Development Of A Finite Element Pelvis And Lower Extremity Model With Growth Plates For Pediatric Pedestrian Protection

Finite element (FE) model is a useful tool frequently used for investigating the injury mechanisms and designing protection countermeasures. At present, no 10 years old (YO) pedestrian FE model has been developed from appropriate anthropometries and validated against limitedly available impact response data. A 10 YO child FE pelvis and lower extremities (PLEX) model was established to fill the gap of lacking such models in this age group. The baseline model was validated against available pediatric postmortem human subjects (PMHS) test data and additional scaled adult data, then the PLEX model was integrated to build a whole-body FE model representing a 10 YO pedestrian. Additional investigations revealed that the immature tissues, growth plates (GPs), should be explicitly modeled because they have different mechanical properties than the surrounding bones. Epidemiological data revealed that GP accounted for a large portion of pediatric fractures. To investigate the GP’s material property for further advancement of the baseline PLEX FE model for simulating impact mechanical responses, a series of tensile and shearing experiments on porcine bone-GP-bone units were carried out. The GPs from the femoral head, distal femur, and proximal tibia of 20-weeks-old piglets were tested, under different strain rates. Randomized block ANOVA was conducted to determine the effects of anatomic region and strain rate on the material properties of GPs. By comparing the porcine experimental data to the limited data obtained from tests on human subjects reported in the literature, an optimal conversion factor was derived to correlate the material properties of 20-week-old piglet GPs and 10 YO child GPs. A transversely isotropic hyperelastic material model (MAT_92 available in LS-DYNA) with added viscosity was adopted to mimic the GP tissues. After a series of optimization procedures, the material parameter sets needed for MAT_92 were determined to represent the GPs of a 10 YO child. To further explore the GP modeling techniques, a sub-model representing the proximal femur was extracted from the PLEX model. The femoral head GP in the sub-model was modeled using the geometry from CT scans and the material properties from early optimizations. FE simulations of femoral head shearing were conducted on the sub-model to determine other GP modeling settings. In the following technical application, similar GP modeling techniques were implemented to model the GPs at the hip and knee regions to update the baseline PLEX model, and further the whole-body model. An SUV-to-pedestrian impact scenario was simulated using the updated whole-body model, the remarkable influences of the GPs on the stress distributions in the PLEX were quantitatively assessed

Estimation of probability distribution on multiple anatomical objects and evaluation of statistical shape models

The estimation of shape probability distributions of anatomic structures is a major research area in medical image analysis. The statistical shape descriptions estimated from training samples provide means and the geometric shape variations of such structures. These are key components in many applications. This dissertation presents two approaches to the estimation of a shape probability distribution of a multi-object complex. Both approaches are applied to objects in the male pelvis, and show improvement in the estimated shape distributions of the objects. The first approach is to estimate the shape variation of each object in the complex in terms of two components: the object's variation independent of the effect of its neighboring objects; and the neighbors' effect on the object. The neighbors' effect on the target object is interpreted using the idea on which linear mixed models are based. The second approach is to estimate a conditional shape probability distribution of a target object given its neighboring objects. The estimation of the conditional probability is based on principal component regression. This dissertation also presents a measure to evaluate the estimated shape probability distribution regarding its predictive power, that is, the ability of a statistical shape model to describe unseen members of the population. This aspect of statistical shape models is of key importance to any application that uses shape models. The measure can be applied to PCA-based shape models and can be interpreted as a ratio of the variation of new data explained by the retained principal directions estimated from training data. This measure was applied to shape models of synthetic warped ellipsoids and right hippocampi. According to two surface distance measures and a volume overlap measure it was empirically verified that the predictive measure reflects what happens in the ambient space where the model lies

IMPACT OF VAGINAL SYNTHETIC PROLAPSE MESHES ON THE MECHANICS OF THE HOST TISSUE RESPONSE

The vagina helps support the bladder, urethra, uterus, and rectum. A lack of support leads to pelvic organ prolapse, and vaginal delivery is a prevalent risk factor; however, there is little research on vaginal biomechanical properties. Despite numerous complications, clinical practice involves surgical repair with synthetic meshes. Complications can be partially attributed to our lack of knowledge regarding the mesh-tissue complex (MTC) after implantation. However, it is difficult to perform rigorous studies without utilizing animal models. Therefore, we evaluated how parity affected the mechanical properties of vaginal tissue in three animal models: rodent, sheep, and non-human primate (NHP) to compare their mechanically properties to parous women who typically undergo prolapse surgery. Parity negatively impacted the mechanical properties of the vagina in NHP, which were biomechanically similar to parous women, making it a suitable model for studying the effects of mesh implantation. Second, we examined the textile and structural properties of commonly used meshes (Gynemesh, UltraPro, SmartMesh, Novasilk, and Polyform) utilizing uniaxial and ball-burst tests. These meshes had significantly different porosity and structural properties. To investigate the host response, three meshes were implanted into the abdominal wall of the rodent and NHP, and on the vagina in the NHP. The MTC was removed, and the tissue contribution was calculated. We did not observe notable changes in the tissue properties following mesh implantation in the rodent; however, implantation of the stiffest mesh (Gynemesh) in the NHP resulted in an exhibition of a stress-shielding response manifested by inferior biomechanical properties of the abdominal and vaginal tissues. Less stiff meshes (UltraPro and SmartMesh) resulted in preservation of tissue properties. To gain insight into how mesh properties affect the tissue contribution, we began developing a finite element model. Utilizing the co-rotational theory with a fiber-recruitment stress-strain relationship, we could describe the behavior of SmartMesh and UltraPro. While an in-depth characterization of these meshes revealed multiple fiber populations, further development of modeling may be instrumental in closing the current knowledge gap. Ultimately, understanding the mesh-tissue interaction will improve clinical outcomes by identifying mesh properties that are essential for providing structural support while maintaining tissue integrity

Development and Validation of a Knee-Thigh-Hip LSDYNA Model of a 50th Percentile Male.

With the introduction of air bags, occupant safety in frontal car crashes has been improved for upper regions of the body, such as the head and thorax. These improvements, however, have not helped improve the safety for the lower extremities, increasing their percentage of injuries in car crashes. Though lower extremity injuries are usually not life threatening, they can have long lasting physical and psychosocial consequences. An LSDYNA finite element model of the knee-thigh-hip (KTH) of a 50th percentile adult male was developed for exploring the mechanics of injuries to the KTH during frontal crash crashes. The model includes a detailed geometry of the bones, the mass of the soft tissue, and a discrete element representation of the ligaments and muscles of the KTH. The bones were validated using physical tests obtained from the National Highway Traffic and Safety Administration\u27s (NHTSA) test database. The geometry, the material properties and the failure mechanisms of bone materials were verified. A validation was also performed against a whole-body cadaver test to verify contributions of passive muscle and ligament forces. Failure mechanisms in the tests and simulations were compared to ensure that the model provides a useful tool for exploring fractures and dislocations in the KTH resulting from frontal vehicle crashes. The validated model was then used to investigate injury mechanisms during a frontal car crash at different occupant positions. The role of muscle forces on these fracture mechanisms was explored and simulations of frontal impacts were then reproduced with the KTH complex at different angles of thigh flexion, adduction and abduction. Results show that the failure mechanism of the lower limb can significantly depend on the occupant position prior to impact. Failure mechanisms in the simulations were compared to results found in literature to ensure the model provides a useful tool for predicting fractures in the lower limb resulting from out-of-position frontal vehicle crashes. The FE model replicate injury criteria developed for ligament failure and suggested lowering the actual used axial femur force threshold for KTH injures both in neutral and out-of-position KTH axial impacts

Development of a Human Body Model for the Analysis of Side Impact Automotive Thoracic Trauma

Occupant thoracic injury incurred during side impact automotive crashes constitutes a significant portion of all fatal and non-fatal automotive injuries. The limited space between the impacting vehicle and occupant can result in significant loads and corresponding injury prior to deceleration of the impacting vehicle. Within the struck vehicle, impact occurs between the occupant and various interior components. Injury is sustained to human structural components such as the thoracic cage or shoulder, and to the internal visceral components such as the heart, lungs, or aorta. Understanding the mechanism behind these injuries is an important step in improving the side impact crash safety of vehicles. This study is focused on the development of a human body numerical model for the purpose of predicting thoracic response and trauma in side impact automotive crash. The human body model has been created using a previously developed thoracic numerical model, originally used for predicting thoracic trauma under simple impact conditions. The original version of the thorax model incorporated three-dimensional finite element representations of the spine, ribs, heart, lungs, major blood vessels, rib cage surface muscles and upper limbs. The present study began with improvements to the original thorax model and furthered with the development of remaining body components such that the model could be assessed in side impact conditions. The improvements to the thoracic model included improved geometry and constitutive response of the surface muscles, shoulder and costal cartilage. This detailed thoracic model was complimented with a pelvis, lower limbs, an abdomen and a head to produce the full body model. These components were implemented in a simplified fashion to provide representative response without significant computational costs. The model was developed and evaluated in a stepwise fashion using experimental data from the literature including side abdominal and pelvic pendulum impact tests. The accuracy of the model response was investigated using experimental testing performed on post mortem human subjects (PMHS) during side and front thoracic pendulum impacts. The model produced good agreement for the side thoracic and side shoulder pendulum impact tests and reasonable correlation during the frontal thoracic pendulum impact test. Complex loading via side sled impact tests was then investigated where the body was loaded unbelted in a NHTSA-type and WSU-type side sled test system. The thorax response was excellent when considering force, compression and injury (viscous criterion) versus time. Compression in the thorax was influenced by the arm position, which when aligned with the coronal plane produced the most aggressive form of compressive loading possible. The simplified components provided good response, falling slightly outside experimental response corridors defined as one standard deviation from the average of the experimental PMHS data. Overall, the predicted model response showed reasonable agreement with the experimental data, while at the same time highlighting areas for future developments. The results from this study suggested that the numerical finite element model developed herein could be used as a powerful tool for improving side impact automotive safety

Cochlear Compartments Segmentation and Pharmacokinetics using Micro Computed Tomography Images

Local drug delivery to the inner ear via micropump implants has the potential to be much more effective than oral drug delivery for treating patients with sensorineural hearing loss and to protect hearing from ototoxic insult due to noise exposure. Delivering appropriate concentrations of drugs to the necessary cochlear compartments is of paramount importance; however, directly measuring local drug concentrations over time throughout the cochlea is not possible. Indirect measurement using otoacoustic emissions and auditory brainstem response are ineffective as they only provide an estimate of concentration and are susceptible to non-linear sensitivity effects. Imaging modalities such as MRI with infused gadolinium contrast agent are limited due to the high spatial resolution requirement for pharmacokinetic analysis, especially in mice with cochlear length in the micron scale. We develop an intracochlear pharmacokinetic model using micro-computed tomography imaging of the cochlea during in vivo infusion of a contrast agent at the basal end of scala tympani through a cochleostomy. This approach requires accurately segmenting the main cochlear compartments: scala tympani (ST), scala media (SM) and scala vestibuli (SV). Each scan was segmented using 1) atlas-based deformable registration, and 2) V-Net, a encoder-decoder style convolutional neural network. The segmentation of these cochlear regions enable concentrations to be extracted along the length of each scala. These spatio-temporal concentration profiles are used to learn a concentration dependent diffusion coefficient, and transport parameters between the major scalae and to clearance. The pharmacokinetic model results are comparable to the current state of the art model, and can simulate concentrations for cases involving different infusion molecules and drug delivery protocols. While our model shows promising results, to extend the approach to larger animals and to generate accurate further experimental data, computational constraints, and time requirements of previous segmentation methods need to be mitigated. To this end, we extended the V-Net architecture with inclusion of spatial attention. Moreover, to enable segmentation in hardware restricted environments, we designed a 3D segmentation network using Capsule Networks that can provide improved segmentation performance along with 90% reduction in trainable parameters. Finally, to demonstrate the effectiveness of these networks, we test them on multiple public datasets. They are also tested on the cochlea dataset and pharmacokinetic model simulations will be validated against existing results