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The purpose of this computational study was to investigate the effects of neonate-focused clinical delivery maneuvers on brachial plexus (BP) during shoulder dystocia. During shoulder dystocia, the anterior shoulder of the neonate is obstructed behind the symphysis pubis of the maternal pelvis, postdelivery of the neonate's head. This is managed by a series of clinical delivery maneuvers. The goal of this study was to simulate these delivery maneuvers and study their effects on neonatal BP strain. Using madymo models of a maternal pelvis and a 90th-percentile neonate, various delivery maneuvers and positions were simulated including the lithotomy position alone of the maternal pelvis, delivery with the application of various suprapubic pressures (SPPs), neonate in an oblique position, and during posterior arm delivery maneuver. The resulting BP strain (%) along with the required maternal delivery force was reported in these independently simulated scenarios. The lithotomy position alone served as the baseline. Each of the successive maneuvers reported a decrease in the required delivery force and resulting neonatal BP strain. As the applied SPP force increased (three scenarios simulated), the required maternal delivery force and neonatal BP strain decreased. A further decrease in both delivery force and neonatal BP strain was observed in the oblique position, with the lowest delivery force and neonatal BP strain reported during the posterior arm delivery maneuver. Data obtained from the improved computational models in this study enhance our understanding of the effects of clinical maneuvers on neonatal BP strain during complicated birthing scenarios such as shoulder dystocia. [ABSTRACT FROM AUTHOR]

Noninvasive compression-induced anterior cruciate ligament rupture (ACL-R) is an easy and reproducible model for studying post-traumatic osteoarthritis (PTOA) in mice. However, equipment typically used for ACL-R is expensive, immobile, and not available to all researchers. In this study, we compared PTOA progression in mice injured with a low-cost custom ACL-rupture device (CARD) to mice injured with a standard system (ElectroForce 3200). We quantified anterior-posterior (AP) joint laxity immediately following injury, epiphyseal trabecular bone microstructure, and osteophyte volume at 2 and 6 weeks post injury using micro-computed tomography, and osteoarthritis progression and synovitis at 2 and 6 weeks post injury using whole-joint histology. We observed no significant differences in outcomes in mice injured with the CARD system compared to mice injured with the Electroforce (ELF) system. However, AP joint laxity data and week 2 micro-CT and histology outcomes suggested that injuries may have been slightly more severe and PTOA progressed slightly faster in mice injured with the CARD system compared to the ELF system. Altogether, these data confirm that ACL-R can be successfully and reproducibly performed with the CARD system and that osteoarthritis (OA) progression is mostly comparable to that of mice injured with the ELF system, though potentially slightly faster. The CARD system is low cost and portable, and we are making the plans and instructions freely available to all interested investigators in the hopes that they will find this system useful for their studies of OA in mice. [ABSTRACT FROM AUTHOR]

Accidental foot injuries including metatarsal fractures commonly result from compressive loading. The ability of personal protective equipment to prevent these traumatic injuries depends on the understanding of metatarsal fracture tolerance. However, the in situ fracture tolerance of the metatarsals under direct compressive loading to the foot's dorsal surface remains unexplored, even though the metatarsals are the most commonly fractured bones in the foot. The goal of this study was to quantify the in situ fracture tolerance of the metatarsals under simulated quasi-static compressive loading. Fresh-frozen cadaveric feet (n = 10) were mounted into a testing apparatus to replicate a natural stance and loaded at the midmetatarsals with a cylindrical bar to simulate a crushing-type injury. A 900 N compressive force was initially applied, followed by 225 N successive load increments. Specimens were examined using X-ray imaging between load increments to assess for the presence of metatarsal fractures. Descriptive statistics were conducted for metatarsal fracture force and deformation. Pearson correlation tests were used to quantify the correlation between fracture force with age and body mass index (BMI). The force and deformation at fracture were 1861 ± 642 N (mean ± standard deviation) and 22.6 ± 3.4 mm, respectively. Fracture force was correlated with donor BMI (r = 0.90). Every fractured specimen experienced a transverse fracture in the second metatarsal. New biomechanical data from this study further quantify the metatarsal fracture risk under compressive loading and will help to improve the development and testing of improved personal protective equipment for the foot to avoid catastrophic injury. [ABSTRACT FROM AUTHOR]

Brachial plexus (BP) birth injury has a reported incidence of 1 to 4 per 1000 live births. During complicated deliveries, neonatal, maternal, and other birth-related factors can cause over-stretching or avulsion of the neonatal brachial plexus leading to injury. Understanding biomechanical responses of the neonate brachial plexus when subjected to stretch can offer insight into the injury outcomes while guiding the development of preventative maneuvers that can help reduce the occurrence of neonatal brachial plexus injuries. This review article aims to offer a comprehensive overview of existing literature reporting biomechanical responses of the brachial plexus, in both adults and neonates, when subjected to stretch. Despite the discrepancies in the reported biomechanical properties of the brachial plexus, available studies confirm the loading rate and loading direction dependency of the brachial plexus tissue. Future studies, possibly in vivo, that utilize clinically relevant neonatal large animal models can provide translational failure values of the biomechanical parameters for the neonatal brachial plexus when subjected to stretch. [ABSTRACT FROM AUTHOR]

The knee valgus angle (KVA) is heavily researched as it has been shown to correlate to anterior cruciate ligament (ACL) injuries when measured during jumping activities. Many different methods of KVA calculation are often treated as equivalent. The purpose of this study is to elucidate differences between these commonly used angles within and across activities to determine if they can indeed properly be treated as equivalent. The kinematics of 23 female athletes, D1 soccer, D1 basketball, and club soccer (height=171.2±88.9cm, weight=66.3±8.6kg, age=19.8±1.9 years), was analyzed using a motion capture system during activities related to their sport and daily living. The abduction KVA, measured using body fixed axes, only correlated to the two-dimensional (2D) global reference frame angle (KVA 2G) in three of the six activities (walking, squatting, and walking down stairs), and one out of six in the three-dimensional (3D) measurements (jogging). This suggests that the abduction KVA does not always relate to other versions of KVA. The KVA with reference to the pelvis coordinate system (KVA 2P) correlated to the KVA 2G in six out of six activities (r= 0.734±0.037, P << 0.001) suggesting the pelvis can be utilized as a reference plane during rotating tasks, such as run-to-cut, when a fixed global system is less meaningful. Not all measures of KVA are equivalent and should be considered individually. A thorough understanding of the equivalence or nonequivalence of various measures of KVA is essential in understanding ACL injury risk. [ABSTRACT FROM AUTHOR]

With an increasing focus on long-term consequences of concussive brain injuries, there is a new emphasis on developing tools that can accurately predict the mechanical response of the brain to impact loading. Although finite element models (FEM) estimate the brain response under dynamic loading, these models are not capable of delivering rapid (~seconds) estimates of the brain's mechanical response. In this study, we develop a multibody spring-mass-damper model that estimates the regional motion of the brain to rotational accelerations delivered either about one anatomic axis or across three orthogonal axes simultaneously. In total, we estimated the deformation across 120 locations within a 50th percentile human brain. We found the multibody model (MBM) correlated, but did not precisely predict, the computed finite element response (average relative error: 18.4 ± 13.1%). We used machine learning (ML) to combine the prediction from the MBM and the loading kinematics (peak rotational acceleration, peak rotational velocity) and significantly reduced the discrepancy between the MBM and FEM (average relative error: 9.8 ± 7.7%). Using an independent sports injury testing set, we found the hybrid ML model also correlated well with predictions from a FEM (average relative error: 16.4 ± 10.2%). Finally, we used this hybrid MBM-ML approach to predict strains appearing in different locations throughout the brain, with average relative error estimates ranging from 8.6% to 25.2% for complex, multi-axial acceleration loading. Together, these results show a rapid and reasonably accurate method for predicting the mechanical response of the brain for single and multiplanar inputs, and provide a new tool for quickly assessing the consequences of impact loading throughout the brain. [ABSTRACT FROM AUTHOR]

With an increasing focus on long-term consequences of concussive brain injuries, there is a new emphasis on developing tools that can accurately predict the mechanical response of the brain to impact loading. Although finite element models (FEM) estimate the brain response under dynamic loading, these models are not capable of delivering rapid (~seconds) estimates of the brain's mechanical response. In this study, we develop a multibody spring-mass-damper model that estimates the regional motion of the brain to rotational accelerations delivered either about one anatomic axis or across three orthogonal axes simultaneously. In total, we estimated the deformation across 120 locations within a 50th percentile human brain. We found the multibody model (MBM) correlated, but did not precisely predict, the computed finite element response (average relative error: 18.4 ± 13.1%). We used machine learning (ML) to combine the prediction from the MBM and the loading kinematics (peak rotational acceleration, peak rotational velocity) and significantly reduced the discrepancy between the MBM and FEM (average relative error: 9.8 ± 7.7%). Using an independent sports injury testing set, we found the hybrid ML model also correlated well with predictions from a FEM (average relative error: 16.4 ± 10.2%). Finally, we used this hybrid MBM-ML approach to predict strains appearing in different locations throughout the brain, with average relative error estimates ranging from 8.6% to 25.2% for complex, multi-axial acceleration loading. Together, these results show a rapid and reasonably accurate method for predicting the mechanical response of the brain for single and multiplanar inputs, and provide a new tool for quickly assessing the consequences of impact loading throughout the brain. [ABSTRACT FROM AUTHOR]

There is a scant biomechanical literature that tests, in a laboratory setting, whether or not determinants of helmet fit affect biomechanical parameters associated with injury. Using conventional cycling helmets and repeatable models of the human head and neck, integrated into a guided drop impact experiment at speeds up to 6 m/s, this study tests the hypothesis that fit affects head kinematics, neck kinetics, and the extent to which the helmet moves relative to the underlying head (an indicator of helmet positional stability). While there were a small subset of cases where head kinematics were statistically significantly altered by fit, when viewed as a whole our measures of head kinematics suggest that fit does not systematically alter kinematics of the head secondary to impact. Similarly, when viewed as a whole, our data suggest that fit does not systematically alter resultant neck compression and resultant moment and associated biomechanical measures. Our data suggest that backward fit helmets exhibit the worst dynamic stability, in particular when the torso is impacted before the helmeted head is impacted, suggesting that the typical certification method of dynamical loading of a helmet to quantify retention may not be representative of highly plausible cycling incident scenarios where impact forces are first applied to the torso leading to loading of the neck prior to the head. Further study is warranted so that factors of fit that affect injury outcome are uncovered in both laboratory and real-world settings. [ABSTRACT FROM AUTHOR]

Linking head kinematics to injury risk has been the focus of numerous brain injury criteria. Although many early forms were developed using mechanics principles, recent criteria have been developed using empirical methods based on subsets of head impact data. In this study, a single-degree-of-freedom (sDOF) mechanical analog was developed to parametrically investigate the link between rotational head kinematics and brain deformation. Model efficacy was assessed by comparing the maximum magnitude of displacement to strain-based brain injury predictors from finite element (FE) human head models. A series of idealized rotational pulses covering a broad range of acceleration and velocity magnitudes (0.1-15 krad/s2 and 1-100 rad/s) with durations between 1 and 3000 ms were applied to the mechanical models about each axis of the head. Results show that brain deformation magnitude is governed by three categories of rotational head motion each distinguished by the duration of the pulse relative to the brain's natural period: for short-duration pulses, maximum brain deformation depended primarily on angular velocity magnitude; for long-duration pulses, brain deformation depended primarily on angular acceleration magnitude; and for pulses relatively close to the natural period, brain deformation depended on both velocity and acceleration magnitudes. These results suggest that brain deformation mechanics can be adequately explained by simple mechanical systems, since FE model responses and experimental brain injury tolerances exhibited similar patterns to the sDOF model. Finally, the sDOF model was the best correlate to strain-based responses and highlighted fundamental limitations with existing rotational-based brain injury metrics. [ABSTRACT FROM AUTHOR]

Venous ulcers are deep wounds that are located predominantly on the lower leg. They are prone to infection and once healed have a high probability of recurrence. Currently, there are no effective measures to predict and prevent venous ulcers from formation. Hence, the goal of this work was to develop a Windkessel-based model that can be used to identify hemodynamic parameters that change between healthy individuals and those with wounds. Once identified, these parameters have the potential to be used as indicators of when internal conditions change, putting the patient at higher risk for wound formation. In order to achieve this goal, blood flow responses in lower legs were measured experimentally by a laser Doppler perfusion monitor (LDPM) and simulated with a modeling approach. A circuit model was developed on the basis of the Windkessel theory. The hemodynamic parameters were extracted for three groups: legs with ulcers ("wounded"), legs without ulcers but from ulcer patients ("nonwounded"), and legs without vascular disease ("healthy"). The model was executed by two independent operators, and both operators reported significant differences between wounded and healthy legs in localized vascular resistance and compliance. The model successfully replicated the experimental blood flow profile. The global and local vascular resistances and compliance parameters rendered quantifiable differences between a population with venous ulcers and healthy individuals. This work supports that the Windkessel modeling approach has the potential to determine patient specific parameters that can be used to identify when conditions change making venous ulcer formation more likely. [ABSTRACT FROM AUTHOR]

Ocular trauma is one of the most common types of combat injuries resulting from the exposure of military personnel with improvised explosive devices. The injury mechanism associated with the primary blast wave is poorly understood. We employed a three-dimensional computational model, which included the main internal ocular structures of the eye, spatially varying thickness of the cornea-scleral shell, and nonlinear tissue properties, to calculate the intraocular pressure and stress state of the eye wall and internal ocular structure caused by the blast. The intraocular pressure and stress magnitudes were applied to estimate the injury risk using existing models for blunt impact and blast loading. The simulation results demonstrated that blast loading can induce significant stresses in the different components of the eyes that correlate with observed primary blast injuries in animal studies. Different injury models produced widely different injury risk predictions, which highlights the need for experimental studies evaluating mechanical and functional damage to the ocular structures caused by the blast loading. [ABSTRACT FROM AUTHOR]

Chronic joint pain is a widespread problem that frequently occurs with aging and trauma. Pain occurs most often in synovial joints, the body's load bearing joints. The mechanical and molecular mechanisms contributing to synovial joint pain are reviewed using two examples, the cervical spinal facet joints and the temporomandibular joint (TMJ). Although much work has focused on the macroscale mechanics of joints in health and disease, the combined influence of tissue mechanics, molecular processes, and nociception in joint pain has only recently become a focus. Trauma and repeated loading can induce structural and biochemical changes in joints, altering their microenvironment and modifying the biomechanics of their constitutive tissues, which themselves are innervated. Peripheral pain sensors can become activated in response to changes in the joint microenvironment and relay pain signals to the spinal cord and brain where pain is processed and perceived. In some cases, pain circuitry is permanently changed, which may be a potential mechanism for sustained joint pain. However, it is most likely that alterations in both the joint microenvironment and the central nervous system (CNS) contribute to chronic pain. As such, the challenge of treating joint pain and degeneration is temporally and spatially complicated. This review summarizes anatomy, physiology, and pathophysiology of these joints and the sensory pain relays. Pain pathways are postulated to be sensitized by many factors, including degeneration and biochemical priming, with effects on thresholds for mechanical injury and/or dysfunction. Initiators of joint pain are discussed in the context of clinical challenges including the diagnosis and treatment of pain. [ABSTRACT FROM AUTHOR]

The article announces the winners of the 2016 Summer Biomechanics, Bioengineering, and Biotransport Conference Student Paper Competition including John P. Carruth, Sonia Kartha, and Jack A. Martin.