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Numerical modelling of brain injuries due to head impacts

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Resumo:The finite element method (FEM) has become an essential tool for simulating traumatic brain injuries (TBI) through the use of detailed human head models. TBI is a leading cause of mortality and long-term disability, frequently resulting in severe conditions such as chronic traumatic encephalopathy (CTE) and other neurodegenerative diseases. In order to enhance our comprehension of TBI, Finite Element Head Models (FEHM) have been developed, facilitating more precise in silico projections. However, the underrepresentation of females in clinical trials raises concerns about the dearth of gender-specific data. The anatomical differences between male and female brains highlight the necessity for a Female Finite Element Head Model (FeFEHM). The objective of this dissertation is to conduct a comprehensive analysis of two FEHMs, one male and one female, in order to predict injury outcomes and explore the biomechanical responses of the brain, focusing on vulnerable regions such as the corpus callosum and the pituitary gland. The methodology involves simulating a range of real-life brain injuries, encompassing those sustained from e-scooter accidents, work-related impact injuries and football-related impacts. By capturing the resulting linear and angular accelerations and applying them to the head’s centre of gravity (COG), these scenarios were subjected to meticulous analysis to predict potential injury patterns and their biomechanical effects. The analyses performed using the failure criteria, revealed significant differences in strain, stress, and pressure thresholds between the head models, with notable variations in Maximum Principal Strain (MPS), von Mises Stress, and brain pressure across different injury scenarios, highlighting that the female brain is more susceptible to injury and exhibits different outcomes compared to the male brain under similar impact conditions. In addition, the effectiveness of a protective helmet in mitigating the impact forces on injuries in most regions, particularly in the critical structures of the brain, is presented. The study advocates for further improvement of the biofidelity of the FEHMs and their integration into real-world accident reconstructions, to improve the accuracy of injury prediction and to better understand the mechanisms underlying traumatic injuries the long-term effects of repetitive brain trauma, thereby enabling the development of more effective safety and post-traumatic measures.
Autores principais:Cardoso, Carlos Gabriel dos Santos
Assunto:Corpus callosum Sex difference Female brain Finite element method Traumatic brain injury Pituitary gland
Ano:2024
País:Portugal
Tipo de documento:dissertação de mestrado
Tipo de acesso:acesso embargado
Instituição associada:Universidade de Aveiro
Idioma:inglês
Origem:RIA - Repositório Institucional da Universidade de Aveiro
Descrição
Resumo:The finite element method (FEM) has become an essential tool for simulating traumatic brain injuries (TBI) through the use of detailed human head models. TBI is a leading cause of mortality and long-term disability, frequently resulting in severe conditions such as chronic traumatic encephalopathy (CTE) and other neurodegenerative diseases. In order to enhance our comprehension of TBI, Finite Element Head Models (FEHM) have been developed, facilitating more precise in silico projections. However, the underrepresentation of females in clinical trials raises concerns about the dearth of gender-specific data. The anatomical differences between male and female brains highlight the necessity for a Female Finite Element Head Model (FeFEHM). The objective of this dissertation is to conduct a comprehensive analysis of two FEHMs, one male and one female, in order to predict injury outcomes and explore the biomechanical responses of the brain, focusing on vulnerable regions such as the corpus callosum and the pituitary gland. The methodology involves simulating a range of real-life brain injuries, encompassing those sustained from e-scooter accidents, work-related impact injuries and football-related impacts. By capturing the resulting linear and angular accelerations and applying them to the head’s centre of gravity (COG), these scenarios were subjected to meticulous analysis to predict potential injury patterns and their biomechanical effects. The analyses performed using the failure criteria, revealed significant differences in strain, stress, and pressure thresholds between the head models, with notable variations in Maximum Principal Strain (MPS), von Mises Stress, and brain pressure across different injury scenarios, highlighting that the female brain is more susceptible to injury and exhibits different outcomes compared to the male brain under similar impact conditions. In addition, the effectiveness of a protective helmet in mitigating the impact forces on injuries in most regions, particularly in the critical structures of the brain, is presented. The study advocates for further improvement of the biofidelity of the FEHMs and their integration into real-world accident reconstructions, to improve the accuracy of injury prediction and to better understand the mechanisms underlying traumatic injuries the long-term effects of repetitive brain trauma, thereby enabling the development of more effective safety and post-traumatic measures.