Medical assessment of penetrating injuries is a difficult and knowledge-intensive task. Physical examination and computed tomographic (CT) imaging data must be combined with detailed anatomic, physiologic, and biomechanical knowledge to assess the injured subject. We are developing a methodology to automate reasoning about penetrating injuries using canonical knowledge combined with specific subject image data. We build a three dimensional geometric model of a subject from segmented images. We link regions in this model to concepts in two knowledge sources: (1) a comprehensive ontology of anatomy containing organ identities, adjacencies, and other information useful for anatomic reasoning, and (2) an ontology of regional perfusion containing formal definitions of arterial anatomy and corresponding regions of perfusion. We developed problem solvers that can determine the organs that are injured given particular trajectories of projectiles, whether vital structures – such as a coronary artery – are injured, and can predict the propagation of injury ensuing after a vital structure is injured. This methodology may improve the speed and accuracy of rapid assessment of penetrating injury.
