Effect of Workpiece/Tool Heat Transfer and Friction Coefficients on Accuracy of Simulated Temperatures and Torques in a Friction Stir Welding Plunge

Friction stir process models are typically validated by tuning heat transfer and friction coefficients until measured temperatures in either the tool or workpiece, but rarely in both, match simulated results. A three-dimensional finite element model for a tool plunge in an AA 6061-T6 is validated for temperature predictions in both the tool and workpiece using a friction coefficient that varies with time. Peak workpiece temperatures were within 1.5% of experimental temperatures and tool temperatures were off by 80 °C. The sensitivity of the predicted temperatures with respect to the workpiece/tool heat transfer coefficient was shown to be high for the tool and low for the workpiece, while the spindle torque was slightly underpredicted in the best case. These results show that workpiece/tool interface properties must be tuned by considering predictions on both sides of the heat generation interface in order to ensure a reliable process simulation.

Numerical Study on the Axial Compressive Behavior of Steel-Tube-Confined Concrete-Filled Steel Tubes

To improve the concrete confinement and mechanical properties of concrete-filled steel tube (CFST) columns, a new configuration of steel-tube-confined concrete-filled steel tube (T-CFST) columns has recently been developed, in which an outer steel tube is employed externally, and the additional tube does not sustain the axial load directly. This preliminary experimental study revealed that, due to the effective concrete confinement by the outer steel tube, the T-CFST column achieves higher compressive strength and more ductile deformation compared to the CFST columns of the same steel ratio. In this study, two finite element (FE) models were developed for the T-CFST cross-section and stub column, respectively. The numerical study results revealed that the concrete can be constrained by the outer steel tube at the beginning of loading and the outer steel tube hoop stress can reach its yield strength at the column's compressive strength, showing its effective confinement to the concrete. Numerous data were generated by the developed FE model to cover a wide range of parameters. Based on that, the calculation methods for the stress components of the inner and outer steel tubes are proposed. Finally, a suitable prediction method is proposed, utilizing the superposition method to determine the compressive strength of the T-CFST stub column, and the results of the calculation method and FE model agree well with each other. This research is the basis for promoting further research of T-CFST columns.

Polyurethane Culture Substrates Enable Long-Term Neuron Monoculture in a Human in vitro Model of Neurotrauma

Human induced pluripotent stem cell (hiPSC)-derived cells can reproduce human-specific pathophysiology, patient-specific vulnerability, and gene-environment interactions in neurological disease. Human in vitro models of neurotrauma therefore have great potential to advance the field. However, this potential cannot be realized until important biomaterials challenges are addressed. Status quo stretch injury models of neurotrauma culture cells on sheets of polydimethylsiloxane (PDMS) that are incompatible with long-term monoculture of hiPSC-derived neurons. Here, we overcame this challenge in an established human in vitro neurotrauma model by replacing PDMS with a highly biocompatible form of polyurethane (PU). This substitution allowed long-term monoculture of hiPSC-derived neurons. It also changed the biomechanics of stretch injury. We quantified these changes experimentally using high-speed videography and digital image correlation. We used finite element modeling to quantify the influence of the culture substrate's thickness, stiffness, and coefficient of friction on membrane stretch and concluded that the coefficient of friction explained most of the observed biomechanical changes. Despite these changes, we demonstrated that the modified model produced a robust, dose-dependent trauma phenotype in hiPSC-derived neuron monocultures. In summary, the introduction of this PU film makes it possible to maintain hiPSC-derived neurons in monoculture for long periods in a human in vitro neurotrauma model. In doing so, it opens new horizons in the field of neurotrauma by enabling the unique experimental paradigms (e.g., isogenic models) associated with hiPSC-derived neurons.

Metal-Metal Bonding Process Research Based on Xgboost Machine Learning Algorithm

Conventionally, the optimization of bonding process parameters requires multi-parameter repetitive experiments, the processing of data, and the characterization of complex relationships between process parameters, and performance must be achieved with the help of new technologies. This work focused on improving metal-metal bonding performance by applying SLJ experiments, finite element models (FEMs), and the Xgboost machine learning (ML) algorithm. The importance ranking of process parameters on tensile-shear strength (TSS) was evaluated with the interpretation toolkit SHAP (Shapley additive explanations) and it optimized reasonable bonding process parameters. The validity of the FEM was verified using SLJ experiments. The Xgboost models with 70 runs can achieve better prediction results. According to the degree of influence, the process parameters affecting the TSS ranked from high to low are roughness, adhesive layer thickness, and lap length, and the corresponding optimized values were 0.89 μm, 0.1 mm, and 27 mm, respectively. The experimentally measured TSS values increased by 14% from the optimized process parameters via the Xgboost model. ML methods provide a more accurate and intuitive understanding of process parameters on TSS.

Study of tractor side tilt operation on intervertebral disc injury between L4 and L5 in drivers

The tilting of the cab seat when the tractor is in deep ploughing operation changes the sitting position of the driver, which may accelerate lumbar spine injury. This paper adopts the musculoskeletal model and the finite element model of the lumbar L4-L5 segment to predict the maximum Von-Mises stress and maximum strain of the driver's lumbar L4-L5 segment intervertebral disc. In this study, we used 3D motion capture to obtain the driver's spine position spatial data when the tractor tilted at different angles. A tractor-driver musculoskeletal model and a finite element model of the lumbar spine L4-L5 segments were created in AnyBody™ and Abaqus, respectively. The tractor-driver musculoskeletal model was used to calculate the load of the driver's lumbar spine L4-L5 segment at different angles of tractor tilt, which was used as the load condition of the finite element model of the lumbar spine L4-L5 segment, and then the influence of tractor tilt angle and vibration on the driver's lumbar spine L4-L5 disc was studied. The results show that the maximum Von-Mises stress and maximum strain of the driver's lumbar L4-L5 intervertebral disc will increase due to the tilt. The maximum Von-Mises stress occurs in the annulus II, and the maximum strain occurs in the upper end plate of the intervertebral disc. With the occurrence of tilt, the position of the maximum Von-Mises stress changes, which can lead to disc injury to the driver, and vibration may exacerbate this injury.

The Potential of Deep Learning to Advance Clinical Applications of Computational Biomechanics

When combined with patient information provided by advanced imaging techniques, computational biomechanics can provide detailed patient-specific information about stresses and strains acting on tissues that can be useful in diagnosing and assessing treatments for diseases and injuries. This approach is most advanced in cardiovascular applications but can be applied to other tissues. The challenges for advancing computational biomechanics for real-time patient diagnostics and treatment include errors and missing information in the patient data, the large computational requirements for the numerical solutions to multiscale biomechanical equations, and the uncertainty over boundary conditions and constitutive relations. This review summarizes current efforts to use deep learning to address these challenges and integrate large data sets and computational methods to enable real-time clinical information. Examples are drawn from cardiovascular fluid mechanics, soft-tissue mechanics, and bone biomechanics. The application of deep-learning convolutional neural networks can reduce the time taken to complete image segmentation, and meshing and solution of finite element models, as well as improving the accuracy of inlet and outlet conditions. Such advances are likely to facilitate the adoption of these models to aid in the assessment of the severity of cardiovascular disease and the development of new surgical treatments.

Finite element analysis of tooth movement under different retraction force and intrusive force in double-archwire lingual orthodontics system

The objectives of this study were to evaluate the tooth movement tendency during space closure in maxillary anterior teeth by various combinations of retraction force and intrusive force in a double-archwire lingual orthodontic system. Mini-implant-double slot lingual orthodontics system models of the bilateral maxillary first premolar extraction cases were constructed. Three-dimensional finite element models of the maxilla were constructed with definite position mini-implants (8 mm) and power arms (6 mm). Different retraction forces(50gf、100gf、150gf)were applied with the help of a nickel-titanium closed coil spring on the plate side. Intrusive forces(0gf、50gf、100gf)were applied with the help of the mini-implant between the two central incisors, and the initial displacements of the maxillary anterior teeth were analyzed. Variable amounts of displacements like controlled tipping, uncontrolled tipping, lingual crown tipping, labial root tipping, extrusion and distal crown tipping were observed in all the models, and these tendencies increased as the magnitude of retraction force increased, and these tendencies decreased as the magnitude of intrusive force increased. When the intrusive force was greater than or equal to the retraction force, the maxillary central incisors showed the trend of lingual crown tipping and labial root tipping, resulting in uncontrolled tipping movement. In terms of horizontal changes, the increasing width of bilateral anterior teeth was observed, with canines showing the least increasing trend. Various combinations of retraction force and intrusive force in a double-archwire lingual orthodontic system provide a new choice for torque control of the anterior teeth. Although anterior mini-implants and elastics can achieve incisor intrusion and lingual root torque, they cannot achieve the expected torque without additional torque control methods.

Biophysical modeling of the electric field magnitude and distribution induced by electrical stimulation with intracerebral electrodes

Intracranial electrodes are used clinically for diagnostic or therapeutic purposes, notably in drug-refractory epilepsy (DRE) among others. Visualization and quantification of the energy delivered through such electrodes is key to understanding how the resulting electric fields modulate neuronal excitability, i.e. the ratio between excitation and inhibition. Quantifying the electric field induced by electrical stimulation in a patient-specific manner is challenging, because these electric fields depend on a number of factors: electrode trajectory with respect to folded brain anatomy, biophysical (electrical conductivity / permittivity) properties of brain tissue and stimulation parameters such as electrode contacts position and intensity.
Here, we aimed to evaluate various biophysical models for characterizing the electric fields induced by electrical stimulation in DRE patients undergoing stereoelectroencephalography (SEEG) recordings in the context of pre-surgical evaluation. This stimulation was performed with multiple-contact intracranial electrodes used in routine clinical practice. We introduced realistic 3D models of electrode geometry and trajectory in the neocortex. For the electrodes, we compared point (0D) and line (1D) sources approximations. For brain tissue, we considered three configurations of increasing complexity: a 6-layer spherical model, a toy model with a sulcus representation, replicating results from previous approaches; and went beyond the state-of-the-art by using a realistic head model geometry.
Electrode geometry influenced the electric field distribution at close distances (~3 mm) from the electrode axis. For larger distances, the volume conductor geometry and electrical conductivity dominated electric field distribution. These results are the first step towards accurate and computationally tractable patient-specific models of electric fields induced by neuromodulation and neurostimulation procedures.&#xD.

Biomechanical Effects of a Novel Pedicle Screw W-Type Rod Fixation for Lumbar Spondylolysis: A Finite Element Analysis

Lumbar spondylolysis involves anatomical defects of the pars interarticularis, which causes instability during motion. The instability can be addressed through instrumentation with posterolateral fusion (PLF). We developed a novel pedicle screw W-type rod fixation system and evaluated its biomechanical effects in comparison with PLF and Dynesys stabilization for lumbar spondylolysis via finite element (FE) analysis. A validated lumbar spine model was built using ANSYS 14.5 software. Five FE models were established simulating the intact L1-L5 lumbar spine (INT), bilateral pars defect (Bipars), bilateral pars defect with PLF (Bipars_PLF), Dynesys stabilization (Bipars_Dyn), and W-type rod fixation (Bipars_Wtyp). The range of motion (ROM) of the affected segment, the disc stress (DS), and the facet contact force (FCF) of the cranial segment were compared. In the Bipars model, ROM increased in extension and rotation. Compared with the INT model, Bipars_PLF and Bipars_Dyn exhibited remarkably lower ROMs for the affected segment and imposed greater DS and FCF in the cranial segment. Bipars_Wtyp preserved more ROM and generated lower stress at the cranial segment than Bipars_PLF or Bipars_Dyn. The injury model indicates that this novel pedicle screw W-type rod for spondylolysis fixation could return ROM, DS, and FCF to levels similar to preinjury.

Study on Flexural Performance of Aluminum Alloy Gusset Joints Subjected to Bending Moment and Shear Force

Aluminum alloy gusset (AAG) joints are widely applied in space reticulated shell structures. To investigate the flexural performance of AAG joints under the combined action of shear force and in-plane and out-of-plane bending moments, this analysis was developed by means of finite element (FE) models implemented in the non-linear code ABAQUS, and the accuracy of the FE simulation results based on the existing AAG joint test results was verified. The FE simulation results effectively described the mechanical properties of the AAG joints, including the failure mode, deformation process and bending moment-rotation curves. Furthermore, a parametric study was conducted by varying the height of the member section, the number of bolts, the radius of the joint plate, the thickness of the joint plate, the bolt preload force, and the ratio of in-plane to out-of-plane bending moments. It was found that these parameters had different effects on the bending behavior of the AAG joints.

Biomechanics of Traumatic Head and Neck Injuries on Women: A State-of-the-Art Review and Future Directions

The biomechanics of traumatic injuries of the human body as a consequence of road crashes, falling, contact sports, and military environments have been studied for decades. In particular, traumatic brain injury (TBI), the so-called "silent epidemic", is the traumatic insult responsible for the greatest percentage of death and disability, justifying the relevance of this research topic. Despite its great importance, only recently have research groups started to seriously consider the sex differences regarding the morphology and physiology of women, which differs from men and may result in a specific outcome for a given traumatic event. This work aims to provide a summary of the contributions given in this field so far, from clinical reports to numerical models, covering not only the direct injuries from inertial loading scenarios but also the role sex plays in the conditions that precede an accident, and post-traumatic events, with an emphasis on neuroendocrine dysfunctions and chronic traumatic encephalopathy. A review on finite element head models and finite element neck models for the study of specific traumatic events is also performed, discussing whether sex was a factor in validating them. Based on the information collected, improvement perspectives and future directions are discussed.

3D Printing Silk-Based Bioresorbable Piezoelectric Self-Adhesive Holey Structures for In Vivo Monitoring on Soft Tissues

Flexible and biocompatible adhesives with sensing capabilities can be integrated onto human body and organ surfaces, characterized by complex geometries, thus having the potential to sense their physiological stimuli offering monitoring and diagnosis of a wide spectrum of diseases. The challenges in this innovative field are the following: (i) the coupling method between the smart adhesive and the soft human substrates, (ii) the bioresorbable behavior of the material, and (iii) the electrical exchange with the substrate. Here, we introduce a multifunctional composite by mixing silk fibroin, featuring piezoelectric properties, with a soluble plant-derived polyphenol (i.e., chestnut tannin) modified with graphene nanoplatelets. This material behaves as a glue on different substrates and gives rise to high elongation at break, conformability, and adhesive performances to gastrointestinal tissues in a rat model and favors the printability via extrusion-based 3D printing. Exploiting these properties, we designed a bioresorbable 3D printed flexible and self-adhesive piezoelectric device that senses the motility once applied onto a phantom intestine and the hand gesture by signal translation. Experimental results also include the biocompatibility study using gastrointestinal cells. These findings could have applicability in animal model studies, and, thanks to the bioresorbable behavior of the materials, such an adhesive device could be used for monitoring the motility of the gastrointestinal tract and for the diagnosis of motility disorders.

Biomechanical effect of anatomical tibial component design on load distribution of medial proximal tibial bone in total knee arthroplasty : finite element analysis indicating anatomical design prevents stress-shielding

Aims

This study aimed to identify the effect of anatomical tibial component (ATC) design on load distribution in the periprosthetic tibial bone of Koreans using finite element analysis (FEA).

Methods

3D finite element models of 30 tibiae in Korean women were created. A symmetric tibial component (STC, NexGen LPS-Flex) and an ATC (Persona) were used in surgical simulation. We compared the FEA measurements (von Mises stress and principal strains) around the stem tip and in the medial half of the proximal tibial bone, as well as the distance from the distal stem tip to the shortest anteromedial cortical bone. Correlations between this distance and FEA measurements were then analyzed.

Results

The distance from the distal stem tip to the shortest cortical bone showed no statistically significant difference between implants. However, the peak von Mises stress around the distal stem tip was higher with STC than with ATC. In the medial half of the proximal tibial bone: 1) the mean von Mises stress, maximum principal strain, and minimum principal strain were higher with ATC; 2) ATC showed a positive correlation between the distance and mean von Mises stress; 3) ATC showed a negative correlation between the distance and mean minimum principal strain; and 4) STC showed no correlation between the distance and mean measurements.

Conclusion

Implant design affects the load distribution on the periprosthetic tibial bone, and ATC can be more advantageous in preventing stress-shielding than STC. However, under certain circumstances with short distances, the advantage of ATC may be offset.

Cite this article: Bone Joint Res 2022;11(5):252–259.

Mechanical Design Optimization of Prosthetic Hand's Fingers: Novel Solutions towards Weight Reduction

From the mechanical function of grabbing objects to the emotional aspect of gesturing, the functionality of human hands is fundamental for both physical and social survival. Therefore, the loss of one or both hands represents a devastating issue, exacerbated by long rehabilitation times and psychological treatments. Prosthetic arms represent an effective solution to provide concrete functional and esthetical support. However, commercial hand prostheses still lack an optimal combination of light weight, durability, adequate cosmetic appearance, and affordability. Among these aspects, the priority for upper-limb prosthesis users is weight, a key parameter that influences both the portability and the functionality of the system. The purpose of this work is to optimize the design of the MyHand prosthesis, by redesigning both the proximal and distal finger and thumb in light of finding an optimal balance between weight reduction and adequate stiffness. Starting from elastic–plastic numerical models and experimental tests on obsolete components, analyzed under the worst loading condition, five different design solutions are suggested. An iterative topology optimization process locates the regions where material removal is permitted. From these results, 2 mm geometrical patterns on the top surface of the hand prosthesis appear as the most prominent, preventing object intrusion.

Substitution for In Vitro and In Vivo Tests: Computational Models from Cell Attachment to Tissue Regeneration

To get an optimal product of orthopaedic implant or regenerative medicine needs to follow trial-and-error analyses to investigate suitable product's material, structure, mechanical properites etc. The whole process from in vivo tests to clinical trials is expensive and time-consuming. Computational model is seen as a useful analysis tool to make the product development. A series of models for simulating tissue engineering process from cell attachment to tissue regeneration are reviewed. The challenging is that models for simulating tissue engineering processes are developed separately. From cell to tissue regeneration, it would go through blood injection after moving out the defect; to cell disperse and attach on the scaffold; to proliferation, migration and differentiation; and to the final part-becoming mature tissues. This paper reviewed models that related to tissue engineering process, aiming to provide an opportunity for researchers to develop a mature model for whole tissue engineering process. This article focuses on the model analysis methods of cell adhesion, nutrient transport and cell proliferation, differentiation and migration in tissue engineering. In cell adhesion model, one of the most accurate method is to use discrete phase model to govern cell movement and use Stanton-Rutland model for simulating cell attachment. As for nutrient transport model, numerical model coupling with volume of fluid model and species transport model together is suitable for predicting nutrient transport process. For cell proliferation, differentiation and migration, finite element method with random-walk algorithm is one the most advanced way to simulate these processes. Most of the model analysis methods require further experiments to verify the accuracy and effectiveness. Due to the lack of technology to detect the rate of nutrient diffusion, there are especially few researches on model analysis methods in the area of blood coagulation. Therefore, there is still a lot of work to be done in the research of the whole process model method of tissue engineering. In the future, the numerical model would be seen as an optimal way to investigate tissue engineering products bioperformance and also enable to optimize the parameters and material types of the tissue engineering products.

Scaling of joint mass and metabolism fluctuations in in silico cell-laden spheroids

Allometric scaling has many applications, from the prediction of pharmacokinetics in animals and humans to the probing of ecosystem dynamics. Most studies have neglected to account for variations and fluctuations, although they are intrinsic features of all biological systems. To understand how metabolic scaling emerges in the presence of variations, we developed computer-generated models of cell-laden spheroids to define the experimental size range of cell cultures with quantifiable similitudes in terms of fluctuations and metabolic scaling with living organisms. We show that the estimates of scaling exponents may change with increasing variability in both mass and metabolic rate. The computational pipeline described underpins the sound design of statistically meaningful cell-based models, with impacts in both biomedical science and ecology.

Variations and fluctuations are characteristic features of biological systems and are also manifested in cell cultures. Here, we describe a computational pipeline for identifying the range of three-dimensional (3D) cell-aggregate sizes in which nonisometric scaling emerges in the presence of joint mass and metabolic rate fluctuations. The 3D cell-laden spheroids with size and single-cell metabolic rates described by probability density functions were randomly generated in silico. The distributions of the resulting metabolic rates of the spheroids were computed by modeling oxygen diffusion and reaction. Then, a method for estimating scaling exponents of correlated variables through statistically significant data collapse of joint probability distributions was developed. The method was used to identify a physiologically relevant range of spheroid sizes, where both nonisometric scaling and a minimum oxygen concentration (0.04 mol⋅m⁻³) is maintained. The in silico pipeline described enables the prediction of the number of experiments needed for an acceptable collapse and, thus, a consistent estimate of scaling parameters. Using the pipeline, we also show that scaling exponents may be significantly different in the presence of joint mass and metabolic-rate variations typically found in cells. Our study highlights the importance of incorporating fluctuations and variability in size and metabolic rates when estimating scaling exponents. It also suggests the need for taking into account their covariations for better understanding and interpreting experimental observations both in vitro and in vivo and brings insights for the design of more predictive and physiologically relevant in vitro models.

Neural Tissue Degeneration in Rosenthal's Canal and Its Impact on Electrical Stimulation of the Auditory Nerve by Cochlear Implants: An Image-Based Modeling Study

Sensorineural deafness is caused by the loss of peripheral neural input to the auditory nerve, which may result from peripheral neural degeneration and/or a loss of inner hair cells. Provided spiral ganglion cells and their central processes are patent, cochlear implants can be used to electrically stimulate the auditory nerve to facilitate hearing in the deaf or severely hard-of-hearing. Neural degeneration is a crucial impediment to the functional success of a cochlear implant. The present, first-of-its-kind two-dimensional finite-element model investigates how the depletion of neural tissues might alter the electrically induced transmembrane potential of spiral ganglion neurons. The study suggests that even as little as 10% of neural tissue degeneration could lead to a disproportionate change in the stimulation profile of the auditory nerve. This result implies that apart from encapsulation layer formation around the cochlear implant electrode, tissue degeneration could also be an essential reason for the apparent inconsistencies in the functionality of cochlear implants.

Open-Source Routines for Building Personalized Left Ventricular Models From Cardiac Magnetic Resonance Imaging Data

Creating patient-specific models of the heart is a promising approach for predicting outcomes in response to congenital malformations, injury, or disease, as well as an important tool for developing and customizing therapies. However, integrating multimodal imaging data to construct patient-specific models is a nontrivial task. Here, we propose an approach that employs a prolate spheroidal coordinate system to interpolate information from multiple imaging datasets and map those data onto a single geometric model of the left ventricle (LV). We demonstrate the mapping of the location and transmural extent of postinfarction scar segmented from late gadolinium enhancement (LGE) magnetic resonance imaging (MRI), as well as mechanical activation calculated from displacement encoding with stimulated echoes (DENSE) MRI. As a supplement to this paper, we provide MATLAB and Python versions of the routines employed here for download from SimTK.

Modeling of inflicted head injury by shaking trauma in children: what can we learn? : Part II: A systematic review of mathematical and physical models

Various types of complex biomechanical models have been published in the literature to better understand processes related to inflicted head injury by shaking trauma (IHI-ST) in infants. In this systematic review, a comprehensive overview of these models is provided. A systematic review was performed in MEDLINE and Scopus for articles using physical (e.g. dolls) and mathematical (e.g. computer simulations) biomechanical models for IHI-ST. After deduplication, the studies were independently screened by two researchers using PRISMA methodology and data extracted from the papers is represented in a “7-steps description”, addressing the different processes occurring during IHI-ST. Eleven papers on physical models and 23 papers on mathematical models were included after the selection process. In both categories, some models focus on describing gross head kinematics during IHI-ST events, while others address the behavior of internal head- and eye structures in various levels of detail. In virtually all physical and mathematical models analyzed, injury thresholds are derived from scaled non-infant data. Studies focusing on head kinematics often use injury thresholds derived from impact studies. It remains unclear to what extent these thresholds reflect the failure thresholds of infant biological material. Future research should therefore focus on investigating failure thresholds of infant biological material as well as on possible alternative injury mechanism and alternative injury criteria for IHI-ST.

Case-specific non-linear finite element models to predict failure behavior in two functional spinal units

Current finite element (FE) models predicting failure behavior comprise single vertebrae, thereby neglecting the role of the posterior elements and intervertebral discs. Therefore, this study aimed to develop a more clinically relevant, case-specific non-linear FE model of two functional spinal units able to predict failure behavior in terms of (i) the vertebra predicted to fail; (ii) deformation of the specimens; (iii) stiffness; and (iv) load to failure. For this purpose, we also studied the effect of different bone density-mechanical properties relationships (material models) on the prediction of failure behavior. Twelve two functional spinal units (T6-T8, T9-T11, T12-L2, and L3-L5) with and without artificial metastases were destructively tested in axial compression. These experiments were simulated using CT-based case-specific non-linear FE models. Bone mechanical properties were assigned using four commonly used material models. In 10 of the 11 specimens our FE model was able to correctly indicate which vertebrae failed during the experiments. However, predictions of the three-dimensional deformations of the specimens were less promising. Whereas stiffness of the whole construct could be strongly predicted (R²  = 0.637-0.688, p < 0.01), we obtained weak correlations between FE predicted and experimentally determined load to failure, as defined by the total reaction force exhibiting a drop in force (R²  = 0.219-0.247, p > 0.05). Additionally, we found that the correlation between predicted and experimental fracture loads did not strongly depend on the material model implemented, but the stiffness predictions did. In conclusion, this work showed that, in its current state, our FE models may be used to identify the weakest vertebra, but that substantial improvements are required in order to quantify in vivo failure loads. © 2018 The Authors. Journal of Orthopaedic Research® Published by Wiley Periodical, Inc. on behalf of Orthopaedic Research Society. J Orthop Res 36:3208-3218, 2018.

Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter Variability

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.

Quantitative Assessments of Mechanical Responses upon Radial Extracorporeal Shock Wave Therapy

Although radial extracorporeal shock wave therapy (rESWT) has been widely used to treat orthopedic disorders with promising clinical results, rESWT largely relies on clinicians' personal experiences and arbitrary judgments, without knowing relationships between administration doses and effective doses at target sites. In fact, practitioners lack a general and reliable way to assess propagation and distribution of pressure waves inside biological tissues quantitatively. This study develops a methodology to combine experimental measurements and computational simulations to obtain pressure fields from rESWT through calibrating and validating computational models with experimental measurements. Wave pressures at the bottom of a petri dish and inside biological tissues are measured, respectively, by attaching and implanting flexible membrane sensors. Detailed wave dynamics are simulated through explicit finite element analyses. The data decipher that waves from rESWT radiate directionally and can be modeled as acoustic waves generated from a vibrating circular piston. Models are thus established to correlate pressure amplitudes at the bottom of petri dishes and in the axial direction of biological tissues. Additionally, a pilot simulation upon rESWT for human lumbar reveals a detailed and realistic pressure field mapping. This study will open a new avenue of personalized treatment planning and mechanism research for rESWT.

Biomechanics of the sclera and effects on intraocular pressure

Accumulating evidence indicates that glaucoma is a multifactorial neurodegenerative disease characterized by the loss of retinal ganglion cells (RGC), resulting in gradual and progressive permanent loss of vision. Reducing intraocular pressure (IOP) remains the only proven method for preventing and delaying the progression of glaucomatous visual impairment. However, the specific role of IOP in optic nerve injury remains controversial, and little is known about the biomechanical mechanism by which elevated IOP leads to the loss of RGC. Published studies suggest that the biomechanical properties of the sclera and scleral lamina cribrosa determine the biomechanical changes of optic nerve head, and play an important role in the pathologic process of loss of RGC and optic nerve damage. This review focuses on the current understanding of biomechanics of sclera in glaucoma and provides an overview of the possible interactions between the sclera and IOP. Treatments and interventions aimed at the sclera are also discussed.

Analysis of Uncertainty and Variability in Finite Element Computational Models for Biomedical Engineering: Characterization and Propagation

Computational modeling has become a powerful tool in biomedical engineering thanks to its potential to simulate coupled systems. However, real parameters are usually not accurately known, and variability is inherent in living organisms. To cope with this, probabilistic tools, statistical analysis and stochastic approaches have been used. This article aims to review the analysis of uncertainty and variability in the context of finite element modeling in biomedical engineering. Characterization techniques and propagation methods are presented, as well as examples of their applications in biomedical finite element simulations. Uncertainty propagation methods, both non-intrusive and intrusive, are described. Finally, pros and cons of the different approaches and their use in the scientific community are presented. This leads us to identify future directions for research and methodological development of uncertainty modeling in biomedical engineering.

Total arthroplasty of basal thumb joint with Elektra prothesis: an in vitro analysis

The reported outcomes of the Elektra thumb carpo-metacarpal joint implant have been very variable. This study evaluates the influence of daily cyclic loads and the type of the screw-fit cup insertion technique in the trapezium, with and without prior threading, on the structural bone behaviour. The study was performed experimentally to predict initial implant stability and cortical bone strains. Computational models were developed to assess the structural cancellous bone behaviour. The use of Elektra implant considerably changed the bone strain behaviour compared with the intact joint. This may be associated with risks of cancellous bone fatigue failure due to overload, particularly in the trapezium. The joint load magnitude has a more important structural role than that of the screw-fit cup insertion technique. Limiting the magnitude of thumb loads after arthroplasty may contribute positively to the longevity of this procedure.

LEVEL OF EVIDENCE

V.

Nodal versus Total Axonal Strain and the Role of Cholesterol in Traumatic Brain Injury

Traumatic brain injury (TBI) is a health threat that affects every year millions of people involved in motor vehicle and sporting accidents, and thousands of soldiers in battlefields. Diffuse axonal injury (DAI) is one of the most frequent types of TBI leading to death. In DAI, the initial traumatic event is followed by a cascade of biochemical changes that take time to develop in full, so that symptoms may not become apparent until days or weeks after the original injury. Hence, DAI is a dynamic process, and the opportunity exists to prevent its progression provided the initial trauma can be predicted at the molecular level. Here, we present preliminary evidence from micro-finite element (FE) simulations that the mechanical response of central nervous system myelinated fibers is dependent on the axonal diameter, the ratio between axon diameter and fiber diameter (g-ratio), the microtubules density, and the cholesterol concentration in the axolemma and myelin. A key outcome of the simulations is that there is a significant difference between the overall level of strain in a given axonal segment and the level of local strain in the Ranvier nodes contained in that segment, with the nodal strain being much larger than the total strain. We suggest that the acquisition of this geometric and biochemical information by means of already available high resolution magnetic resonance imaging techniques, and its incorporation in current FE models of the brain will enhance the models capacity to predict the site and magnitude of primary axonal damage upon TBI.

The effects of plaque morphology and material properties on peak cap stress in human coronary arteries

Heart attacks are often caused by rupture of caps of atherosclerotic plaques in coronary arteries. Cap rupture occurs when cap stress exceeds cap strength. We investigated the effects of plaque morphology and material properties on cap stress. Histological data from 77 coronary lesions were obtained and segmented. In these patient-specific cross sections, peak cap stresses were computed by using finite element analyses. The finite element analyses were 2D, assumed isotropic material behavior, and ignored residual stresses. To represent the wide spread in material properties, we applied soft and stiff material models for the intima. Measures of geometric plaque features for all lesions were determined and their relations to peak cap stress were examined using regression analyses. Patient-specific geometrical plaque features greatly influence peak cap stresses. Especially, local irregularities in lumen and necrotic core shape as well as a thin intima layer near the shoulder of the plaque induce local stress maxima. For stiff models, cap stress increased with decreasing cap thickness and increasing lumen radius (R = 0.79). For soft models, this relationship changed: increasing lumen radius and increasing lumen curvature were associated with increased cap stress (R = 0.66). The results of this study imply that not only accurate assessment of plaque geometry, but also of intima properties is essential for cap stress analyses in atherosclerotic plaques in human coronary arteries.

A method to estimate biomechanics and mechanical properties of optic nerve head tissues from parameters measurable using optical coherence tomography

Optic nerve head (ONH) tissue properties and biomechanics remain mostly unmeasurable in the experiment. We hypothesized that these can be estimated numerically from ocular parameters measurable in vivo with optical coherence tomography (OCT). Using parametric models representing human ONHs we simulated acute intraocular pressure (IOP) increases (10 mmHg). Statistical models were fit to predict, from OCT-measurable parameters, 15 outputs, including ONH tissue properties, stresses, and deformations. The calculations were repeated adding parameters that have recently been proposed as potentially measurable with OCT. We evaluated the sensitivity of the predictions to variations in the experimental parameters. Excellent fits were obtained to predict all outputs from the experimental parameters, with cross-validated R2s between 0.957 and 0.998. Incorporating the potentially measurable parameters improved fits significantly. Predictions of tissue stiffness were accurate to within 0.66 MPa for the sclera and 0.24 MPa for the lamina cribrosa. Predictions of strains and stresses were accurate to within 0.62% and 4.9 kPa, respectively. Estimates of ONH biomechanics and tissue properties can be obtained quickly from OCT measurements using an applet that we make freely available. These estimates may improve understanding of the eye sensitivity to IOP and assessment of patient risk for development or progression of glaucoma.

Determinants of forearm strength in postmenopausal women

Bone strength at the ultradistal radius, quantified by micro-finite element modeling, can be predicted by variables obtained from high-resolution peripheral quantitative computed tomography scans. The specific formula for this bone strength surrogate (-555.2 + 8.1 × [trabecular vBMD] + 19.6 × [cortical area] + 4.2 × [total cross-sectional area]) should be validated and tested in fracture risk assessment.

INTRODUCTION

The purpose of this study was to identify key determinants of ultradistal radius (UDR) strength and evaluate their relationships with age, sex steroid levels, and measures of habitual skeletal loading.

METHODS

UDR failure load (~strength) was assessed by micro-finite element (μFE) modeling in 105 postmenopausal controls from an earlier forearm fracture case-control study. Predictors of bone strength obtained by high-resolution peripheral quantitative computed tomography (HRpQCT) in this group were then evaluated in a population-based cohort of 214 postmenopausal women. Sex steroids were measured by mass spectrometry.

RESULTS

A surrogate variable (-555.2 + 8.1 × [trabecular vBMD] + 19.6 × [cortical area] + 4.2 × [total cross-sectional area]) predicted UDR strength modeled by μFE (R(2) = 0.81), and all parameters except total cross-sectional area declined with age. Evaluated cross-sectionally, the 21% fall in predicted bone strength between ages 40-49 years and 80+ years more resembled the change in trabecular volumetric bone mineral density (vBMD) (-15%) than that in cortical area (-41%). In multivariable analyses, measures of body composition and physical activity were stronger predictors of UDR trabecular vBMD, cortical area, total cross-sectional area, and predicted bone strength than were sex steroid levels, but bio-available estradiol and testosterone were correlated with body mass.

CONCLUSIONS

Bone strength at the UDR, as quantified by μFE, can be predicted from variables obtained by HRpQCT. Predicted bone strength declines with age with changes in UDR trabecular vBMD and cortical area, related in turn to reduced skeletal loading and sex steroid levels. The predicted bone strength formula should be validated and tested in fracture risk assessment.

Modulus of elasticity of human periodontal ligament by optical measurement and numerical simulation

OBJECTIVE

To determine the elastic modulus of the periodontal ligament (PDL).

MATERIALS AND METHODS

This study was carried out on eight human maxillary jaw segments containing central incisors. Displacements were measured under load using a laser sensing system, electronic speckle pattern interferometry (ESPI). Subsequently, finite element models presenting the same individual geometry as the respective autopsy material were developed by the software of Mimics and Ansys, based on scanning data from micro computed tomography (micro CT), to simulate tooth mobility numerically under the same force systems as were used in the experiment. Numerical force/deflection curves obtained from the models were fitted to the experimental curves by repeatedly calculating theoretical tooth deflections and varying the elasticity parameters of the human PDL.

RESULTS

A bilinear material parameter set was assumed to simulate tooth deflections. Mean values of E₁  =  0.04 MPa, E₂  =  0.16 MPa, and ultimate strain of ε₁₂  =  7.3% were derived for the elastic behavior of the PDL.

CONCLUSION

Force/deflection curves from the measurements showed a significant nonlinear behavior of elastic stiffness of the PDL. A bilinear material parameter set was suitably assumed to be a description of nonlinear properties of the PDL.

Finding consistent strain distributions in the glenohumeral capsule between two subjects: implications for development of physical examinations

The anterior-inferior glenohumeral capsule is the primary passive stabilizer to the glenohumeral joint during anterior dislocation. Physical examinations following dislocation are crucial for proper diagnosis of capsule pathology; however, they are not standardized for joint position which may lead to misdiagnoses and poor outcomes. To suggest joint positions for physical examinations where the stability provided by the capsule may be consistent among patients, the objective of this study was to evaluate the distribution of maximum principal strain on the anterior-inferior capsule using two validated subject-specific finite element models of the glenohumeral joint at clinically relevant joint positions. The joint positions with 25 N anterior load applied at 60° of glenohumeral abduction and 10°, 20°, 30° and 40° of external rotation resulted in distributions of strain that were similar between shoulders (r² ≥ 0.7). Furthermore, those positions with 20-40° of external rotation resulted in capsule strains on the glenoid side of the anterior band of the inferior glenohumeral ligament that were significantly greater than in all other capsule regions. These findings suggest that anterior stability provided by the anterior-inferior capsule may be consistent among subjects at joint positions with 60° of glenohumeral abduction and a mid-range (20-40°) of external rotation, and that the glenoid side has the greatest contribution to stability at these joint positions. Therefore, it may be possible to establish standard joint positions for physical examinations that clinicians can use to effectively diagnose pathology in the anterior-inferior capsule following dislocation and lead to improved outcomes.