3D modeling of foreign bodies in pediatric injuries: a web-based public health prevention approach

Abstract Background Injuries caused by foreign bodies (FBs) in children represent a significant public health concern. Characterizing FBs is essential for developing targeted prevention strategies, as the risk of injury is shaped by the interplay of morphology, size, material composition, and the biomechanical dynamics of aspiration or ingestion. This study aims to develop a web-based approach that leverages high-resolution 3D scanning technology to characterize FBs for profiling injury risk and establishing targeted prevention strategies to reduce the incidence and severity of pediatric FB injuries. Methods Data were drawn from the Susy Safe registry, a multicenter international database collecting FB injury cases in children under 14 years. 500 physical FBs were processed through 3D scanning. Each object was analyzed using CAD software to extract morphometric parameters, including maximum diameter, length-to-width ratio, surface roughness, and curvature maps. Dimensional thresholds were compared with pediatric airway and esophageal diameters, and biomechanical simulations were conducted to predict anatomical fit. Extracted features were combined in machine learning models to identify injury risk. Validated predictive algorithms were integrated into a web-based platform to enable real-time risk assessment. Results Among the 500 scanned FBs, 60% were rigid. Preliminary findings indicate that objects with spherical shapes and low surface friction are more likely to lodge in the trachea or bronchi (OR 2.8; 95% CI: 1.9-4.2). Irregular or angular objects, especially those with sharp projections, tend to become lodged in the esophagus (OR 3.1; 95% CI: 2.0-4.9) due to mechanical interlocking, increasing the risk of lacerations. Conclusions Integrating 3D object modeling into pediatric FB injury surveillance offers a data-driven approach to enable real-time risk assessment, support clinical decision-making, inform policy recommendations, and guide public health prevention. Key messages • 3D modeling of foreign bodies enables objective, morphology-based risk stratification, enhancing clinical understanding of injury mechanisms in children. • Integrating 3D modeling and predictive algorithms into FB injury surveillance offers a data-driven tool to inform prevention strategies through collaboration with clinicians and policymakers.