Evaluation and Validation of Thorax Model Responses: A Hierarchical Approach to Achieve High Biofidelity for Thoracic Musculoskeletal System

The I-PREDICT 50th Percentile Male Warfighter Finite Element Model: Development and Validation of the Thoracolumbar Spine

Military personnel are commonly at risk of lower back pain and thoracolumbar spine injury. Human volunteers and postmortem human subjects have been used to understand the scenarios where injury can occur and the tolerance of the warfighter to these loading regimes. Finite element human body models (HBMs) can accurately simulate the mechanics of the human body and are a useful tool for understanding injury. In this study, a HBM thoracolumbar spine was developed and hierarchically validated as part of the Incapacitation Prediction for Readiness in Expeditionary Domains: an Integrated Computational Tool (I-PREDICT) program. Constitutive material models were sourced from literature and the vertebrae and intervertebral discs were hexahedrally meshed from a 50th percentile male CAD dataset. Ligaments were modeled through attaching beam elements at the appropriate anatomical insertion sites. 94 simulations were replicated from experimental PMHS tests at the vertebral body, functional spinal unit (FSU), and regional lumbar spine levels. The BioRank (BRS) biofidelity ranking system was used to assess the response of the I-PREDICT model. At the vertebral body level, the I-PREDICT model showed good agreement with experimental results. The I-PREDICT FSUs showed good agreement in tension and compression and had comparable stiffness values in flexion, extension, and axial rotation. The regional lumbar spine exhibited "good" biofidelity when tested in tension, compression, extension, flexion, posterior shear, and anterior shear (BRS regional average = 1.05). The validated thoracolumbar spine of the I-PREDICT model can be used to better understand and mitigate injury risk to the warfighter.

Explaining and predicting the increased thorax injury in aged females: age and subject-specific thorax geometry coupled with improved bone constitutive models and age-specific material properties evaluated in side impact conditions

Predicting and understanding thorax injury is fundamental for the assessment and development of safety systems to mitigate injury risk to the increasing and vulnerable aged population. While computational human models have contributed to the understanding of injury biomechanics, contemporary human body models have struggled to predict rib fractures and explain the increased incidence of injury in the aged population. The present study enhanced young and aged human body models (HBMs) by integrating a biofidelic cortical bone constitutive model and population-based bone material properties. The HBMs were evaluated using side impact sled tests assessed using chest compression and number of rib fractures. The increase in thoracic kyphosis and the associated change in rib angle with increasing age, led to increased rib torsional moment increasing the rib shear stress. Coupled with and improved cortical bone constitutive model and aged material properties, the higher resulting shear stress led to an increased number of rib fractures in the aged model. The importance of shear stress resulting from torsional load was further investigated using an isolated rib model. In contrast, HBM chest compression, a common thorax injury-associated metric, was insensitive to the aging factors studied. This study proposes an explanation for the increased incidence of thorax injury with increasing age reported in epidemiological data, and provides an enhanced understanding of human rib mechanics that will benefit assessment and design of future safety systems.

Construction and study of a three-dimensional visualization model of superficial temporal artery branches: With an explicatory case

BACKGROUND

The anatomical parameters of the superficial temporal artery branches were measured by a three-dimensional measurement method to provide anatomical reference for relevant clinical operations.

METHODS

Seventy original images were selected who had cranial CTA examination. The patients were aged 30-79 years, with an average of 60.0 years, including 32 females and 38 males. After reconstructing the superficial temporal artery by professional medical 3D reconstruction software, its anatomical parameters were measured.

RESULTS

The length of the secondary branches of the frontal branch of the superficial temporal artery were 47.6 ± 23.6 mm and 37.3 ± 21.6 mm in males and females, respectively, with a statistically significant difference. The length of the secondary branches of the parietal branch of the superficial temporal artery were 39.6 ± 20.4 mm and 49.2 ± 20.3 mm in young and middle-aged people and older people respectively, which were statistically different. The remaining measures were not statistically different across gender and age groups. The frontal branch of the superficial temporal artery was divided into three types, and the parietal branch of the superficial temporal artery was divided into two types.

CONCLUSIONS

The anatomical parameters of the superficial temporal artery branches can be accurately measured by means of 3D visualization, providing an anatomical reference for relevant clinical operations.

Development of a biofidelic computational model of human pelvis for predicting biomechanical responses and pelvic fractures

BACKGROUND AND OBJECTIVE

The pelvis, a crucial structure for human locomotion, is susceptible to injuries resulting in significant morbidity and disability. This study aims to introduce and validate a biofidelic computational pelvis model, enhancing our understanding of pelvis injury mechanisms under lateral loading conditions.

METHODS

The Finite Element (FE) pelvic model, representing a mid-sized male, was developed with variable cortical thickness in pelvis bones. Material properties were determined through a synthesis of existing constitutive models, parametric studies, and multiple validations. Comprehensive validation included various tests, such as load-displacement assessments of sacroiliac joints, quasi-static and dynamic lateral compression on the acetabulum, dynamic side impacts on the acetabulum and iliac wing using defleshed pelvis, and lateral impacts by a rigid plate on the full body's pelvis region.

RESULTS

Simulation results demonstrated a reasonable correlation between the pelvis model's overall response and cadaveric testing data. Predicted fracture patterns of the isolated pelvis exhibited fair agreement with experimental results.

CONCLUSIONS

This study introduces a credible computational model, providing valuable biomechanical insights into the pelvis' response under diverse lateral loading conditions and fracture patterns. The work establishes a robust framework for developing and enhancing the biofidelity of pelvis FE models through a multi-level validation approach, stimulating further research in modeling, validation, and experimental studies related to pelvic injuries. The findings are expected to offer critical perspectives for predicting, preventing, and mitigating pelvic injuries from vehicular accidents, contributing to advancements in clinical research on medical treatments for pelvic fractures.

Biofidelity assessment of the GHBMC M50-O in a rear-facing seat configuration during high-speed frontal impact

The objective of this study was to assess the biofidelity of the Global Human Body Models Consortium (GHBMC) 50th male (M50-O) v6.0 seated in an upright (25-degree recline) all-belts-to-seat (ABTS) in a 56 km/h rear-facing frontal impact. The experimental boundary conditions from the post-mortem human subjects (PMHS) tests were replicated in the computational finite element (FE) environment. The performance of the rigidized FE ABTS model obtained from the original equipment manufacturer was validated via simulations using a Hybrid III FE model and comparison with experiments. Biofidelity of the GHBMC M50-O was evaluated using the most updated NHTSA Biofidelity Ranking System (BRS) method, where a biofidelity score under 2 indicates that the GHBMC response varies from the mean PMHS response by less than two standard deviations, suggesting good biofidelity. The GHBMC M50-O received an occupant response score and a seat loading score of 1.71 and 1.44, respectively. Head (BRS = 0.93) and pelvis (BRS = 1.29) resultant accelerations, and T-spine (avg. BRS = 1.55) and pelvis (BRS = 1.66) y-angular velocities were similar to the PMHS. The T-spine resultant accelerations (avg. BRS = 1.93) and head (BRS = 2.82), T1 (BRS = 2.10) and pelvis (BRS = 2.10) Z-displacements were underestimated in the GHBMC. Peak chest deflection in the anterior-posterior deflection in the GHBMC matched with the PMHS mean, however, the relative upward motion of abdominal contents and subsequent chest expansion were not observed in the GHBMC. Updates to the GHBMC M50-O towards improved thorax kinematics and mobility of abdominal organs should be considered to replicate PMHS characteristics more closely.

Modeling of active skeletal muscles: a 3D continuum approach incorporating multiple muscle interactions

Skeletal muscles have a highly organized hierarchical structure, whose main function is to generate forces for movement and stability. To understand the complex heterogeneous behaviors of muscles, computational modeling has advanced as a non-invasive approach to evaluate relevant mechanical quantities. Aiming to improve musculoskeletal predictions, this paper presents a framework for modeling 3D deformable muscles that includes continuum constitutive representation, parametric determination, model validation, fiber distribution estimation, and integration of multiple muscles into a system level for joint motion simulation. The passive and active muscle properties were modeled based on the strain energy approach with Hill-type hyperelastic constitutive laws. A parametric study was conducted to validate the model using experimental datasets of passive and active rabbit leg muscles. The active muscle model with calibrated material parameters was then implemented to simulate knee bending during a squat with multiple quadriceps muscles. A computational fluid dynamics (CFD) fiber simulation approach was utilized to estimate the fiber arrangements for each muscle, and a cohesive contact approach was applied to simulate the interactions among muscles. The single muscle simulation results showed that both passive and active muscle elongation responses matched the range of the testing data. The dynamic simulation of knee flexion and extension showed the predictive capability of the model for estimating the active quadriceps responses, which indicates that the presented modeling pipeline is effective and stable for simulating multiple muscle configurations. This work provided an effective framework of a 3D continuum muscle model for complex muscle behavior simulation, which will facilitate additional computational and experimental studies of skeletal muscle mechanics. This study will offer valuable insight into the future development of multiscale neuromuscular models and applications of these models to a wide variety of relevant areas such as biomechanics and clinical research.

A Surrogate Model Based on a Finite Element Model of Abdomen for Real-Time Visualisation of Tissue Stress during Physical Examination Training

Robotic patients show great potential for helping to improve medical palpation training, as they can provide feedback that cannot be obtained in a real patient. They provide information about internal organ deformation that can significantly enhance palpation training by giving medical trainees visual insight based on the pressure they apply for palpation. This can be achieved by using computational models of abdomen mechanics. However, such models are computationally expensive, and thus unable to provide real-time predictions. In this work, we proposed an innovative surrogate model of abdomen mechanics by using machine learning (ML) and finite element (FE) modelling to virtually render internal tissue deformation in real time. We first developed a new high-fidelity FE model of the abdomen mechanics from computerized tomography (CT) images. We performed palpation simulations to produce a large database of stress distribution on the liver edge, an area of interest in most examinations. We then used artificial neural networks (ANNs) to develop the surrogate model and demonstrated its application in an experimental palpation platform. Our FE simulations took 1.5 h to predict stress distribution for each palpation while this only took a fraction of a second for the surrogate model. Our results show that our artificial neural network (ANN) surrogate has an accuracy of 92.6%. We also showed that the surrogate model is able to use the experimental input of palpation location and force to provide real-time projections onto the robotics platform. This enhanced robotics platform has the potential to be used as a training simulator for trainees to hone their palpation skills.

Methodology to geometrically age human body models to average and subject-specific anthropometrics, demonstrated using a small stature female model assessed in a side impact

The aged population has been associated with an increased risk of injury in car-crash, creating a critical need for improved assessment of safety systems. Finite element human body models (HBMs) have been proposed, but require representative geometry of the aged population and high mesh quality. A new hybrid Morphing-CAD methodology was applied to a 26-year-old (YO) 5^th percentile female model to create average 75YO and subject-specific 86YO HBMs. The method achieved accurate morphing targets while retaining high mesh quality. The three HBMs were integrated into a side sled impact test demonstrating similar kinematic response but differing rib fracture patterns.

Fatal blunt chest trauma: an evaluation of rib fracture patterns and age

The following study was undertaken to determine if any specific occupant characteristics, crash factors, or associated injuries identified at autopsy could predict the occurrence or number of fractured ribs in adults. Data were accrued from the Traffic Accident Reporting System (TARS) and coronial autopsy reports from Forensic Science SA, Adelaide, South Australia, from January 2000 to December 2020. A total of 1475 motor vehicle fatalities were recorded in TARS between January 2000 and December 2020, and 1082 coronial autopsy reports were identified that corresponded to TARS fatal crash data. After applying exclusion criteria involving missing data, 874 cases were included in the analysis. Of the 874 cases, 685 cases had one or more rib fractures. The leading cause of death for those with rib fractures was multiple trauma (54%), followed by head injury (17%) and chest injuries (10%). The strongest predictor of one or more rib fractures was increasing age (p < 0.001). Other factors found in the regression to be predictive of the number of rib fractures were the presence of a variety of other injuries including thoracic spinal fracture, lower right extremity fracture, splenic injury, liver injury, pelvic fracture, aortic injury, lung laceration, and hemothorax. Age is most likely associated with increasing rib fractures due to reduced tolerance to chest deflection with greater injuries occurring at lower magnitudes of impact. The association of other injuries with rib fractures may be a marker of higher impact severity crashes.

Development and multi-level validation of a computational model to predict traumatic aortic injury

Traumatic aortic injury (TAI) is one of the leading causes of fatalities in blunt impact. However, there is no consensus on the injury mechanism of TAI in traffic accidents, mainly due to the complexity of occurrence scenarios and limited real-world crash data relevant to TAI. In this study, a computational model of the aorta with nonlinear mechanical characteristics and accurate morphology was developed and integrated within a thorax finite element model that included all major anatomical structures. To maximize the model's capability for predicting TAI, a multi-level process was presented to validate the model comprehensively. At the component level, the in vitro aortic pressurization testing was simulated to mimic the aortic burst pressure. Then, a sled test of a truncated cadaver was modeled to evaluate aorta response under posterior acceleration. The frontal chest pendulum impact was utilized to validate the performance of the aorta within full body model under direct chest compression. A parametric study was implemented to determine an injury tolerance for the aorta under these different loading conditions. The simulated peak pressure before aortic rupture was within the range of the experimental burst pressure. For the sled test, the simulated chest deflection and cross-sectional pressure of the aorta were correlated with the experimental measurement. No aorta injury was observed in simulated results of both sled test and chest pendulum impact, which matched the experimental findings. The present model will be a useful tool for understanding the TAI mechanisms, evaluating injury tolerance, and developing prevention strategies for aortic injuries.