damage
171(1)
10.6 Summary
172(5)
References
172(5)
Chapter 11 Development of a coupled physical-computational methodology for the investigation of infant head injury
177(16)
M.D. Jones
G.A. Khalid
Raj K. Prabhu
11.1 Introduction
177(4)
11.2 Methods
181(5)
11.2.1 Pediatric head development
181(1)
11.2.2 Material properties
182(2)
11.2.3 Mesh convergence
184(1)
11.2.4 Boundary and loading conditions
184(1)
11.2.5 Global validation of the FE-head against PMHS
185(1)
11.2.6 Global, regional, and local validation of the FE-head against the physical model
185(1)
11.2.7 Statistical analysis
185(1)
11.3 Results and discussion
186(5)
11.3.1 Global validation of the FE-head versus the postmortem human surrogate
186(1)
11.3.2 Global validation of the FE-head versus the physical model
187(1)
11.3.3 FE-head regional and local validation versus the physical model
188(2)
11.3.4 Head deformation
190(1)
11.4 Summary
191(2)
References
191(2)
Chapter 12 Experimental data for validating the structural response of computational brain models
193(16)
A. Alshareef
J.S. Giudice
D. Shedd
K. Reynier
T. Wu
M.B. Panzer
12.1 Introduction
193(2)
12.2 Methods
195(8)
12.2.1 Experimental brain pressure measurements
195(1)
12.2.2 Experimental brain deformation measurements
196(7)
12.3 Challenges and limitations
203(2)
12.4 Summary and future perspectives
205(4)
References
206(3)
Chapter 13 A review of fluid flow in and around the brain, modeling, and abnormalities
209(30)
R. Prichard
M. Gibson
C. Joseph
W. Strasser
13.1 Introduction
209(1)
13.2 Flow anatomy
209(2)
13.2.1 Ventricular system
209(1)
13.2.2 Ventricles and subarachnoid space
210(1)
13.3 Characteristic numbers
211(2)
13.3.1 Reynolds number
211(1)
13.3.2 Womersley number
212(1)
13.3.3 Peclet number
212(1)
13.4 Common brain flow abnormalities
213(3)
13.4.1 Misfolded proteins
214(1)
13.4.2 Injury
215(1)
13.4.3 Reduced arterial pulsatility
215(1)
13.4.4 Hydrocephalus
215(1)
13.4.5 Chiari malformation
216(1)
13.4.6 Syringomyelia and syringobulbia
216(1)
13.5 Boundary conditions for models
216(3)
13.5.1 General comments
216(1)
13.5.2 Cardiac flow
217(1)
13.5.3 Respiratory flow
217(1)
13.5.4 Circulatory flow
217(2)
13.5.5 Intracranial pressure
219(1)
13.6 Brain measurement and imaging
219(3)
13.6.1 Magnetic resonance imaging
219(1)
13.6.2 Spin/field/gradient echo MRI
219(1)
13.6.3 Phase contrast MRI
220(1)
13.6.4 MRI limitations
220(1)
13.6.5 Pressure monitoring
221(1)
13.6.6 MRI segmentation m
221(1)
13.7 Flow modeling
222(11)
13.7.1 CFD simplifications: rigid walls
231(1)
13.7.2 CFD simplifications: microstructures
232(1)
13.8 Literature gap
233(6)
References
233(6)
Chapter 14 Resonant frequencies of a human brain, skull, and head
239(16)
T.R. Fonville
S.J. Scarola
Y. Hammi
Raj K. Prabhu
Mark F. Horstemeyer
14.1 Introduction
239(2)
14.2 Problem set-up for the finite element simulations
241(2)
14.3 Results
243(4)
14.3.1 Whole head: fundamental frequency and mode shapes
244(1)
14.3.2 Brain: fundamental frequency and mode shapes
244(3)
14.4 Discussion
247(4)
14.5 Conclusions
251(4)
References
252(3)
Chapter 15 State-of-the-art of multiscale modeling of mechanical impacts to the human brain
255(4)
Mark F. Horstemeyer
15.1 Introduction
255(1)
15.2 Work to be completed
255(3)
15.2.1 Multiphy sics aspects of the brain
255(1)
15.2.2 Multiscale structure-property relationships of the brain
255(1)
15.2.3 Different biological effects on the brain
256(1)
15.2.4 The liquid-solid aspects of the brain
257(1)
15.2.5 Different human ages
257(1)
15.3 Conclusions
258(1)
References
258(1)
Index 259
CAVS Chair Professor, Department of Mechanical Engineering, Mississippi State University

Dr. Horstemeyer has published over 350 journal articles, conference papers, books, and technical reports. He has won many awards including the R&D 100 Award, AFS Best Paper Award, Sandia Award for Excellence, the SAE Teetor Award and was a consultant for the Columbia Accident Investigation Board. He is a fellow of the American Society of Mechanical Engineers, the American Society of Metals, the American Association for the Advancement of Science, and the Society of Automotive Engineers.

Before coming to MSU, he worked at Sandia National Laboratories for 15 years where he worked on a myriad of projects mostly focusing on weapons programs but transferred the research and technologies developed at Sandia to the automotive industry. Dr. Raj K. Prabhu is the Deputy Project Scientist, NASA Human Research Programs (HRPs) Cross-Cutting Computational Modeling Project (CCMP) at Universities Space Research Association. In his current position, Dr. Prabhu supports CCMPs computational modeling efforts to investigate human physiological responses to space stressors and provide modeling and simulation-based support to mitigate HRP-related risks. Before the CCMP role, Dr. Raj Prabhu jointly served as an Associate Professor of Biomedical Engineering and Associate Director at the Center for Advanced Vehicular Systems, Mississippi State University (MSU), Starkville, MS. Dr. Prabhu obtained his doctoral and masters degrees in mechanical engineering and computational engineering respectively. He completed his bachelors degree in chemical engineering from the Indian Institute of Technology-Madras, Chennai, India. Dr. Prabhus research background is in multiscale modeling, integrated computational biomedical modeling, dynamic responses of soft tissue, bio-inspired design, and human-centric structural design. Dr. Prabhu has made novel contributions to the multiscale biomechanics of traumatic brain injury due to external mechanical loads and a bio-inspired football helmet design.
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