Gaewsky 1 A NUMERICAL APPROACH TO IDENTIFY INJURY RISK REGIONS WITHIN SOFT TISSUES OF DYNAMIC HUMAN BODY FINITE ELEMENT MODELS

Objective: As different morphologies and postures of human body models (HBMs) are developed, simulations of occupants in real world motor vehicle collisions (MVCs) can become more sensitive to injury risk factors. Despite the detail of modern HBMs, most dynamic analyses of these models studied body region-level injury metrics like displacements and accelerations, while most element-level analyses focus on peak stresses and strains. The objective of this study was to analyze the dynamic nature of thoracic soft tissue deformations using local areas of increased strains to identify potential injury sites. Methods: Eleven frontal MVCs from the CIREN and NASS-CDS databases were reconstructed using a previously developed dynamic finite element methodology. These MVC reconstructions used scaled versions of the Total HUman Model for Safety (THUMS) AM50 v4.01 and a tuned simplified vehicle model. CIREN radiology and NASS-CDS injury reports indicated that five of eleven driver occupants sustained soft tissue thoracic injuries (AIS 2+) including pulmonary contusion, pneumothorax, hemothorax, and hemomediastinum. In each simulation, strain data were output for all elements in the lungs, pleurae, heart, pericardium, and rib cage at 0.5 ms intervals. The shape of the time-varying profiles of each element for maximum principal strain (εmp) were compared using normalized cross-correlation. The normalized cross-correlation coefficient between each pair of elements allowed grouping of elements that shared similar time-dependent deformation patterns during the impact. Element groups with increased strain metrics were identified as hotspots. Results: The dynamic deformation profiles for each anatomical structure were processed for each reconstructed MVC. A fraction of elements exceeding previous pulmonary contusion strain thresholds were calculated. The largest hotspot’s average εmp for the left lung (p=0.43), right lung (p=0.70) and heart (p=0.76) parts were not significantly different between injurious and non-injurious cases. Conclusions: A method to analyze dynamic deformation patterns in FE simulations was applied across eleven MVC reconstructions. This algorithm promotes understanding which regions of the anatomical structures deform together, and may improve the ability to model complex and multiphasic injury mechanisms.