International Journal for Numerical Methods in Biomedical Engineering最新文献

The management of proximal humeral fractures is challenging, and fixation plates often show a high failure rate. However, new fixation plates with variable angle screws could be beneficial. Finite element (FE) studies have shown some benefits of plates with variable angle screws, but not all possible combinations have been explored, and hence worst and optimal scenarios have not been identified. The full exploration of the solution space is not possible using FE techniques due to the computational expense; therefore, a more computationally affordable technique is needed. This study aimed to develop adaptive neural network (ANN) models that can predict the likelihood of a screw collision and the level of strain on the humeral bone when the orientation of the screws is changed. ANN models were trained using input and output data from FE simulations with varying screw angles, developed on a single subject with a two-part fracture in the proximal humerus. Training sets of different sizes were developed to determine the quantity of data required for an accurate model. Firstly, the ANNs were used to make predictions of results from FE unseen data, showing an 84.4% accuracy for the prediction of screw collision and good correlation (R² = 0.99) and low levels of error (RMSE = 0.65%–5.49% strain) for the prediction of bone strain. The ANNs were used to make predictions of a full factorial scenario, showing that the variation of the orientation of the screw in the calcar region has the greatest impact on the bone strain around all screws.

In therapeutic focused ultrasound (FUS), such as thermal ablation and hyperthermia, effective acousto-thermal manipulation requires precise targeting of complex geometries, sound wave propagation through irregular structures, and selective focusing at specific depths. Acoustic holographic lenses (AHLs) provide a distinctive capability to shape acoustic fields into precise, complex, and multifocal FUS-thermal patterns. Acknowledging the under-explored potential of AHLs in shaping ultrasound-induced heating patterns, this study introduces a roadmap for acousto-thermal modeling in the design of AHLs. Three primary modeling approaches are studied and contrasted using four distinct shape groups for the imposed target field. They include pressure-based time reversal (TR) (basic (BSC-TR) and iterative (ITER-TR)), temperature-based (inverse heat transfer optimization (IHTO-TR)), and machine learning (ML)-based (generative adversarial network (GaN) and GaN with feature (Feat-GAN)) methods. Novel metrics, including image quality, thermal efficiency, thermal control, and computational time, are introduced, providing each method's strengths and weaknesses. The importance of evaluating target pattern complexity, thermal and pressure requirements, and computational resources is highlighted. As a further step, two case studies: (1) transcranial FUS and (2) liver hyperthermia, demonstrate the practical use of acoustic holography in therapeutic settings. This paper offers a practical reference for selecting modeling approaches based on therapeutic goals and modeling requirements. Alongside established methods like BSC-TR and ITER-TR, new techniques IHTO-TR, GaN, and Feat-GaN are introduced. BSC-TR serves as a baseline, while ITER-TR enables refinement based on target shape characteristics. IHTO-TR supports thermal control, GaN offers rapid solutions under fixed conditions, and Feat-GaN provides adaptability across varying application settings.

The role of the vasa vasorum in the growth and rupture of intracranial aneurysms, as well as the conditions stimulating its local development along aneurysm walls are not completely clear and have not been studied on an aneurysm-specific basis. In this study, the oxygen distribution throughout the wall of an intracranial aneurysm that underwent substantial thickening and developed an extensive adventitial vasa vasorum network was numerically modeled in order to elucidate the role played by the vasa vasorum. The computational model was constructed based on high-resolution ex vivo micro computed tomography and multi-photon microscopy images of a tissue sample of the aneurysm harvested during open surgery. The mathematical model was based on the transport equation including oxygen diffusion and consumption in the tissue and diffusion across the lumen in the intimal side, and the vasa vasorum in the adventitial side. The governing equation was numerically solved with a finite volume approach on a high-resolution mesh containing approximately 48 million tetrahedra with an element size of 10 μm. The results demonstrate that the observed vasa vasorum plexus provided adequate oxygen supply to the outer layers of the thickened walls. Furthermore, the models show that without the vasa vasorum, due to consumption throughout the wall, the oxygen demand could not be met by diffusion from the luminal surface. These findings support the idea that local hypoxic conditions in regions of increased wall thickness stimulate the development of the vasa vasorum network on the adventitial surface.

Subject-specific finite element models could improve understanding of how spinal loading varies between people, based on differences in morphology and tissue properties. However, determining accurate subject-specific intervertebral disc (IVD) properties can be difficult due to the spine's complex behaviour, in six degrees of freedom. Previous studies optimising IVD properties have utilised axial compression alone or range of motion data in three axes. This study aimed to optimise IVD properties using 6-axis force-moment data, and compare the resultant model's accuracy against a model optimised using IVD pressure data. Additionally, model vertebral alignment was assessed to determine if differences between imaged specimen alignment and in vitro 6-axis test alignment affected the optimisation process. A finite element model of a porcine lumbar motion segment was developed, with generic IVD properties. The model loading and boundary conditions replicated in vitro 6-axis stiffness matrix testing of the same specimen. The model was then optimised twice, once using experimental IVD pressures and once using forces and moments. A second model with geometry based on the specimen's vertebral alignment from the 6-axis testing was also developed and optimised. The 6-axis force-moment optimised model had more accurate overall 6-axis load-displacement behaviour, but less accurate IVD pressures than the pressure optimised model. Neither optimised model fully captured spinal behaviours, due to model and optimisation process limitations. The 6-axis vertebral alignment model had lower error and different optimised IVD properties than the imaged vertebral alignment model. Thus, vertebral alignment affected segment stiffness, so should be considered when developing spine models.

Implantable pulmonary artery pressure sensors (PAPS) might impose a flow-induced risk of thrombus formation in the pulmonary artery (PA). To assess this risk, an in silico study-enhanced animal study with 20 sensors implanted in 10 pigs had previously been conducted. In the in silico study, PAPS were virtually implanted mimicking real implantations, based upon data acquired by CT. This animal in silico study investigated changes in hemodynamics caused by PAPS using image-based computational fluid dynamics (CFD). However, porcine and human PA differ significantly in geometry and hemodynamics. To investigate the transferability of animal in silico study findings toward human conditions, we propose a parallel in silico human study. Based on a similarity analysis (L1 norm for 8 geometric features) human PA geometries with the least difference to 10 porcine PA were selected. PAPS were virtually implanted in human PA as close as possible, mimicking the implantation configuration of the animal study. Finally, a numerical flow analysis of the hemodynamic changes due to PAPS implantation was done. Comparing human and porcine PA, we found significantly larger left and right PA diameters in humans, whereas no differences were found for main PA diameters and bifurcation angle. Comparing hemodynamic boundary conditions, we found a significantly smaller heart rate and a significantly higher peak systolic main PA flow rate in humans, whereas no significant differences for cardiac output were found. The human in silico PAPS study found no relevant changes in hemodynamics increasing the risk of thrombus formation after sensor implantation. This is also valid for PAPS that were non-optimally implanted. Thus, despite differences between species, findings of the in silico animal study were confirmed by the human in silico study.

Currently, it is unclear why some patients experience restenosis after carotid endarterectomy (CEA) and whether the closing procedure is linked to greater rates of restenosis. Here, the morphology and hemodynamics are compared for the carotid bulb of two patients post-CEA. One carotid bulb was closed with a patch which later suffered a restenosis, while the other patient's bulb was treated using primary closure and did not. Contrast-enhanced magnetic resonance angiography (CE-MRA) was segmented to provide the domain for computational fluid dynamics (CFD). Flowrate waveforms measured with phase-contrast MR were provided for the common carotid artery (CCA) and internal carotid artery (ICA), while only the mean flow rate was provided for the external carotid artery (ECA), requiring the ECA waveform to be calculated. A Womersley profile was applied to the CCA inlet and ECA outlet, with a traction-free boundary condition applied to the ICA outlet. The patch patient who restenosed exhibited a nonphysiological hemodynamic environment that differed from the flow environment observed in the healthy, contralateral bulb. In contrast, the hemodynamics of the primary closure patient who underwent a successful CEA showed more favorable levels and trends of WSS as well as healthy mixing from vortices that were both present in the healthy, contralateral bulb. Changing model parameters such as flow rate, wall compliance, and flow waveforms did not alter these conclusions. Therefore, the geometry of the carotid bulb, as opposed to flow characteristics, seems responsible for the observed differences between these two cases in hemodynamic environments and subsequent outcomes.

This paper presents a comprehensive examination of finite element modeling (FEM) approaches for seismocardiography (SCG), a non-invasive method for assessing cardiac function through chest surface vibrations. The paper provides a comparative analysis of existing FEM approaches, exploring the strengths and challenges of various modeling choices in the literature. Additionally, we introduce a sample framework for developing FEM models of SCG, detailing key methodologies from governing equations and meshing techniques to boundary conditions and material property selection. This framework serves as a guide for researchers aiming to create accurate models of SCG signal propagation and offers insights into capturing complex cardiac mechanics and their transmission to the chest surface. By consolidating the current methodologies, this paper aims to establish a reference point for advancing FEM-based SCG modeling, ultimately improving our understanding of SCG waveforms and enhancing their reliability and applicability in cardiovascular health assessment.