Endovascular coil embolization is the primary therapeutic modality for intracranial aneurysms. Substantial reports have been found regarding the coil packing density and inflow jet. However, the hemodynamic effect of increasing the rate of tamponade in the inflow jet area within the aneurysm remains unclear. In this study, individualized geometries of six intracranial aneurysms were recruited: all six aneurysms were located in the internal carotid artery. Two groups were created by changing the position and orientation of the microcatheter for the release of the third segment of the filling coil. The finite element method was used to simulate coil deployment. Computational fluid dynamics was used to characterize hemodynamics in post-deployment aneurysms. The parameters evaluated included velocity reduction, wall shear stress (WSS), low WSS (LWSS), relative residence time (RRT), flow kinetic energy in the neck region of the aneurysms, and residual flow volume (RFV) in the aneurysms. At the peak time (t = 0.17 s), the targeted deployment group has similar proportion of LWSS area to conventional deployment groups: targeted 78.13% ± 34.59% versus normal 74.20% ± 36.94% (mean ± SD, p = 0.583). The targeted deployment group has a higher RRT area (targeted 16.84% ± 5.58% vs. normal 6.42% ± 5.67% [mean ± SD, p = 0.009]), smaller flow kinetic energy (targeted 9.43 ± 4.33 vs. normal 16.23 ± 5.92 [mean ± SD, p = 0.047]), and a larger RFV in the aneurysms (targeted 35.97 ± 24.35 mm vs. normal 25.80 ± 18.94 mm [mean ± SD, p = 0.44]). Inflow jets play an important role in the treatment of aneurysms, and deploying filling coils in accordance with inflow jets may result in a better hemodynamic environment.

In this study, 18 rib cages (8 males and 10 females) were segmented from computer tomography (CT) images. In order to analyze the potential differences in thoracic biomechanics during cardiopulmonary resuscitation (CPR), a set of numerical experiments was conducted using finite elements (FE). Compression forces were applied at different points on the rib cage. Results indicated that the optimal compression area for both sexes is the sternum at the 5th rib level, requiring the least force to achieve the desired compression depth. Males required greater force than females. Among females, those with lower width/depth ratios (more rounded thoracic shape) required less force compared to those with higher ratios (more oval-shaped thorax).

This study presents an investigation of an innovative microfluidic flow separator using both numerical and experimental approaches to calibrate contrast-enhanced ultrasound scanners. Numerical simulations were conducted using Lagrangian particles tracking and passive scalar transport methodologies using the OpenFOAM software. The experimental validation confirmed the accuracy of the numerical simulations, particularly at an imposed total pressure of , showing an excellent agreement in particle distributions. The study emphasizes the computational efficiency and modeling of passive scalar transport, providing valuable understanding into the behavior of scalar quantities in microfluidic systems. An optimized diffusion coefficient value of was identified, showing its critical role in achieving accurate simulation results and optimizing the performance of microfluidic flow separators for contrast-enhanced ultrasound scanner calibration.

Reported in this paper is a cutting-edge computational investigation into the influence of geometric characteristics on abdominal aortic aneurysm (AAA) rupture risk, beyond the traditional measure of maximum aneurysm diameter. A Comprehensive fluid-structure interaction (FSI) analysis was employed to assess risk factors in a range of patient scenarios, with the use of three-dimensional (3D) AAA models reconstructed from patient-specific aortic data and finite element method. Wall shear stress (WSS), and its derivatives such as time-averaged WSS (TAWSS), oscillatory shear index (OSI), relative residence time (RRT) and transverse WSS (transWSS) offer insights into the force dynamics acting on the AAA wall. Emphasis is placed on these WSS-based metrics and seven key geometric indices. By correlating these geometric discrepancies with biomechanical phenomena, this study highlights the novel and profound impact of geometry on risk prediction. This study demonstrates the necessity of a multidimensional assessment approach, future efforts should complement these findings with experimental validations for an applicable approach for clinical use.

The blast shock waves generated by the explosion are severe threat to soldiers on the battlefield, while the helmets currently equipped for the soldiers cannot offer sufficient blast protection. Some helmet pads have been developed to improve the protection performance of the combat helmets against shock waves. However, it remains unclear how to design the helmet pads to protect the head more effectively against blast shock waves. This study aims to design a new mechanics-guided helmet pad and evaluate its protection performance by numerical simulations. The design of the new helmet pad is guided by the oblique reflection theory (ORT), and the advanced combat helmet (ACH) pad is applied for comparison. The protection performance of the pads against blast waves from two directions (frontal and lateral) was investigated. The differences in the distributions of overpressure inside the helmet using two types of pads were analyzed, and the intracranial pressure (ICP) of head was compared. The ORT-guided pads can reduce the overpressure inside the helmet, minimizing the possibility of blast-induced traumatic brain injury. Furthermore, the underwash phenomenon can also be controlled when the new pads are applied. The results in this study provide an important theoretical basis and some guidelines on the design of helmet pads for the protection of human brain from blast shock waves.

Precision in force simulationis critical for forecasting tooth movement and optimizing orthodontic treatment strategies. While traditional techniques have provided valuable insights, there remains a need for improved methodologies that can seamlessly integrate with fixed orthodontic practices. This study aims to refine orthodontic force simulation techniques by integrating a nodal displacement approach within finite element analysis, specifically designed to enhance prediction accuracy in tooth movement and optimize orthodontic treatment planning. Three-dimensional patient-specific models of the Tooth, Periodontal Ligament, and Bone Complex (TPBC) of five volunteers were created, along with models of brackets and wires. The simulation involved an initial step of estimating node displacements to align the archwire with the brackets, followed by a subsequent step to attain the required tooth movement and determine the orthodontic force. Experimental validation of the simulation results was performed using an orthodontic force tester (OFT). Utilizing the nodal displacement approach, the simulation successfully positioned the archwire onto the brackets. When benchmarked against the OFT, 80% of the simulated force directions exhibited angular discrepancies of less than 5°. Additionally, the absolute differences in force magnitude reached 20.06 cN, and in moments, up to 71.76 cN mm. The relative differences were as high as 9.55% for force and 13.83% for moments. These findings represent an improvement of up to 10.45% in force accuracy and 8.87% in moment accuracy compared to median values reported in most recent literature. In this research, a nodal displacement methodology was employed to simulate orthodontic forces with precision across the dental arch. The results demonstrate the approache's potential to enhance the accuracy of force prediction in orthodontic treatment planning, thereby advancing our understanding of orthodontic biomechanics.

The mechanisms leading to aneurysm occlusion after treatment with flow-diverting devices are not fully understood. Flow modification induces thrombus formation within the aneurysm cavity, but fibrin can simultaneously accumulate and cover the device scaffold, leading to further flow modification. However, the interplay and relative importance of these processes are not clearly understood. A computational model of fibrin accumulation and flow modification after flow diversion treatment of cerebral aneurysms has been developed under the guidance of in vitro experiments and observations. The model is based on the loose coupling of flow and transport-reaction equations that are solved separately by independent codes. Interaction or reactive terms account for thrombin production from prothrombin stimulated by thrombogenic metallic wires and inhibition by antithrombin as well as fibrin production from fibrinogen stimulated by thrombin and flow shear stress, and fibrin adhesion to device wires and already attached fibrin. The computational model was demonstrated and tested on idealized vessel and aneurysm geometries. The model was able to reproduce the salient features of fibrin accumulation after the deployment of flow-diverting devices in idealized in vitro models of cerebral aneurysms. Namely, fibrin production in regions of high shear stress, initial accumulation at the inflow zone, and progressive occlusion of the device and corresponding flow attenuation. The computational model linking flow dynamics to fibrin production, transport, and adhesion can be used to investigate and better understand the effects that lead to fibrin accumulation and the resulting aneurysm inflow reduction and intra-aneurysmal flow modulation.

In the last decades, many computational models have been developed to predict soft tissue growth and remodeling (G&R). The constrained mixture theory describes fundamental mechanobiological processes in soft tissue G&R and has been widely adopted in cardiovascular models of G&R. However, even after two decades of work, large organ-scale models are rare, mainly due to high computational costs (model evaluation and memory consumption), especially in long-range simulations. We propose two strategies to adaptively integrate history variables in constrained mixture models to enable large organ-scale simulations of G&R. Both strategies exploit that the influence of deposited tissue on the current mixture decreases over time through degradation. One strategy is independent of external loading, allowing the estimation of the computational resources ahead of the simulation. The other adapts the history snapshots based on the local mechanobiological environment so that the additional integration errors can be controlled and kept negligibly small, even in G&R scenarios with severe perturbations. We analyze the adaptively integrated constrained mixture model on a tissue patch for a parameter study and show the performance under different G&R scenarios. To confirm that adaptive strategies enable large organ-scale examples, we show simulations of different hypertension conditions with a real-world example of a biventricular heart discretized with a finite element mesh. In our example, adaptive integrations sped up simulations by a factor of three and reduced memory requirements to one-sixth. The reduction of the computational costs gets even more pronounced for simulations over longer periods. Adaptive integration of the history variables allows studying more finely resolved models and longer G&R periods while computational costs are drastically reduced and largely constant in time.

This study introduces an innovative real-time surgical planning platform optimized for the treatment of arterial aneurysms using intrasaccular flow disruption (IFD) devices. This platform incorporates a cutting-edge fast virtual deployment (FVD) algorithm alongside a discrete element method (DEM) for computational fluid dynamics (CFD) analyses. It facilitates the efficient virtual deployment of IFD devices, minimizing computational overhead while allowing for comprehensive postoperative hemodynamic efficacy assessment. The FVD algorithm employs an adaptive wall adherence and curvature control system, validated through both idealized and patient-specific model simulations. Post-treatment hemodynamic shifts are quantified by discretizing device wire filaments into discrete particles, which are then integrated with blood flow simulations for enhanced realism. The FVD algorithm efficiently executes virtual deployment of IFD devices within seconds, producing DEM-CFD computational models that align closely with bench testing, traditional Finite Element Method (FEM) analyses, and angiographic data. DEM-CFD outcomes link occlusion effectiveness to post-implantation hemodynamic characteristics, influenced by the aneurysm's unique anatomical features and clinical intervention strategies. The proposed platform demonstrates substantial improvement in balancing computational efficiency with analytical precision. It provides a viable and innovative framework for real-time surgical planning, presenting significant implications for clinical application in arterial aneurysm management.

We develop a cluster-based model order reduction (called C-pRBMOR) approach for efficient homogenization of bones, compatible with a large variety of generalized standard material (GSM) models. To this end, the pRBMOR approach based on a mixed incremental potential formulation is extended to a clustered version for a significantly improved computational efficiency. The microscopic modeling of bones falls into a mixed incremental class of the GSM framework, originating from two potentials. An offline phase of the C-pRBMOR approach includes both a clustering analysis spatially decomposing the micro-domain within an RVE and a space-time decomposition of the microscopic plastic strain fields. A comparative study on two different clustering approaches and two algorithms for mode identification is additionally conducted. For an online analysis, a cluster-enhanced version of evolution equations for the reduced variables is derived from an effective incremental variational formulation, rendering a very small set of nonlinear equations to be numerically solved. Several numerical examples show the effectiveness of the C-pRBMOR approach. A striking acceleration rate beyond 10 against conventional FE computations and that beyond 10 against the original pRBMOR approach are observed.

Healing of tibia demonstrates a complex mechanobiological process as it is stimulated by the major factor of strains applied by body weight. The effect of screw heads and bodies as well as their pressure distribution is often overlooked. Hence, effective mechanical conditions of the healing process of tibia can be categorized into the material of the plate and screws, post-operation loadings, and screw type and pressure. In this paper, a mathematical biodegradation model was used to simulate the PGF/PLA plate-screw device over 8 weeks. The effect of different post-operation loading patterns was studied for both locking and non-locking screws. The aim was to reach the best configuration for the most achievable healing using FEA by computing the healing pattern, trend, and efficiency with the mechano-regulation theory based on deviatoric strain. The biodegradation process of the plate and screws resulted in 82% molecular weight loss and 1.05 GPa decrease in Young's modulus during 8 weeks. The healing efficiency of the cases ranged from 4.72% to 14.75% in the first week and 18.64% to 63.05% in the eighth week. Finally, an optimal case was achieved by considering the prevention of muscle erosion, bone density reduction, and nonunion, according to the obtained results.

This study investigates the pulse compression technique to improve the performance of magneto-acousto-electrical tomography (MAET) with magnetic field measurements through numerical studies. Emphasizing the effects of specific coil configuration on MAET measurements, the study conducts evaluations using a linear phased array (LPA) transducer and numerical breast models with tumor inclusion. It provides feasibility and a detailed comparative analysis of various excitations, including linear frequency modulated (LFM), Barker code, and Golay code excitations in MAET. To simulate experimental conditions, additive White Gaussian noise is added to the MAET signal detected by the receiver coils. The results obtained from the LPA steering angle at 0° and the reconstructed B-mode MAET images using the pulse compression technique lead to improvements compared with conventional single-cycle excitation. The computed mean signal-to-noise ratio (SNR) improvements for LFM, Barker code, and Golay code excitations in B-mode MAET images for 10,000 iterations are 7.42, 8.36, and 8.44 dB, respectively, compared with single-cycle excitation. Similarly, the mean contrast-to-noise ratio (CNR) improvements for these excitations in B-mode MAET images are 1.43, 1.63, and 1.9 dB, respectively. The results demonstrate that Golay code is superior in CNR and image quality metrics, while Golay and Barker codes have comparable SNR and outperform LFM. The research shows that the coil configuration significantly impacts tumor detection. With Golay code excitation, detecting a tumor as small as 5 mm × 2 mm at a depth of 33 mm with an SNR of 6.38 dB is possible, achieving an axial resolution of 2 mm.

Movement patterns may be a factor for manipulating the lumbar load, although little information is yet available in the literature about the relationship between this variable and intervertebral disc pressure (IDP). A finite element model of the lumbar spine (49-year-old asymptomatic female) was used to simulate intervertebral movements (L2-L5) of 127 asymptomatic participants. The data from participants that at least completed a simulation of lumbar vertebral movement during the first 53% of a movement cycle (flexion phase) were used for further analyses. Then, for each vertebral angular motion curve with constant spatial peaks, different temporal patterns were simulated in two stages: (1) in lumbar pattern exchange (LPE), each vertebral angle was simulated by the corresponding vertebrae of other participants data; (2) in vertebral pattern exchange (VPE), vertebral angles were simulated by each other. The k-mean algorithm was used to cluster two groups of variables; peak and cumulative IDP, in both stages of simulations (i.e., LPE and VPE). In the second stage of the simulation (VPE), Kendall's tau was utilized to consider the relationship between different temporal patterns and IDPs for each individual lumbar level. Cluster analyses showed that the temporal movement pattern did not exhibit any effect on the peak IDP while the cumulative IDP changed significantly for some patterns. Earlier involvement in lumbar motion at any level led to higher IDP in the majority of simulations. There is therefore a possibility of manipulating lumbar IDP by changing the temporal pattern with the same ROM, in which optimal distribution of the loads among lumbar levels may be applied as preventive or treatment interventions. Evaluating load benefits, such as load, on biomechanically relevant lumbar levels, dynamically measured by quantitative fluoroscopy, may help inform interventional exercises.

Doppler ultrasound is a commonly used method to assess hemodynamics of the fetal cardiovascular system and to monitor the well-being of the fetus. Indices based on the velocity profile are often used for diagnosis. However, precisely linking these indices to specific underlying physiology factors is challenging. Several influences, including wave reflections, fetal growth, vessel stiffness, and resistance distal to the vessel, contribute to these indices. Understanding these data is essential for making informed clinical decisions. Mathematical models can be used to investigate the relation between velocity profiles and physiological properties. This study presents a mathematical model designed to simulate velocity wave propagation throughout the fetal cardiovascular system, facilitating the assessment of factors influencing velocity-based indices. The model combines a one-fiber model of the heart with a 1D wave propagation model describing the larger vessels of the circulatory system and a lumped parameter model for the microcirculation. Fetal growth from 20 to 40 weeks of gestational age is incorporated by adjusting cardiac and circulatory parameter settings according to scaling laws. The model's results, including cardiac function, cardiac output distribution, and volume distribution, show a good agreement with literature studies for a growing healthy fetus from 20 to 40 weeks. In addition, Doppler indices are simulated in various vessels and agree with literature as well. In conclusion, this study introduces a novel closed-loop 0D-1D mathematical model that has been verified against literature studies. This model offers a valuable platform for analyzing factors influencing velocity-based indices in the fetal cardiovascular system.

Estimation of the knee joint strength by maximum voluntary isometric contraction (MVIC) is a common practice to assess strength, coordination, safety to return to work or engage in sports after an injury, and to evaluate the efficacy of treatment modalities and rehabilitation strategies. In this study, we utilize a previously validated coupled finite element-musculoskeletal model of the lower extremity to explore the sensitivity of output measures (posterior cruciate ligament [PCL]/muscle/contact forces and passive moments) in knee MVIC flexion exercises at seated position. To do so, at three knee flexion angles (KFA), input measures (resistance moment and contribution moments of quadriceps and gastrocnemii) were varied at four levels each using the Taguchi design of experiment. Our findings reveal significant increases in PCL forces with KFA (p < 0.01), net MVIC moment (p < 0.01), and resistance moment of quadriceps (p < 0.01). In contrast, they drop at larger activity in gastrocnemii (p < 0.01). Tibiofemoral (TF) contact forces increase with the net MVIC moment (p < 0.01). The passive knee flexion moment, while highly dependent on the location at which computed, also increases with the net MVIC moment (p < 0.01). Changes in KFA, MVIC moment, and proportions thereof carried by quadriceps and/or gastrocnemii substantially affect biomechanics of the joint. Compared with level walking and stair ascent, slightly larger contact forces/stresses and much greater PCL forces are computed. This study improves our understanding of the knee joint behavior during MVIC in effective evaluation and rehabilitation interventions. Besides, it emphasizes the importance of positioning the joint center in model studies.

Mastication is an essential and preliminary step of the digestion process involving fragmentation and mixing of food. Controlled muscle movement of jaws with teeth executes crushing, leading towards fragmentation of food particles. Understanding various parameters involved with the process is essential to solve any biomedical complication in the area of interest. However, exploring and analyzing such process flow through an experimental route is challenging and inefficient. Computational techniques such as discrete element numerical modeling can effectively address such problems. The current work employs the Discrete Element Method (DEM) as a numerical modeling technique to simulate the human mastication process. Tavares and Ab-T10 breakage models coupled with Gaudin Schumann and Incomplete Beta fragment distribution models have been implemented to analyze the fragmental distribution of food particles. The effect of particle shape (spherical, polyhedron, and faceted cylinder), size (aspect ratio), and orientation (vertical and horizontal) on breakage and fragment distribution is analyzed. To account for the elastic-plastic behavior and moisture content in food particles, modifications has been made in breakage models by incorporating numerical softening factor and adhesion force. The study demonstrates how numerical modeling techniques can be utilized to analyze the mastication process involving multiple process parameters.

This paper introduces a novel computational framework for evaluating above-knee prostheses, addressing a major challenge in gait deviation studies: distinguishing between prosthesis-specific and patient-specific contributions to gait deviations. This innovative approach utilizes three separate computational models to quantify the changes in gait dynamics necessary to achieve a set of ideal gait kinematics across different prosthesis designs. The pilot study presented here employs a simple two-dimensional swing-phase model to conceptually demonstrate how the outcomes of this three-model framework can assess the extent to which prosthesis design impacts a user's ability to replicate the dynamics of able-bodied gait. Furthermore, this framework offers potential for optimizing passive prosthetic devices for individual patients, thereby reducing the need for real-life experiments, clinic visits, and overcoming rehabilitation challenges.

This study aimed to ascertain the relevance of intervertebral discs (IVD) in the stress distribution on growthplates (GPs) of a trunk model with adolescent idiopathic scoliosis (AIS) following a unilateral weakening of muscles. A thoracolumbar spine finite element (FE) model of a young female healthy and an AIS spine comprising GPs linked to the T12 through sacrum vertebrae. Two scenarios of including (FEI) and excluding (FEE) IVDs were considered. Then, using optimization-driven musculoskeletal models of the AIS and healthy trunks, the FE models were examined under subject-specific muscle forces and gravity loads. Results of this study demonstrate that when IVDs included in the FE model, an increase, ranging from 0.2 to 1.7 MPa, with the highest value occurring at the apex of the AIS model, in the von Mises stresses in the GPs. The ratio of 1.5 was found for the maximum von-Mises stress value on the most tilted GP in the FEI over the FEE model. Unilateral paralysis of muscles caused a reduction of 50% and 63% in the von Mises stress ratio of the concave-over-convex side of the most tilted GP in the FEI and FEE models of the AIS spine with healthy muscles, respectively. The intradiscal pressures, found for FEE and FEI models, assented to recent in-vivo investigations. Nonetheless, employing IVDs in the simulations provides an indispensable tool to anticipate the effects of neuromuscular disorders on GP stresses in an AIS spine and predict deformity progression during growth.

Blasts are a threat both in military and civil contexts due not only to explosive devices but also to gas leakages or other accidents. Numerical models could aid to plan response strategies in the short and long term. Nevertheless, due to modeling complexities, a standardized computational framework has not been established yet. In this challenging context, the present study assesses the prediction of blast-induced traumas by using the total human model for safety (THUMS) human model, which has never been attempted before to the authors knowledge. The pedestrian model is publicly available, hence the demonstration of its suitability to predict blast injuries could benefit the establishment of a common modeling framework. Therefore, the THUMS human model was exposed to different blast scenarios both in free field and partially confined spaces and the response of vital organs was investigated. Trauma patterns to internal organs of the THUMS were consistent with available experimental data and injury thresholds. In conclusion, THUMS open-source human model demonstrated its validity to reproduce primary blast-related injuries, addressing the development of standardization of numerical simulations of human response to explosions.

Deep lung delivery is crucial for respiratory disease treatment. Although nano and submicron particles exhibited a good deposition efficiency in deep regions of the lung, powder nonuniformity and particle agglomeration reduce their efficiency. Inhalation of porous particles (PPs) can overcome the mentioned challenges due to their larger size and low-density. The present study numerically investigates the deposition and penetration efficiency of orally inhaled PPs. A revised drag coefficient was implemented for PP transport. A realistic mouth-throat to the fifth generation of the lung was reconstructed from CT-scan images. A dilute suspension of uniformly distributed particles was considered at three inhalation flow rates (15, 30, and 45 L/min). Governing equations of the flow field and particle transport are solved using an Eulerian-Lagrangian approach. The results demonstrate that inhaling PPs significantly reduces the total and regional deposition of particles. There was also a critical porosity value under moderate and high inhalation flow rates for large PPs. Below this critical value, PP deposition efficiency substantially decreases. Additionally, it was also found that under low inhalation flow rates, the impact of porosity value is negligible. Almost 95% of the PPs penetrate the lower branches. These findings provide particle engineers and pharmaceutics with profound insight into developing novel inhalation techniques and drug delivery methods for deep lung delivery.

Experimental studies on the cellular uptake of nanoparticles (NPs), useful for the investigation of NP-based drug delivery systems, are often difficult to interpret due to the large number of parameters that can contribute to the phenomenon. It is therefore of great interest to identify insignificant parameters to reduce the number of variables used for the design of experiments. In this work, a model of the wrapping of elliptical NPs by the cell membrane is used to compare the influence of the aspect ratio of the NP, the membrane tension, the NP-membrane adhesion, and its variation during the interaction with the NP on the equilibrium state of the wrapping process. Several surrogate models, such as Kriging, Polynomial Chaos Expansion (PCE), and artificial neural networks (ANN) have been built and compared to emulate the computationally expensive model. Only the ANN-based model outperformed the other approaches by providing much better predictivity metrics and could therefore be used to compute the sensitivity indices. Our results showed that the NP's aspect ratio, the initial NP-membrane adhesion, the membrane tension, and the delay for the increase of the NP-membrane adhesion after receptor dynamics are the main contributors to the cellular internalization of the NP, while the influence of other parameters is negligible.