Fluid‐structure interaction analysis of transcatheter aortic valve implantation

Abstract

Transcatheter aortic valve implantation (TAVI) is a minimally invasive intervention for the treatment of severe aortic valve stenosis. The main cause of failure is the structural deterioration of the implanted prosthetic leaflets, possibly inducing a valvular re‐stenosis 5–10 years after the implantation. Based solely on pre‐implantation data, the aim of this work is to identify fluid‐dynamics and structural indices that may predict the possible valvular deterioration, in order to assist the clinicians in the decision‐making phase and in the intervention design. Patient‐specific, pre‐implantation geometries of the aortic root, the ascending aorta, and the native valvular calcifications were reconstructed from computed tomography images. The stent of the prosthesis was modeled as a hollow cylinder and virtually implanted in the reconstructed domain. The fluid‐structure interaction between the blood flow, the stent, and the residual native tissue surrounding the prosthesis was simulated by a computational solver with suitable boundary conditions. Hemodynamical and structural indicators were analyzed for five different patients that underwent TAVI – three with prosthetic valve degeneration and two without degeneration – and the comparison of the results showed a correlation between the leaflets' structural degeneration and the wall shear stress distribution on the proximal aortic wall. This investigation represents a first step towards computational predictive analysis of TAVI degeneration, based on pre‐implantation data and without requiring additional peri‐operative or follow‐up information. Indeed, being able to identify patients more likely to experience degeneration after TAVI may help to schedule a patient‐specific timing of follow‐up.

The role of computational methods in cardiovascular medicine: a narrative review

“…Another image-based computational model for hemodynamics was developed ( 93 ) for the investigation on transcatheter aortic valve implantation (TAVI) and the occurrence of structural valve degeneration (SVD) years after the intervention. Based only on pre - implantation CT acquisitions, we reconstructed the patient-specific geometries of the aorta for different patients (three that encountered SVD and two that did not), virtually implanted the prosthetic device, and simulated numerically the blood flow and its interaction with the prosthesis and the native valvular tissue, in a post - implantation scenario.…”

“… WSS on the aortic wall of patients with TAVI ( 93 ): WSS distribution at systolic peak (left) and time evolution of average WSS in the orange area (right). High intensity and long persistence of WSS are predictive indicators of SVD.…”

“…Furthermore, the physical content of mathematical models can also give access to quantities that are not measurable in vivo . This is the case, for example, of the shear stress exerted by the blood flow on the ventricular ( 45 ) and aortic ( 93 ) wall or even on valve leaflets ( 113 ), as shown in Figure 7 , the transmembrane electric potential in the atria ( 18 ) and ventricles ( 84 , 118 ), as shown in Figure 1 , or the specific orientation of conduction fibers in atria ( 18 , 122 ). The relevance of quantifying these quantities lies in the established correlation they have with the heart function or the development of pathological conditions: e.g., fiber orientation strongly affects the overall electrical activity and contraction of the heart ( 123 , 124 ), and strongly oscillating values of the WSS are known to induce plaque formation in the vessels ( 125 , 126 ).…”

Accelerated simulation methodologies for computational vascular flow modelling

“…Coupling the haemodynamics to solid mechanics or biochemical reaction models may also be required in certain applications. Fluid-structure interaction (FSI) is required when vessel distensibility is important or when there is a complex interaction between blood flow and valves or implanted devices [7][8][9][10]. Biochemical reactions are crucial in modelling thrombosis and endothelialisation depends on interactions between blood and blood-contacting surfaces of devices [11,12].…”

A fast in silico model for preoperative risk assessment of paravalvular leakage

“…Fumagalli et al. ( 2023 ) developed a FSI model to identify fluid dynamics and structural indices to predict the possibility of valvular deterioration to assist clinicians in the intervention design. Their results showed there was a correlation between the leaflets’ structural degeneration and the wall shear stress distribution on the proximal aortic wall.…”