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The introduction of drug-eluting stents (DES) has reduced the occurrence of restenosis in coronary arteries. However, restenosis remains a problem in stented coronary bifurcations. This study investigates and compares three different second generation DESs when being implanted in the curved main branch of a coronary bifurcation with the aim of providing better insights into the related changes of the mechanical environment. The 3D bifurcation model is based on patient-specific angiographic data that accurately reproduce the in vivo curvatures of the vessel segments. The layered structure of the arterial wall and its anisotropic mechanical behavior are taken into account by applying a novel algorithm to define the fiber orientations. An innovative simulation strategy considering the insertion of a folded balloon catheter over a guide wire is proposed in order to position the stents within the curved vessel. Straightening occurs after implantation of all stents investigated. The resulting distributions of the wall stresses are strongly dependent on the stent design. Using a parametric modeling approach, two design modifications, which reduce the predicted maximum values of the wall stress, are proposed and analyzed.

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The purpose of this study is to investigate how the imposition of personalized, non-invasively measured blood flow rates as boundary conditions (BCs) influences image-based computational hemodynamic studies in the human aorta. We extracted from 4D phase-contrast MRI acquisitions of a healthy human (1) the geometry of the thoracic aorta with supra-aortic arteries and (2) flow rate waveforms at all boundaries. Flow simulations were carried out, and the implications that the imposition of different BC schemes based on the measured flow rates have on wall shear stress (WSS)-based indicators of abnormal flow were analyzed. Our results show that both the flow rate repartition among the multiple outlets of the aorta and the distribution and magnitude of the WSS-based indicators are strongly influenced by the adopted BC strategy. Keeping as reference hemodynamic model the one where the applied BC scheme allowed to obtain a satisfactory agreement between the computed and the measured flow rate waveforms, differences in WSS-based indicators up to 49% were observed when the other BC strategies were applied. In conclusion, we demonstrate that in subject-specific computational hemodynamics models of the human aorta the imposition of BC settings based on non-invasively measured flow rate waveforms influences indicators of abnormal flow to a large extent. Hence, a BCs set-up assuring realistic, subject-specific instantaneous flow rate distribution must be applied when BCs such as flow rates are prescribed.

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Aims: Our aim was to validate patient-specific software integrating baseline anatomy and biomechanical properties of both the aortic root and valve for the prediction of valve morphology and aortic leaflet calcium displacement after TAVI.Methods and results: Finite element computer modelling was performed in 39 patients treated with a Medtronic CoreValve System (MCS; n=33) or an Edwards SAPIEN XT (ESV; n=6). Quantitative axial frame morphology at inflow (MCS, ESV) and nadir, coaptation and commissures (MCS) was compared between multislice computed tomography (MSCT) post TAVI and a computer model as well as displacement of the aortic leaflet calcifications, quantified by the distance between the coronary ostium and the closest calcium nodule. Bland-Altman analysis revealed a strong correlation between the observed (MSCT) and predicted frame dimensions, although small differences were detected for, e.g., Dmin at the inflow (mean±SD MSCT vs. model: 21.6±2.4 mm vs. 22.0±2.4 mm; difference±SD: -0.4±1.3 mm, p<0.05) and Dmax (25.6±2.7 mm vs. 26.2±2.7 mm; difference±SD: -0.6±1.0 mm, p<0.01). The observed and predicted calcium displacements were highly correlated for the left and right coronary ostia (R 2 =0.67 and R 2 =0.71, respectively p<0.001).Conclusions: Dedicated software allows accurate prediction of frame morphology and calcium displacement after valve implantation, which may help to improve outcome. KEYWORDS• aortic stenosis • computer modelling • transcatheter aortic valve implantation (TAVI)