A surrogate model for plaque modeling in carotids based on Robin conditions calibrated by cine MRI data

Toward a physiological model of vascular wall vibrations in the arteriovenous fistula

The mechanism behind hemodialysis arteriovenous fistula (AVF) failure remains poorly understood, despite previous efforts to correlate altered hemodynamics with vascular remodeling. We have recently demonstrated that transitional flow induces high-frequency vibrations in the AVF wall, albeit with a simplified model. This study addresses the key limitations of our original fluid-structure interaction (FSI) approach, aiming to evaluate the vibration response using a more realistic model. A 3D AVF geometry was generated from contrast-free MRI and high-fidelity FSI simulations were performed. Patient-specific inflow and pressure were incorporated, and a three-term Mooney-Rivlin model was fitted using experimental data. The viscoelastic effect of perivascular tissue was modeled with Robin boundary conditions. Prescribing pulsatile inflow and pressure resulted in a substantial increase in vein displacement ( + 400 %) and strain ( + 317 %), with a higher maximum spectral frequency becoming visible above -42 dB (from 200 to 500 Hz). Transitioning from Saint Venant-Kirchhoff to Mooney-Rivlin model led to displacement amplitudes exceeding 10 micrometers and had a substantial impact on strain ( + 116 %). Robin boundary conditions significantly damped high-frequency displacement ( - 60 %). Incorporating venous tissue properties increased vibrations by 91%, extending up to 700 Hz, with a maximum strain of 0.158. Notably, our results show localized, high levels of vibration at the inner curvature of the vein, a site known for experiencing pronounced remodeling. Our findings, consistent with experimental and clinical reports of bruits and thrills, underscore the significance of incorporating physiologically plausible modeling approaches to investigate the role of wall vibrations in AVF remodeling and failure.

Fluid-structure interaction analysis of transcatheter aortic valve implantation

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.

Fluid structure interaction analysis to stratify the behavior of different atheromatous carotid plaques

BACKGROUND

In asymptomatic carotid stenosis (ACS), different plaque types, i.e. lipidic (LP), fibrous (FP), and calcific (CP), could have different hemodynamic and structural behaviors.

METHODS

Different carotid plaques, reconstructed from medical imaging of ACS >70%, were analyzed by computing fluid structure interaction (FSI), modeling the spatial distribution of wall shear stresses (WSS), plaque displacements (D), von Mises stresses (VMS), and absorbed elastic energy (AEE) together with their maximum-in-space values at the systole (WSS<inf>syst</inf>, D<inf>syst</inf>, VMS<inf>syst</inf> and AEE<inf>syst</inf>).

RESULTS

WSS resulted significantly higher in CP, whereas D and VMS showed the highest values for LP. Regarding AEE<inf>syst</inf> stored by the plaques, LP absorbed in average 2320 J/m³, FP 408 J/m³ (470%) and CP 99 J/m³ (2240%), (P<0.01, P<0.01, and P<0.01, respectively).

CONCLUSIONS

Depending upon their nature, plaques store different deformations and inner distributions of forces, thus potentially influencing their vulnerability.

Inverse problems in blood flow modeling: A review

Mathematical and computational modeling of the cardiovascular system is increasingly providing non-invasive alternatives to traditional invasive clinical procedures. Moreover, it has the potential for generating additional diagnostic markers. In blood flow computations, the personalization of spatially distributed (i.e., 3D) models is a key step which relies on the formulation and numerical solution of inverse problems using clinical data, typically medical images for measuring both anatomy and function of the vasculature. In the last years, the development and application of inverse methods has rapidly expanded most likely due to the increased availability of data in clinical centers and the growing interest of modelers and clinicians in collaborating. Therefore, this work aims to provide a wide and comparative overview of literature within the last decade. We review the current state of the art of inverse problems in blood flows, focusing on studies considering fully dimensional fluid and fluid-solid models. The relevant physical models and hemodynamic measurement techniques are introduced, followed by a survey of mathematical data assimilation approaches used to solve different kinds of inverse problems, namely state and parameter estimation. An exhaustive discussion of the literature of the last decade is presented, structured by types of problems, models and available data.

Computational Fluid-Structure Interaction Study of a New Wave Membrane Blood Pump

PURPOSE

Wave membrane blood pumps (WMBP) are novel pump designs in which blood is propelled by means of wave propagation by an undulating membrane. In this paper, we computationally studied the performance of a new WMBP design (J-shaped) for different working conditions, in view of potential applications in human patients.

METHODS

Fluid-structure interaction (FSI) simulations were conducted in 3D pump geometries and numerically discretized by means of the extended finite element method (XFEM). A contact model was introduced to capture membrane-wall collisions in the pump head. Mean flow rate and membrane envelope were determined to evaluate hydraulic performance. A preliminary hemocompatibility analysis was performed via calculation of fluid shear stress.

RESULTS

Numerical results, validated against in vitro experimental data, showed that the hydraulic output increases when either the frequency or the amplitude of membrane oscillations were higher, with limited increase in the fluid stresses, suggesting good hemocompatibility properties. Also, we showed better performance in terms of hydraulic power with respect to a previous design of the pump. We finally studied an operating point which achieves physiologic flow rate target at diastolic head pressure of 80 mmHg.

CONCLUSION

A new design of WMBP was computationally studied. The proposed FSI model with contact was employed to predict the new pump hydraulic performance and it could help to properly select an operating point for the upcoming first-in-human trials.