International Journal for Numerical Methods in Biomedical Engineering最新文献

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 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.

Heat transfer in the human eyeball, a complex organ, is significantly influenced by various pathophysiological and external parameters. Particularly, heat transfer critically affects fluid behavior within the eye and ocular drug delivery processes. Overcoming the challenges of experimental analysis, this study introduces a comprehensive three-dimensional mathematical and computational model to simulate the heat transfer in a realistic geometry. Our work includes an extensive sensitivity analysis to address uncertainties and delineate the impact of different variables on heat distribution in ocular tissues. To manage the model's complexity, we employed a very fast model reduction technique with certified sharp error bounds, ensuring computational efficiency without compromising accuracy. Our results demonstrate remarkable consistency with experimental observations and align closely with existing numerical findings in the literature. Crucially, our findings underscore the significant role of blood flow and environmental conditions, particularly in the eye's internal tissues. Clinically, this model offers a promising tool for examining the temperature-related effects of various therapeutic interventions on the eye. Such insights are invaluable for optimizing treatment strategies in ophthalmology.

The opening and closing dynamics of the aortic valve (AV) has a strong influence on haemodynamics in the aortic root, and both play a pivotal role in maintaining normal physiological functions of the valve. The aim of this study was to establish a subject-specific fluid-structure interaction (FSI) workflow capable of simulating the motion of a tricuspid healthy valve and the surrounding haemodynamics under physiologically realistic conditions. A subject-specific aortic root was reconstructed from magnetic resonance (MR) images acquired from a healthy volunteer, whilst the valve leaflets were built using a parametric model fitted to the subject-specific aortic root geometry. The material behaviour of the leaflets was described using the isotropic hyperelastic Ogden model, and subject-specific boundary conditions were derived from 4D-flow MR imaging (4D-MRI). Strongly coupled FSI simulations were performed using a finite volume-based boundary conforming method implemented in FlowVision. Our FSI model was able to simulate the opening and closing of the AV throughout the entire cardiac cycle. Comparisons of simulation results with 4D-MRI showed a good agreement in key haemodynamic parameters, with stroke volume differing by 7.5% and the maximum jet velocity differing by less than 1%. Detailed analysis of wall shear stress (WSS) on the leaflets revealed much higher WSS on the ventricular side than the aortic side and different spatial patterns amongst the three leaflets.

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 10⁴ against conventional FE computations and that beyond 10³ against the original pRBMOR approach are observed.

Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time-resolved three-dimensional phase-contrast magnetic resonance imaging (4D flow MRI), which enables noninvasive time-dependent velocity measurements within large vessels. However, several limitations hinder the usability of 4D flow MRI and other experimental methods for quantitative hemodynamics analysis. These mainly include measurement noise, corrupt or missing data, low spatiotemporal resolution, and other artifacts. Traditional filtering is routinely applied for denoising experimental blood flow data without any detailed discussion on why it is preferred over other methods. In this study, filtering is compared to different singular value decomposition (SVD)-based machine learning and autoencoder-type deep learning methods for denoising and filling in missing data (imputation). An artificially corrupted and voxelized computational fluid dynamics (CFD) simulation as well as in vitro 4D flow MRI data are used to test the methods. SVD-based algorithms achieve excellent results for the idealized case but severely struggle when applied to in vitro data. The autoencoders are shown to be versatile and applicable to all investigated cases. For denoising, the in vitro 4D flow MRI data, the denoising autoencoder (DAE), and the Noise2Noise (N2N) autoencoder produced better reconstructions than filtering both qualitatively and quantitatively. Deep learning methods such as N2N can result in noise-free velocity fields even though they did not use clean data during training. This work presents one of the first comprehensive assessments and comparisons of various classical and modern machine-learning methods for enhancing corrupt cardiovascular flow data in diseased arteries for both synthetic and experimental test cases.

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.

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.

Comminuted proximal humerus fractures are often repaired by metal plates, but potentially still experience bone refracture, bone "stress shielding," screw perforation, delayed healing, and so forth. This "proof of principle" investigation is the initial step towards the design of a new plate using alternative materials to address some of these problems. Finite element modeling was used to create design graphs for bone stress, plate stress, screw stress, and interfragmentary motion via three different fixations (no, 1, or 2 "kickstand" [KS] screws across the fracture) using a wide range of plate elastic moduli (E_P = 5-200 GPa). Well-known design optimization criteria were used that could minimize bone, plate, and screw failure (i.e., peak stress < ultimate tensile strength), reduce bone "stress shielding" (i.e., bone stress under the new plate ≥ bone stress for an intact humerus, titanium plate, and/or steel plate "control"), and encourage callus growth leading to early healing (i.e., 0.2 mm ≤ axial interfragmentary motion ≤ 1 mm; shear/axial interfragmentary motion ratio <1.6). The findings suggest that a potentially optimal configuration involves the new plate being manufactured from a material with an E_P of 5-41.5 GPa with 1 KS screw; but, using no KS screws would cause immediate bone fracture and 2 KS screws would almost certainly lead to delayed healing. A prototype plate might be fabricated using alternative materials suggested for orthopedics and other industries, like fiber-metal laminates, fiber-reinforced polymers, metal foams, pure polymers, shape memory alloys, or 3D-printed porous metals.

The article presents a semi-automatic approach to generating structured hexahedral meshes of patient-specific aortas ailed by aortic dissection. The condition manifests itself as a formation of two blood flow channels in the aorta, as a result of a tear in the inner layers of the aortic wall. Subsequently, the morphology of the aorta is greatly impacted, making the task of domain discretization highly challenging. The meshing algorithm presented herein is automatic for the individual lumina, whereas the tears require user interaction. Starting from an input (triangle) surface mesh, we construct an implicit surface representation as well as a topological skeleton, which provides a basis for the generation of a block-structure. Thereafter, the mesh generation is performed via transfinite maps. The meshes are structured and fully hexahedral, exhibit good quality and reliably match the original surface. As they are generated with computational fluid dynamics in mind, a fluid flow simulation is performed to verify their usefulness. Moreover, since the approach is based on valid block-structures, the meshes can be made very coarse (around 1000 elements for an entire aortic dissection domain), and thus promote using solvers based on the geometric multigrid method, which is typically reliant on the presence of a hierarchy of coarser meshes.