Fairly direct hit! Advances in imaging of shotgun projectiles in MRI.

Abstract

To investigate the magnetic properties of different types of projectiles and qualify the metal artefact reduction technique for diagnostic and/or forensic MRI. Ten different projectiles embedded in ordnance gelatine blocks underwent an in vitro 1.5-T MR study with seven sequences including a recently developed metal artefact reduction sequence (Advanced WARP) combining VAT (view-angle-tilting) and SEMAC (slice-encoding metal-artefact-correction). Resulting image quality (five-point scale: 1=best; 5=worst) was scored. Quantifiable magnetic characteristics were correlated with qualitative rating of the MR sequences and torque dislodgment. Metal artefact reduction sequence (median: 2.5) significantly (p < 0.001) improves depiction of projectiles in comparison to all other MR pulse sequences (median: 4.75). Images from diamagnetic composed bullets (median: 2) are much less disturbed compared to magnetic attracted ones (median: 5). Correlation (0.623) between deflection angle measurement (ferromagnetic mean 84.2°; paramagnetic 62°; diamagnetic mean 0°) and median qualitative image quality was highly significant (p = 0.027). Torque dislodgement was distinct for elongated magnetic attracted projectiles. Significant improvement of MR imaging of projectiles using metal artefact reduction techniques has important implications for diagnostic/forensic work-up. The correlations between magnetic attraction force, deflection-angle results and image properties demonstrate that the MR safety of projectiles can be estimated with one of these methods. • Metal artefact reduction sequence improves overall image quality of bullets (p < 0.001). • Deflection angle assessment significantly predicts image quality of bullets (p = 0.027). • Classification of projectiles' magnetic properties based on artefacts' characteristics is possible. • Classifying of bullets has important implications in diagnostic and forensic imaging. • Identification of projectiles' magnetic attributes improves estimation of patients' injury risk.