Brain Imaging Features in Patients with Gunshot Wounds to the Head.

Abstract

To introduce the UChicago PBI Imaging score, a novel characterization of imaging features using head computed tomography (HCT) in patients with gunshot wounds to the head (GSWH) resulting in penetrating brain injury (PBI) and to quantify the association with mortality. We retrospectively collected and analyzed data from 230 patients with GSWH admitted to our Level 1 trauma center between May 1, 2018, and October 31, 2023. HCT images obtained on hospital arrival were evaluated for predefined imaging features by two blinded readers and arbitrated, when needed, by a third. The average contribution of each radiological feature to mortality at hospital discharge was assessed using a SuperLearner ensemble model trained on ∼77% of the cohort. Each feature's contribution was scaled to ensure the additive final score per patient ranged between 0 and 100. The HCT features predicting in-hospital mortality, ranked from highest to lowest importance, were transhemispheric projectile below the level of the third ventricle (18 [16.8, 19.9]), presence of blood in the lateral ventricles (ventricles casted) (18[16.8, 19.6]), brainstem involvement (14 [12.7, 15.1]), transhemispheric projectile above the level of the third ventricle (11 [9.7, 11.6]), presence of any amount of blood in the ambient cistern (9[8.2, 10]), presence of any amount of blood in the lateral ventricles (9 [7.9, 9.8]), cerebellar involvement (9 [7.9, 9.5]), any evidence of ventricular effacement (4 [3.4, 4.6]), midline shift (MLS) >0 mm (4 [3.4, 4.4]), perforating injury (3 [2.4, 3.2]), and presence of an intracerebral hematoma (ICH) >20 mm in the largest diameter (2 [1.4, 1.9]). The UChicago PBI Imaging score showed a strong performance, achieving an area under the curve (AUC) of 0.86 (95% CI: [0.77, 0.96]) on a test set of 56 patients who were not included in model training. This indicates better prediction accuracy compared to both the Rotterdam score (AUC 0.8, 95% CI: [0.68, 0.96]) and the Marshall score (AUC 0.66, 95% CI: [0.52, 0.81]). Our model performed particularly well for patients with a Glasgow Coma Scale (GCS) score between 5 and 9. In this range, our model's performance (AUC 0.86) remained stable, while the Rotterdam and Marshall Scores showed notably lower predictive accuracy, with AUCs of 0.61 and 0.52, respectively. A dedicated evaluation of GSWH HCT reveals an association between disease burden, as quantified by unique features not native to blunt TBI imaging models, and mortality. Specifically, transhemispheric injury below the level of the third ventricle along with blood-casting bilateral ventricles and brainstem involvement was highly associated with mortality. The model is optimized for intermediate GCS scores where greater prognostic uncertainty exists. This study parallels efforts to refine TBI classification, underscoring the necessity for precise imaging-based classification in PBI to identify imaging biomarkers and ultimately enhance prognostication and targeted treatment.