International Journal for Numerical Methods in Biomedical Engineering最新文献

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.

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.

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 mm³ vs. normal 25.80 ± 18.94 mm³ [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.

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.

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 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.

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.

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 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 $0.7P_0$ , 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 ${10}^{-7}{m}^2{s}^{-1}$ 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.

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.