Photon-counting CT for bullet material differentiation: applications in forensic radiology.

Abstract

Background: Gunshot deaths due to homicide or military encounters are a major health concern. Noninvasive bullet characterization is of major importance for patients with lodged bullets or in mass disasters with multiple cadavers, which must be prioritized for autopsy. Therefore, the aim of this study was to investigate whether brass and lead bullets can be differentiated using photon-counting CT (PCCT).

Methods: Nine different lead (n = 6) or brass (n = 3) bullets were investigated on a state-of-the-art PCCT using a clinically unavailable research mode. Here, four image sets were reconstructed for different energy thresholds (20, 55, 72, 90 keV). Three circular regions of interest were placed on the 20-keV threshold images by two readers and automatically copied to the three other threshold images. Based on measured HU mean and max values, dual-energy indices (DEI) were calculated for the low/high energy threshold pairs of 20/90, 55/90, and 72/90 keV.

Results: Significant differences of DEIs between lead and brass projectiles were observed for the 20/90 keV DEI for HU mean ± standard deviation values (Qr40 kernel, lead: -0.085 ± 0.021, brass: 0.024 ± 0.048) and HU max values (Qr40 kernel, lead: -0.093 ± 0.011, brass: 0.023 ± 0.057) (p < 0.001 for both). Differences decreased for the 55/90 and 72/90 keV DEIs between the two projectile materials but remained statistically significant.

Conclusion: In this PCCT phantom study, significant differences were observed between lead and brass bullets in the different energy threshold images.

Relevance statement: Photon-counting CT could be a promising tool for bullet identification as significant differences were found in the different energy threshold images for lead and brass bullets, with application in clinical and forensic radiology.

Key points: In emergency settings, noninvasive bullet characterization is of importance for law enforcement. Bullet material characterization can be performed using photon-counting CT. These characteristics can be quantified in the four different energy threshold images.