International Journal for Numerical Methods in Biomedical Engineering最新文献

This study aimed to explore the variability in nasal airflow patterns among different sexes and populations using computational fluid dynamics (CFD). We focused on evaluating the universality and applicability of dimensionless parameters R (bilateral nasal resistance) and ϕ (nasal flow asymmetry), initially established in a Caucasian Spanish cohort, across a broader spectrum of human populations to assess normal breathing function in healthy airways. In this retrospective study, CT scans from Cambodia (20 males, 20 females), Russia (20 males, 18 females), and Spain (19 males, 19 females) were analyzed. A standardized CFD workflow was implemented to calculate R-ϕ parameters from these scans. Statistical analyses were conducted to assess and compare these parameters across different sexes and populations, emphasizing their distribution and variances. Our results indicated no significant sex-based differences in the R parameter across the populations. However, moderate sexual dimorphism in the ϕ parameter was observed in the Cambodian group. Notably, no geographical differences were found in either R or ϕ parameters, suggesting consistent nasal airflow characteristics across the diverse human groups studied. The study also emphasized the importance of using dimensionless variables to effectively analyze the relationships between form and function in nasal airflow. The observed consistency of R-ϕ parameters across various populations highlights their potential as reliable indicators in both medical practice and further CFD research, particularly in diverse human populations. Our findings suggest the potential applicability of dimensionless CFD parameters in analyzing nasal airflow, highlighting their utility across diverse demographic and geographic contexts. This research advances our understanding of nasal airflow dynamics and underscores the need for additional studies to validate these parameters in broader population cohorts. The approach of employing dimensionless parameters paves the way for future research that eliminates confounding size effects, enabling more accurate comparisons across different populations and sexes. The implications of this study are significant for the advancement of personalized medicine and the development of diagnostic tools that accommodate individual variations in nasal airflow.

Despite being among the most common medical procedures, needle insertions suffer from a high error rate. Impedance measurements using electrode-equipped needles offer promise for improved tissue targeting and reduced errors. Impedance visualization usually requires an extensive pre-measured impedance dataset for tissue differentiation and knowledge of the electric fields contributing to the resulting impedances. This work presents two finite element simulation approaches for both problems. The first approach describes the generation of a multitude of impedances with Monte Carlo simulations for both, homogeneous and inhomogeneous tissue to circumvent the need to rely on previously measured data. These datasets could be used for tissue discrimination. The second method describes the simulation of the spatial sensitivity distribution of an electrode layout. Two singularity analysis methods were employed to determine the bulk of the sensitivity within a finite volume, which in turn enables consistent 3D visualization. The modeled electrode layout consists of 12 electrodes radially placed around a hypodermic needle. Electrical excitation was simulated using two neighboring electrodes for current carriage and voltage pickup, which resulted in 12 distinct bipolar excitation states. Both, the impedance simulations and the respective singularity analysis methods were compared with each other. The results show that the statistical spread of impedances is highly dependent on the tissue type and its inhomogeneities. The bounded bulk of sensitivities of both methods are of similar extent and symmetry. Future models should incorporate more detailed tissue properties such as anisotropy or changing material properties due to tissue deformation to gain more accurate predictions.

As living standards rise, more and more people are paying attention to their own health, especially issues such as cerebral thrombosis, cerebral infarction, and other cerebral blood flow problems. An accurate simulation of blood flow within cerebral vessels has emerged as a crucial area of research. In this study, we focus on microcirculatory blood flow in ischemic brain tissue and employ a 0D-1D geometric multi-scale coupled model to characterize this process. Given the intricate nature of human cerebral vessels, we apply a numerical method combining the finite element method and the third-order Runge–Kutta method to resolve the coupled model. To enhance computational efficiency, we introduce a fast method based on the reduced-order extrapolation algorithm. Our numerical example underscores the stability of the method and convergence accuracy to $��O�\left(�h^3�+�{\tau }^3�\right)�$, while significantly improving the accuracy and efficiency of blood flow simulation, making the mechanism analysis more accurate. Additionally, we present examples detailing variations and distribution of intracranial pressure and blood flow in ischemic brain tissue throughout a cardiac cycle. Both reduced vascular compliance and vascular stenosis can have adverse effects on intracranial cerebral pressure and blood flow, leading to insufficient local oxygen supply and negative effects on brain function. Meanwhile, there will also be corresponding changes in volume flow and pulsatile blood pressure.

Both cell migration and osteogenic differentiation are critical for successful bone regeneration. Therefore, understanding the mechanobiological aspects that govern these two processes is essential in designing effective scaffolds that promote faster bone regeneration. Studying these two factors at different locations is necessary to manage bone regeneration in various sections of a scaffold. Hence, a multiscale computational model was used to observe the mechanical responses of osteoblasts placed in different positions of the trabecular bone and gyroid scaffold. Fluid shear stresses in scaffolds at cell seeded locations (representing osteogenic differentiation) and strain energy densities in cells at cell substrate interface (representing cell migration) were observed as mechanical response parameters in this study. Comparison of these responses, as two critical factors for bone regeneration, between the trabecular bone and gyroid scaffold at different locations, is the overall goal of the study. This study reveals that the gyroid scaffold exhibits higher osteogenic differentiation and cell migration potential compared to the trabecular bone. However, the responses in the gyroid only mimic the trabecular bone in two out of nine positions. These findings can guide us in predicting the ideal cell seeded sites within a scaffold for better bone regeneration and in replicating a replaced bone condition by altering the physical parameters of a scaffold.

Atrial fibrillation (AF) poses a significant risk of stroke due to thrombus formation, which primarily occurs in the left atrial appendage (LAA). Medical image-based computational fluid dynamics (CFD) simulations can provide valuable insight into patient-specific hemodynamics and could potentially enhance personalized assessment of thrombus risk. However, the importance of accurately representing the left atrial (LA) wall dynamics has not been fully resolved. In this study, we compared four modeling scenarios; rigid walls, a generic wall motion based on a reference motion, a semi-generic wall motion based on patient-specific motion, and patient-specific wall motion based on medical images. We considered a LA geometry acquired from 4D computed tomography during AF, systematically performed convergence tests to assess the numerical accuracy of our solution strategy, and quantified the differences between the four approaches. The results revealed that wall motion had no discernible impact on LA cavity hemodynamics, nor on the markers that indicate thrombus formation. However, the flow patterns within the LAA deviated significantly in the rigid model, indicating that the assumption of rigid walls may lead to errors in the estimated risk factors. In contrast, the generic, semi-generic, and patient-specific cases were qualitatively similar. The results highlight the crucial role of wall motion on hemodynamics and predictors of thrombus formation, and also demonstrate the potential of using a generic motion model as a surrogate for the more complex patient-specific motion. While the present study considered a single case, the employed CFD framework is entirely open-source and designed for adaptability, allowing for integration of additional models and generic motions.

A prosthetic knee is designed to replace the functionality of an anatomical knee in transfemoral amputees. The purpose of a prosthetic knee is to restore mobility and compensate amputees for their impairment. In the present research numerical modelling and simulation of a carbon fabric reinforced polymer made polycentric prosthetic knee with four-bar mechanism was performed. Virtual prototyping with computer-aided design and computer-aided engineering software ensured geometric and structural stability of the knee design. The linkage mechanism, instantaneous centre's location and trajectory were investigated using multibody dynamics and analytical formulations. Computational simulations with a non-linear finite element model were employed with joints, contact formulations and an orthotropic material model to predict the displacement, stress formulated and life of the knee prosthesis under static and cyclic loading conditions. Finite element analysis assessed the strength and durability of knee in accordance to standards. Maximum Principal stress of 155 MPa and life expectancy of 3.1 × 10⁶ cycles were determined for the composite knee through numerical simulations ensuring a safe design. Experimental testing was also conducted as per standards and the percentage error was estimated to be 2.52%, thereby establishing the validity of the finite element model deployed. This type of simulation-based approach can be implemented to efficiently and affordably design and prototype a prosthetic knee with desired functioning criteria.

Finite Element modeling has been an extended methodology to build numerical model to simulate the behavior of the hearing system. Due to the complexity of the system and the difficulties to reduce the uncertainties of the geometric data, they result in computationally expensive models, sometimes generic, representative of average geometries. It makes it difficult to validate the model with direct experimental data from the same specimen or to establish a patient-oriented modeling strategy. In the present paper, a first attempt to automatize the process of model building is made. The source information is geometrical information obtained from CT of the different elements that compose the system. Importing that data, we have designed the complete procedure to build a model including tympanic membrane, ossicular chain and cavities. The methodology includes the proper coupling of all the elements and the generation of the corresponding finite element model. The whole automatic procedure is not complete, as we need to make some human-assisted decisions; however, the model development time is reduced from 4 weeks to approximately 3 days. The goal of the modeling algorithm is to build a Finite Element Model with a limited computational cost. Several tasks as contour identification or model decimation are designed and integrated in order to follow a semi-automated process that allows generating a patient-oriented model.

We examined the effect of minimal lumen segmentation uncertainty on Fractional Flow Reserve obtained from Coronary Computed Tomography Angiography $��\left({\mathrm{FFR}}_{\mathrm{CT}}\right)�$. A total of 14 patient-specific coronary models with different stenosis locations and degrees of severity were enrolled in this study. The optimal segmented coronary lumens were disturbed using intra $��\left(�\pm �6�\%�\right)�$ and inter-operator $��\left(�\pm �15�\%�\right)�$ variations on the segmentation threshold. $��{\mathrm{FFR}}_{\mathrm{CT}}�$ was evaluated in each case by 3D-OD CFD simulations. The findings suggest that the sensitivity of $��{\mathrm{FFR}}_{\mathrm{CT}}�$ to this type of uncertainty increases distally and with the stenosis severity. Cases with moderate or severe distal coronary lesions should undergo either exact and thorough segmentation operations or invasive FFR measurements, particularly if the $��{\mathrm{FFR}}_{\mathrm{CT}}�$ is close to the cutoff (0.80). Therefore, we conclude that it is crucial to consider the lesion's location and degree of severity when evaluating $��{\mathrm{FFR}}_{\mathrm{CT}}�$ results.

In microwave imaging, the adjoint method is widely used for the efficient calculation of the update direction, which is then used to update the unknown model parameter. However, the utilization and the formulation of the adjoint method differ significantly depending on the imaging scenario and the applied optimization algorithm. Because of the problem-specific nature of the adjoint formulations, the dissimilarities between the adjoint calculations may be overlooked. Here, we have classified the adjoint method formulations into two groups: the direct and indirect methods. The direct method involves calculating the derivative of the cost function, whereas, in the indirect method, the derivative of the predicted data is calculated. In this review, the direct and indirect adjoint methods are presented, compared, and discussed. The formulations are explicitly derived using the two-dimensional wave equation in frequency and time domains. Finite-difference time-domain simulations are conducted to show the different uses of the adjoint methods for both single source-multiple receiver, and multiple transceiver scenarios. This study demonstrated that an appropriate adjoint method selection is significant to achieve improved computational efficiency for the applied optimization algorithm.