Evaluation of Head Injury: Extent and Distribution of Extra-axial Lesions from Motor Vehicle Crashes

Approximately 1.7 million people sustain a traumatic brain injury (TBI) each year, with motor vehicle crash (MVC) representing the leading cause for TBI-related hospitalization. Subarachnoid hemorrhage (SAH), subdural hematoma (SDH), cerebral contusion, and diffuse axonal injury (DAI), are some of the most common and serious consequences of MVC-related TBI and are associated with high mortality and morbidity rates. Little is known, however, about the relationship between the contact location on the head and resulting intracranial trauma. Contact location between the head and internal components of the vehicle were used in the analysis of hemorrhage extent and distribution in order to better understand occupant injury, with the hypothesis that the common contacts for occupants in MVCs would correlate with specific hemorrhage patterns. Head computed tomography (CT) scans demonstrating cerebral SAH (42), SDH (33), contusion (25), and/or DAI (12) were selected from the Crash Injury Research Engineering Network (CIREN) database. Semi-automated methods were used to quantify intracranial volume, extent and distribution, and approximate contact location identified from a soft tissue scalp contusion. Label maps representing the injured volume and the scalp contusion were converted to three-dimensional (3D) point clouds. The 3D data from each occupant was aligned to a global spherical coordinate system using bony landmarks identified on the skull. Incremental calculation of injury volume was performed at 0.2 radian by 0.2 radian increments along the azimuth and elevation axes of the spherical coordinate system. The volume was calculated from a 3D Delaunay triangulation to create a polygonal surface of the convex hull of the points. Injury distribution and extent was quantified in terms of theta (about SAE Z-axis) and phi (from the SAE XY-plane) in relation to the contact location. This study is the first volumetric analysis of real-world head injuries using clinical CT and known crash characteristics with contact information. These data highlight the utility of combining clinical neuroimaging with mechanical crash data for investigating mechanisms of TBI. Results from this study will allow for a better understanding of the biomechanics of traumatic brain injury. Such data may be used in the future for the validation of finite element models of the head to better mitigate and prevent head injury.