Fatigue analysis of canine tracheal stents using the finite element method

This study aimed to evaluate fatigue of three stent designs when various forces are applied and perform a comparative analyses. A computer simulation using the finite element method was performed. In particular, we constructed a three-dimensional finite element model of nitinol stents with three designs (S6: single-woven wire, wire diameter: 0.006 inch; D6: double-woven wire, wire diameter: 0.006 inch, and D7: double-woven wire, wire diameter: 0.007 inch) that are used to treat canine tracheal collapse (TC). The stents were subjected to a 200 mmHg compression force, a pure torsion force in a perpendicular direction, and a bending-torsion force combining perpendicular and axial forces. The von Mises stress was calculated to evaluate the extent of stent displacement, and Goodman diagrams were plotted to compare fatigue life cycles. D7 exhibited a longer fatigue life compared to S6 and D6. Under compression, pure torsion, and bending-torsion forces, displacement was the smallest for D7, followed by D6 and S6. Similarly, the fatigue life was the longest for D7, followed by D6 and S6. S6 showed the greatest displacement when subjected to external forces; among stents designed using the same wire, D6 displayed less displacement than S6, and D7 exhibited superior fatigue life when subjected to varying degrees of force. This study showed that the structural stability and fatigue life of stents could be effectively compared using finite element method D7 has the greatest stability and structural rigidity under cyclic load.

Numerical Simulation of Dynamic Degradation and Fatigue Damage of Degradable Zinc Alloy Stents

Current research on the fatigue properties of degradable zinc alloy stents has not yet considered the issue of the fatigue life changing with material properties during the dynamic degradation process. Therefore, in this paper, we established a fatigue damage algorithm to study the fatigue problem affected by the changing of material properties during the dynamic degradation process of the stent under the action of pulsating cyclic loading. Three models: the dynamic degradation model, the dynamic degradation model under pulsating cyclic loading, and the coupled model of fatigue damage and dynamic degradation, were developed to verify the effect of fatigue damage on stent life. The results show that fatigue damage leads to a deeper degree of inhomogeneous degradation of the stent, which affects the service life of the stent. Fatigue damage is a factor that cannot be ignored. Therefore, when studying the mechanical properties and lifetime of degradable stents, incorporating fatigue damage into the study can help more accurately assess the lifetime of the stents.

Design and Optimization of a New Anti-reflux Biliary Stent With Retractable Bionic Valve Based on Fluid-Structure Interaction Analysis

Duodenal biliary reflux has been a challenging common problem which could cause dreadful complications after biliary stent implantation. A novel anti-reflux biliary stent with a retractable bionic valve was proposed according to the concertina motion characteristics of annelids. A 2D equivalent fluid-structure interaction (FSI) model based on the axial section was established to analyze and evaluate the mechanical performances of the anti-reflux biliary stent. Based on this model, four key parameters (initial shear modulus of material, thickness, pitch, and width) were selected to investigate the influence of design parameters on anti-reflux performance via an orthogonal design to optimize the stent. The results of FSI analysis showed that the retrograde closure ratio of the retractable valve primarily depended on initial shear modulus of material (p < 0.05) but not mainly depended on the thickness, pitch, and width of the valve (p > 0.05). The optimal structure of the valve was finally proposed with a high retrograde closing ratio of 95.89%. The finite element model revealed that the optimized anti-reflux stent possessed improved radial mechanical performance and nearly equal flexibility compared with the ordinary stent without a valve. Both the FSI model and experimental measurement indicated that the newly designed stent had superior anti-reflux performance, effectively preventing the duodenobiliary reflux while enabling the bile to pass smoothly. In addition, the developed 2D equivalent FSI model provides tremendous significance for resolving the fluid-structure coupled problem of evolution solid with large deformation and markedly shortens the calculation time.

Computational Design and Optimization of Nerve Guidance Conduits for Improved Mechanical Properties and Permeability

Nerve guidance conduits (NGCs) are tubular tissue engineering scaffolds used for nerve regeneration. The poor mechanical properties and porosity have always compromised their performances for guiding and supporting axonal growth. Therefore, in order to improve the properties of NGCs, the computational design approach was adopted to investigate the effects of different NGC structural features on their various properties, and finally design an ideal NGC with mechanical properties matching human nerves and high porosity and permeability. Three common NGC designs, namely hollow luminal, multichannel, and microgrooved, were chosen in this study. Simulations were conducted to study the mechanical properties and permeability. The results show that pore size is the most influential structural feature for NGC tensile modulus. Multichannel NGCs have higher mechanical strength but lower permeability compared to other designs. Square pores lead to higher permeability but lower mechanical strength than circular pores. The study finally selected an optimized hollow luminal NGC with a porosity of 71% and tensile modulus of 8 MPa to achieve multiple design requirements. The use of computational design and optimization was shown to be promising in future NGC design and nerve tissue engineering research.

Assessment of cortical bone fracture resistance curves by fusing artificial neural networks and linear regression

Bone injures (BI) represents one of the major health problems, together with cancer and cardiovascular diseases. Assessment of the risks associated with BI is nontrivial since fragility of human cortical bone is varying with age. Due to restrictions for performing experiments on humans, only a limited number of fracture resistance curves (R-curves) for particular ages have been reported in the literature. This study proposes a novel decision support system for the assessment of bone fracture resistance by fusing various artificial intelligence algorithms. The aim was to estimate the R-curve slope, toughness threshold and stress intensity factor using the two input parameters commonly available during a routine clinical examination: patients age and crack length. Using the data from the literature, the evolutionary assembled Artificial Neural Network was developed and used for the derivation of Linear regression (LR) models of R-curves for arbitrary age. Finally, by using the patient (age)-specific LR models and diagnosed crack size one could estimate the risk of bone fracture under given physiological conditions. Compared to the literature, we demonstrated improved performances for estimating nonlinear changes of R-curve slope (R² = 0.82 vs. R² = 0.76) and Toughness threshold with ageing (R² = 0.73 vs. R² = 0.66).

Three-dimensional reconstruction and NURBS-based structured meshing of coronary arteries from the conventional X-ray angiography projection images

Despite its two-dimensional nature, X-ray angiography (XRA) has served as the gold standard imaging technique in the interventional cardiology for over five decades. Accordingly, demands for tools that could increase efficiency of the XRA procedure for the quantitative analysis of coronary arteries (CA) are constantly increasing. The aim of this study was to propose a novel procedure for three-dimensional modeling of CA from uncalibrated XRA projections. A comprehensive mathematical model of the image formation was developed and used with a robust genetic algorithm optimizer to determine the calibration parameters across XRA views. The frames correspondences between XRA acquisitions were found using a partial-matching approach. Using the same matching method, an efficient procedure for vessel centerline reconstruction was developed. Finally, the problem of meshing complex CA trees was simplified to independent reconstruction and meshing of connected branches using the proposed nonuniform rational B-spline (NURBS)-based method. Because it enables structured quadrilateral and hexahedral meshing, our method is suitable for the subsequent computational modelling of CA physiology (i.e. coronary blood flow, fractional flow reverse, virtual stenting and plaque progression). Extensive validations using digital, physical, and clinical datasets showed competitive performances and potential for further application on a wider scale.

STUDY ON THE IMPACT OF STRAIGHT STENTS ON ARTERIES WITH DIFFERENT CURVATURES

Different stent structures lead to different deformations of blood vessels, such as different cross-sectional shapes, which further influence the blood flow patterns. In this paper, six non-commercial stents with different link structures called I-, C-, S-, U-, N- and W-types were considered. Their influences on arteries with five different curvatures (i.e., 0[Formula: see text], 15[Formula: see text], 30[Formula: see text], 45[Formula: see text] and 60[Formula: see text]) were studied using finite element method. Four indices including the maximum plastic strain of stents, the rate of expansion, the maximum von Mises stress and the ellipticity of arteries, were compared for all cases. The results showed that the S-type or U-type stents, with larger plastic strain and lower von Mises stress on the arteries, provided the optimal outcome. As the link structures became complex, the arterial expansion increased monotonically, while the ellipticity of arteries showed a decreasing tendency in the vessel models. The present study could be useful for the commercial design and clinic selection of a stent with different link structures for different curved arteries.

Finite element analysis of uncommonly large renal arteriovenous malformation--adjacent renal cyst complex

BACKGROUND

Renal arteriovenous malformation (RAVM) represents abnormal communication between the intrarenal arterial and venous system. The purpose of this study was to investigate hemodynamics and biomechanics quantities which may influence the instability of RAVM and imply clinical complications.

METHODS

A detailed 3D reconstruction of RAVM was obtained from the patient CT scans, aortic inlet flow was measured by color-flow Doppler ultrasound, while material characteristics were adopted from the literature. A numerical finite element analysis (FEA) of the blood flow was performed by solving the governing equations for the viscous incompressible flow. The physical quantities calculated at the systolic and diastolic peak moment were velocity, pressure, shear stress and drag forces.

RESULTS

We reported a case of a 50-year-old patient with a large RAVM and adjacent renal cyst, who unsuccessfully underwent two attempts of embolization that resulted in the consequent nephrectomy. FEA showed that the cyst had a very low pressure intensity and velocity field (with unstable flow in diastolic peak). For both systolic and diastolic moments, increased values of wall shear stress were found on the places with intensive wall calcification. Unusually high values of drag force which would likely explain the presence of pressure in the cystic formation were found on the infero-medial side where the cyst wall was the thinnest and where the flow streamlines converged.

CONCLUSIONS

FEA showed that the hemodynamics of the cyst-RAVM complex was unstable making it prone to rupture. Clinically established diagnosis of imminent rupture together with unfavorable hemodynamics of the lesion consequently made additional attempts of embolization risky and unsuccessful leading to total nephrectomy.