Linking Brain Deformation to Environmental Sensor Data via Validating a Gyrated Human Head Phantom Under Impulsive Loading
Abstract
The current proposal summarizes and outlines a unique approach in the addressing a critical knowledge gap that directly links acquired environmental exposure data, such as helmet acceleration and blast overpressure, to observed clinical outcomes as to establish injury thresholds. Specifically, this approach will leverage and improve previously developed Anthropomorphic Neurologic Gyrated Unified Standard (ANGUS) biofidelic phantom to capture brain tissue deformation due to rotational impulses during blast and blunt exposures. To deploy a non-invasive strategy to quantify brain injury through acceleration and blast gauge pressure data will provide objective markers predicting clinical outcomes and personalization of treatment. This innovative approach directly aligned with the current TBIPHRP Focus Area: Prevent: identification and validation of biomarker or objective markers for diagnosis, prognosis, or monitoring. The diagnostic and quantification of TBI remains a significant challenge for the civilian and military health systems. Although clinical manifestations, such as concussions, can result from blast and blunt trauma exposures, there is a growing concern that sub-concussive events may also trigger undetectable tissue injury that could lead to cumulative and progressive neurologic symptoms. Given the wide breadth of clinical TBI outcomes, with the lack of medical imaging, it is particularly challenging to predict risk for worsening and patients requiring close neurosurgical and intensive care monitoring – yet this is exactly the scenario we will encounter in prolonged field care. Thus, military operational medicine requires a robust and flexible approach to identify and personalize clinical management plans through targeted triage and interventions to optimize recovery by linking exposure data to clinical risk. Within the Department of Defense (DOD) and National Collegiate Athletic Association (NCAA), there has been a continuous effort in the collection and quantification of extracranial accelerations and motions as a result of blast and blunt exposures, respectively. Based on these collected exposure datasets, a unique strategy has been proposed that links physical exposures to clinical outcome profiles through brain tissue deformation. An inherent advantage of this approach is that it can applied to establish objective markers that can be deployed across operational and training environments without the need for biospecimen collection and analysis. However, there is a fundamental knowledge gap in the direct and quantified correlation between head motion after exposure, the resultant brain deformation, and observed clinical manifestation as observed by clinicians. The ANGUS phantom was developed to bridge that knowledge gap and has shown to be an effective empirical tool in the study of exposure mechanics. Thus far, the phantom has been utilized to quantify brain tissue motion under various models of extracranial motion during impact loading. Additionally, ANGUS has been characterized using magnetic resonance imaging (MRI) and has been shown to be comparable to human subject data. The current effort will leverage this previous work to (1) improve and validate ANGUS in its ability to predict human brain tissue under non-injurious rotational impulsive loading. Specifically, this will be achieved through modification of the material and anatomic additions. Additionally, the effort will aim to (2) expose the improved and validated ANGUS to range of blunt and blast exposure parameters while collecting head accelerations and blast overpressures as to link sensor data directly to brain tissue deformation. Although traditional computational models have been effective in capturing the complexities of human anatomy and its changes after loading, the resultant data have only been validated in human cadavers. Furthermore, conventional physical phantoms typically focus on modeling skull fractures and no
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 28, 2022
- Source ID
- W81XWH2211118
Entities
People
- Philip V. Bayly
Organizations
- United States Army
- Washington University in St. Louis