High Throughput Brain Modeling For Real-Time Computation of Brain Injury Metrics

Open Access
- Author:
- Menghani, Ritika Raj
- Graduate Program:
- Mechanical Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- May 16, 2024
- Committee Members:
- Robert Kunz, Professor in Charge/Director of Graduate Studies
Melissa Brindise, Major Field Member
Elizabeth Proctor, Outside Unit & Field Member
Reuben Kraft, Chair & Dissertation Advisor
Xiaogang Hu, Major Field Member - Keywords:
- finite element modeling
traumatic brain injury
computational biomechanics - Abstract:
- Mild Traumatic brain injury (mTBI) is a major health concern for people worldwide. One common cause of mTBI is head trauma sustained in contact sports. Many mTBIs go undiagnosed which has led to the growth of instrumented mouthguards (iMGs) to monitor head impacts in real-time. However, iMGs offer limited data about the biomechanics of the brain during impact. This has led to the development and use of numerical brain models to conduct simulations that use physics to inform the brain’s mechanical behavior, however, this research has primarily remained within the brain modeling community. Further, the practical application of these models in diagnosing injuries remains largely unexplored. To tackle this challenge, we have developed a brain modeling platform that can predict the brain’s response based on kinematic data provided by iMGs and other sensors and can be used to run large-scale simulations. The platform uses cloud computing to increase accessibility and to allow for scalability and automation and provides information on the biomechanics of the impact, the severity of the injury. and may help diagnose concussions in the future. Through large-scale studies, we aim to bridge the gap between modeling and diagnosis, facilitating broader utilization of these technologies. My research objectives can be broadly separated into two categories: • Computational Development: Development of the computational aspects of the brain simulation research platform which includes exploring the creation of personalized meshes and building and validating a custom finite element code. This allows for large scale personalized simulations to be run at low costs, making the technology accessible to the public. • Analysis of Brain Injury Data: This includes working on establishing the relationship between various brain injury metrics and the symptoms that occur after a severe head impact. This can pave the way for the platform to be used as a diagnostic tool.