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Abstract
Objectives: Contemporary finite element (FE) models, like that from the Global Human Body Models Consortium (GHBMC), have been useful for developing safety systems to reduce the severity of injuries in motor vehicle crashes (MVCs), including traumatic brain injury (TBI). However, not all injury occurs during the MVC. Cerebral edema after TBI contributes to mortality by increasing intracranial pressure (ICP) and preventing adequate cerebral blood supply. The focus of this study was to model post-traumatic cerebral edema and subsequent mortality due to increased ICP.
Methods: Brain tissue swells in a manner consistent with triphasic biomechanics, which models biological tissues as a charged deformable porous solid matrix (fixed charge density [FCD]), a solvent, and monovalent counter-ions (cerebrospinal fluid). Fluid uptake into the brain is driven by the Gibbs-Donnan osmotic pressure as the FCD is exposed when cells die. Post-TBI edema was simulated in FEBio (febio.org), which includes triphasic material formulations.
The GHBMC mesh was imported into FEBio, and each element was assigned a FCD to represent impact-related cell death based on its maximum principal strain (MPS) experienced during the crash-simulation using the stock GHBMC model and LS-DYNA. The ensuing pathophysiology was simulated in FEBio in two steps. First, the brain swelled in response to exposure of FCD, causing some adjacent elements to compress as fluid was redistributed. Biologically, the compression was assumed to reduce blood flow and cause ischemic cell death, represented by additional exposure of FCD, swelling, and increased ICP. Using published prognostic models of clinical outcome, mortality was predicted based on ICP.
Results: Post-traumatic volume ratio of elements ranged from less than 30% (compaction) to greater than 200% (swelling). Predicted ICP values for a fatal impact were as high as 8.55 kPa (64.1 mmHg), which is associated with a 99% probability of death.
Conclusion: To the best of our knowledge, this is the first study to simulate post-traumatic brain swelling to predict outcome. By incorporating swelling, ischemia, and cell death, our novel approach may improve fidelity of predicting outcome after MVCs. A strength of our approach is relying on the validated GHBMC model to predict brain deformation in the crash-scenario. The main goal of the current study was to demonstrate feasibility of simulating post-injury swelling using triphasic biomechanics. We successfully predicted clinically relevant increases in ICP that suggest a high likelihood of death when simulating a fatal impact scenario, however, more validation of our methodology is needed.