Retrograde type A dissection after thoracic endovascular aortic repair has been a major drawback of endovascular treatment. This study investigated the biomechanical mechanism of stent‐graft‐induced new lesions after implantation and analyzed the relationship between radial force and spring‐back force of the stent‐graft when it was implanted virtually under different oversizing ratios. Based on the computed tomography angiography images, a three‐dimensional geometric model of a patient‐specific aortic dissection was established. The stent was designed in CAD software and the stent‐graft implantation procedure under different oversizing ratios was simulated in the finite element analysis software. Implantation simulations were performed six times for each stent‐graft model under 0%, 3%, 6%, 9%, 12%, and 15% oversizing ratios and the peak stress of the aorta was compared among groups. It was observed that the peak stress of the aorta was located where the proximal bare stent interacted with aortic wall and its value was increased by 62.2% from 0% to 15% oversizing ratio. The conclusions are reached that the long‐term higher stress in the aortic wall may lead to the emergence of new lesions in these areas, and the radial force plays a key role in the formation of a new entry in the real aorta model.
BackgroundEndovascular intervention using a stent is a mainstream treatment for cerebral aneurysms. To assess the effect of intervention strategies on aneurysm hemodynamics, we have developed a fast virtual stenting (FVS) technique to simulate stent deployment in patient-specific aneurysms. However, quantitative validation of the FVS against experimental data has not been fully addressed. In this study, we performed in vitro analysis of a patient-specific model to illustrate the realism and usability of this novel FVS technique.MethodsWe selected a patient-specific aneurysm and reproduced it in a manufactured realistic aneurismal phantom. Three numerical simulation models of the aneurysm with an Enterprise stent were constructed. Three models were constructed to obtain the stented aneurysms: a physical phantom scanned by micro-CT, fast virtual stenting technique and finite element method. The flow in the three models was simulated using a computational fluid dynamics software package, and the hemodynamics parameters for the three models were calculated and analyzed.ResultsThe computational hemodynamics in the patient-specific aneurysm of the three models resembled the very well. A qualitative comparison revealed high similarity in the wall shear stress, streamline, and velocity plane among the three different methods. Quantitative comparisons revealed that the difference ratios of the hemodynamic parameters were less than 10%, with the difference ratios for area average of wall shear stress in the aneurysm being very low.ConclusionsIn conclusion, the results of the computational hemodynamics indicate that FVS is suitable for evaluation of the hemodynamic factors that affect treatment outcomes.
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