Computational Modeling of Bridging Vein Rupture and Acute Subdural Hematoma Growth.

Abstract

Due to relative motion between the skull and brain caused by mechanical impact to the head during traumatic brain injury (TBI), bridging vein (BV) rupture can occur, resulting in the formation of acute subdural hematoma (ASDH). ASDH is associated with worse clinical outcomes and higher mortality because the resulting blood clot compresses surrounding brain tissue, exacerbating secondary injuries such as cerebral edema and ischemia. In this study, we developed a computational schema to predict BV rupture and model ASDH growth. Leveraging the deformation in the cerebrospinal fluid (CSF) layer in the Global Human Body Models Consortium (GHBMC) finite element head model to evaluate relative motion at the brain-skull interface, we introduced a novel BV rupture prediction approach based on statistical measures of the strain of these CSF elements. This approach attempts to account for the population variability in BV geometry. Validation using real-world crash accident reconstruction data demonstrated good predictive performance. Based on BV rupture predictions, we modeled ASDH growth, in which hematoma expansion was driven by the simulated patient-specific intracranial pressure (ICP) response due to primary injury and secondary injuries. Hematoma growth ceased once local hematoma cavity pressure equilibrated with ICP. Simulation results produced significant hematoma expansion with greater ICP elevation, a critical indicator for high mortality rate in the clinic. The computational schema developed in this study provides a foundation for future studies to improve the prediction of mortality rate for patients with BV rupture and ASDH after TBI, which can aid in safety system design.