Computational simulation of stent thrombosis induced by various degrees of stent malapposition.

Percutaneous coronary intervention with stent implantation is one of the most commonly used approaches to treat coronary artery stenosis. Stent malapposition (SM) can increase the incidence of stent thrombosis, but the quantitative association between SM distance and stent thrombosis is poorly clarified. The objective of this study is to determine the biomechanical reaction mechanisms underlying stent thrombosis induced by SM and to quantify the effect of different SM severity grades on thrombosis. The thrombus simulation was performed in a continuous model based on the diffusion-convection response of blood substance transport. Simulated models included well-apposed stents and malapposed stents with various severities where the detachment distances ranged from 0 to 400 µm. The abnormal shear stress induced by SM was considered a critical contributor affecting stent thrombosis, which was dependent on changing SM distances in the simulation. The results illustrate that the proportion of thrombus volume was 1.88% at a SM distance of 75 µm (mild), 3.46% at 150 µm, and 3.93% at 400 µm (severe), but that a slight drop (3.18%) appeared at the detachment distance of 225 µm (intermediate). The results indicate that when the SM distance was less than 150 µm, the thrombus rose notably as the gap distance increased, whereas the progression of thrombogenicity weakened when it exceeded 150 µm. Therefore, more attention should be paid when SM is present at a gap distance of 150 µm. Moreover, when the SM length of stents are the same, thrombus tends to accumulate downstream towards the distal end of the stent as the SM distance increases.

A computational analysis of potential aortic dilation induced by the hemodynamic effects of bicuspid aortic valve phenotypes.

BACKGROUND AND OBJECTIVES: The bicuspid aortic valve (BAV) is a major risk factor for the progression of aortic dilation (AD) because of the induced abnormal blood flow environment in aorta. The differences in the development of AD induced by BAV phenotypes remains unclear. Therefore, the objective of this study was to assess the potential locations of AD induced by different phenotypes of BAV. The different effects of opening orifice area and leaflet orientation on ascending aortic hemodynamics in Type-1 BAV was investigated by means of numerical simulation. METHODS: Finite element dynamic analysis was performed on tricuspid aortic valve (TAV) and BAV models to simulate the motion of the leaflets and obtain the geometrical characteristics of AV at peak systole as a reference, which were used for aortic models. Then, four sets of aortic fluid models were designed according to the leaflet fusion types [TAV; BAV (left-right-coronary cusp fusion, LR; right-non-coronary cusp fusion, RN; left-non-coronary cusp fusion, LN)], and the computational fluid dynamics method was applied to compare the hemodynamic differences within the aorta at peak systole. RESULTS: The maximum opening area of BAV was significantly reduced, resulting in alterations in aortic hemodynamics compared with TAV. The velocity streamlines were essentially parallel to the aortic wall in TAV. The average pressure and wall shear stress in aorta tend to be stable. In contrary, the eccentricity of BAV orifice jet resulted in high-velocity flow directed toward the ascending aorta (AA) wall and aortic arch for LR and LN; RN features an asymmetrical velocity distribution toward the outer bend of the middle AA, and eccentric flow tends to impact the distal AA. As the flow angle is associated with distinct flow impingement locations, different degrees of WSS and pressure concentration occur along the aortic wall from the AA to the aortic arch in three BAV types. CONCLUSIONS: The BAV morphotype affects the aortic hemodynamics, and the abnormal blood flow associated with BAV may play a role in AD. The different BAV phenotypes determine the direction of blood flow jet and change the expression of dilation. LR is likely to cause dilation of the tubular AA; RN results in dilation of the middle AA to proximal aortic arch; and LN causes an increased incidence of the tubular AA and the proximal aortic arch.

Research on the Method of Predicting Fractional Flow Reserve Based on Multiple Independent Risk Factors.

The use of diameter stenosis (DS), as revealed by coronary angiography, for predicting fractional flow reserve (FFR) usually results in a high error rate of detection. In this study, we investigated a method for predicting FFR in patients with coronary stenosis based on multiple independent risk factors. The aim of the study was to improve the accuracy of detection. First, we searched the existing literature to identify multiple independent risk factors and then calculated the corresponding odds ratios. The improved analytic hierarchy process (IAHP) was then used to determine the weighted value of each independent risk factor, based on the corresponding odds ratio. Next, we developed a novel method, based on the top seven independent risk factors with the highest weighted values, to predict FFR. This model was then used to predict the FFR of 253 patients with coronary stenosis, and the results were then compared with previous methods (DS alone and a simplified scoring system). In addition to DS, we identified a range of other independent risk factors, with the highest weighted values, for predicting FFR, including gender, body mass index, location of stenosis, type of coronary artery distribution, left ventricular ejection fraction, and left myocardial mass. The area under the receiver-operating characteristic curve (AUC) for the newly developed method was 84.3% (95% CI: 79.2-89.4%), which was larger than 65.3% (95% CI: 61.5-69.1%) of DS alone and 74.8% (95% CI: 68.4-81.2%) of the existing simplified scoring system. The newly developed method, based on multiple independent risk factors, effectively improves the prediction accuracy for FFR.