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This study presents a novel statistical volume element (SVE) for micromechanical modeling of the white matter structures, with histology-informed randomized distribution of axonal tracts within the extracellular matrix. The model was constructed based on the probability distribution functions obtained from the results of diffusion tensor imaging as well as the histological observations of scanning electron micrograph, at two structures of white matter susceptible to traumatic brain injury, i.e. corpus callosum and corona radiata. A simplistic representative volume element (RVE) with symmetrical arrangement of fully alligned axonal fibers was also created as a reference for comparison. A parametric study was conducted to find the optimum grid and edge size which ensured the periodicity and ergodicity of the SVE and RVE models. A multi-objective evolutionary optimization procedure was used to find the hyperelastic and viscoelastic material constants of the constituents, based on the experimentally reported responses of corpus callosum to axonal and transverse loadings. The optimal material properties were then used to predict the homogenized and localized responses of corpus callosum and corona radiata. The results indicated similar homogenized responses of the SVE and RVE under quasi-static extension, which were in good agreement with the experimental data. Under shear strain, however, the models exhibited different behaviors, with the SVE model showing much closer response to the experimental observations. Moreover, the SVE model displayed a significantly better agreement with the reports of the experiments at high strain rates. The results suggest that the randomized fiber architecture has a great influence on the validity of the micromechanical models of white matter, with a distinguished impact on the model's response to shear deformation and high strain rates. Moreover, it can provide a more detailed presentation of the localized responses of the tissue substructures, including the stress concentrations around the low caliber axonal tracts, which is critical for studying the axonal injury mechanisms.

During pregnancy, traumas can threaten maternal and fetal health. Various trauma effects on a pregnant uterus are little investigated. In the present study, a finite element model of a uterus along with a fetus, placenta, amniotic fluid, and two most effective ligament sets is developed. This model allows numerical evaluation of various loading on a pregnant uterus. The model geometry is developed based on CT-scan data and validated using anthropometric data. Applying Ogden hyper-elastic theory, material properties of uterine wall and placenta are developed. After simulating the "rigid-bar" abdominal loading, the impact force and abdominal penetration are investigated. Findings are compared with the experimental abdominal response corridor, previously developed for a nonpregnant abdomen. "Response corridor" denotes a bounded envelope in response space, within which the system responses usually lie. Results show that at low abdominal penetrations (less than 45 mm), the pregnant abdomen response is highly compatible with the nonpregnant case. While, at large penetrations, the pregnant abdomen demonstrates stiffer behavior. The reason must be the existence of a fetus in the model. This reveals that the existing response corridors would not be reliable to be extended for a pregnant abdomen. Hence, response corridor development for a pregnant abdomen is a crucial task. In this study, a new fixed-back rigid-bar loading response corridor is proposed for a pregnant abdomen using the load-penetration behavior of the developed model. This model and response corridor can help to study the pregnant uterus response to environmental loading and investigate the injury risk to the uterus and fetus., (© 2019 John Wiley & Sons, Ltd.)

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

In this paper, a micromechanical model for connective soft tissues based on the available histological evidences is developed. The proposed model constituents i.e. collagen fibers and ground matrix are considered as hyperelastic materials. The matrix material is assumed to be isotropic Neo-Hookean while the collagen fibers are considered to be transversely isotropic hyperelastic. In order to take into account the effects of tissue structure in lower scales on the macroscopic behavior of tissue, a strain energy density function (SEDF) is developed for collagen fibers based on tissue hierarchical structure. Macroscopic response and properties of tissue are obtained using the numerical homogenization method with the help of ABAQUS software. The periodic boundary conditions and the proposed constitutive models are implemented into ABAQUS using the DISP and the UMAT subroutines, respectively. The existence of the solution and stable material behavior of proposed constitutive model for collagen fibers are investigated based on the poly-convexity condition. Results of the presented micromechanics model for connective tissues are compared and validated with available experimental data. Effects of geometrical and material parameters variation at microscale on macroscopic mechanical behavior of tissues are investigated. The results show that decrease in collagen content of the connective tissues like the tendon due to diseases leads 20% more stretch than healthy tissue under the same load which can results in connective tissue malfunction and hypermobility in joints., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Paramecium or other ciliates have the potential to be utilized for minimally invasive surgery systems, making internal body organs accessible. Paramecium shows interesting responses to changes in the concentration of specific ions such as K(+), Mg(2+), and Ca(2+) in the ambient fluid. Some specific responses are observed as, changes in beat pattern of cilia and swimming toward or apart from the ion source. Therefore developing a model for chemotactic motility of small organisms is necessary in order to control the directional movements of these microorganisms before testing them. In this article, we have developed a numerical model, investigating the effects of Ca(2+) on swimming trajectory of Paramecium. Results for Ca(2+)-dependent chemotactic motility show that calcium gradients are efficient actuators for controlling the Paramecium swimming trajectory. After applying a very low Ca(2+) gradient, a directional chemotaxis of swimming Paramecium is observable in this model. As a result, chemotaxis is shown to be an efficient method for controlling the propulsion of these small organisms.

Needle insertion simulation and planning systems (SPSs) will play an important role in diminishing inappropriate insertions into soft tissues and resultant complications. Difficulties in SPS development are due in large part to the computational requirements of the extensive calculations in finite element (FE) models of tissue. For clinical feasibility, the computational speed of SPSs must be improved. At the same time, a realistic model of tissue properties that reflects large and velocity-dependent deformations must be employed. The purpose of this study is to address the aforementioned difficulties by presenting a cost-effective SPS platform for needle insertions into the liver. The study was constrained to planar (2D) cases, but can be extended to 3D insertions. To accommodate large and velocity-dependent deformations, a hyperviscoelastic model was devised to produce an FE model of liver tissue. Material constants were identified by a genetic algorithm applied to the experimental results of unconfined compressions of bovine liver. The approach for SPS involves B-spline interpolations of sample data generated from the FE model of liver. Two interpolation-based models are introduced to approximate puncture times and to approximate the coordinates of FE model nodes interacting with the needle tip as a function of the needle initiation pose; the latter was also a function of postpuncture time. A real-time simulation framework is provided, and its computational benefit is highlighted by comparing its performance with the FE method. A planning algorithm for optimal needle initiation was designed, and its effectiveness was evaluated by analyzing its accuracy in reaching a random set of targets at different resolutions of sampled data using the FE model. The proposed simulation framework can easily surpass haptic rates (>500 Hz), even with a high pose resolution level ( approximately 30). The computational time required to update the coordinates of the node at the needle tip in the provided example was reduced from 177 s to 0.8069 ms. The planning accuracy was acceptable even with moderate resolution levels: root-mean-square and maximum errors were 1 mm and 1.2 mm, respectively, for a pose and PPT resolution levels of 17 and 20, respectively. The proposed interpolation-based models significantly improve the computational speed of needle insertion simulation and planning, based on the discretized (FE) model of the liver and can be utilized to establish a cost-effective planning platform. This modeling approach can also be extended for use in other surgical simulations.