Hemodynamics of Stent Implantation Procedures in Coronary Bifurcations: an in vitro study

Stent implantation in coronary bifurcations presents unique challenges and currently there is no universally accepted stent deployment approach. Despite clinical and computational studies, to date, the effect of each stent implantation method on the coronary artery hemodynamics is not well understood. In this study the hemodynamics of stented coronary bifurcations under pulsatile flow conditions were investigated experimentally. Three implantation methods, provisional side branch (PSB), culotte (CUL), and crush (CRU), were investigated using time-resolved particle image velocimetry (PIV) to measure the velocity fields. Subsequently, hemodynamic parameters including wall shear stress (WSS), oscillatory shear index (OSI), and relative residence time (RRT) were calculated and the pressure field through the vessel was non-invasively quantified. The effects of each stented case were evaluated and compared against an un-stented case. CRU provided the lowest compliance mismatch, but demonstrated detrimental stent interactions. PSB, the clinically preferred method, and CUL maintained many normal flow conditions. However, PSB provided about a 300% increase in both OSI and RRT. CUL yielded a 10% and 85% increase in OSI and RRT, respectively. The results of this study support the concept that different bifurcation stenting techniques result in hemodynamic environments that deviate from that of un-stented bifurcations, to varying degrees.Comment: 33 pages, 8 figures, 3 table

A fully coupled computational fluid dynamics – agent-based model of atherosclerotic plaque development: Multiscale modeling framework and parameter sensitivity analysis

Background: Peripheral Artery Disease (PAD) is an atherosclerotic disorder that leads to impaired lumen patency through intimal hyperplasia and the build-up of plaques, mainly localized in areas of disturbed flow. Computational models can provide valuable insights in the pathogenesis of atherosclerosis and act as a predictive tool to optimize current interventional techniques. Our hypothesis is that a reliable predictive model must include the atherosclerosis development history. Accordingly, we developed a multiscale modeling framework of atherosclerosis that replicates the hemodynamic-driven arterial wall remodeling and plaque formation. Methods: The framework was based on the coupling of Computational Fluid Dynamics (CFD) simulations with an Agent-Based Model (ABM). The CFD simulation computed the hemodynamics in a 3D artery model, while 2D ABMs simulated cell, Extracellular Matrix (ECM) and lipid dynamics in multiple vessel cross-sections. A sensitivity analysis was also performed to evaluate the oscillation of the ABM output to variations in the inputs and to identify the most influencing ABM parameters. Results: Our multiscale model qualitatively replicated both the physiologic and pathologic arterial configuration, capturing histological-like features. The ABM outputs were mostly driven by cell and ECM dynamics, largely affecting the lumen area. A subset of parameters was found to affect the final lipid core size, without influencing cell/ECM or lumen area trends. Conclusion: The fully coupled CFD-ABM framework described atherosclerotic morphological and compositional changes triggered by a disturbed hemodynamics

Relationship between hemodynamics and in-stent restenosis in femoral arteries

Although percutaneous transluminal angioplasty with stenting is one of the preferred treatments of lower extremity peripheral artery disease, this procedure suffers from a 66% 1-year primary patency rate. The unfavorable outcome is mostly attributable to in-stent restenosis, an inflammatory-driven arterial response, characterized by excessive smooth muscle cell proliferative and synthetic activity ultimately leading to lumen re-narrowing. The etiology of in-stent restenosis is multifactorial, involving different systemic, biological and biomechanical drivers. Among the biomechanical factors, a key role has been recognized to the stent-induced hemodynamic alteration, influencing smooth muscle cell activity both directly and through endothelium-dependent mechanisms. In this scenario, computational fluid dynamics simulations of stented femoral arteries allowed quantifying the local hemodynamics and identifying wall shear stress-based hemodynamic predictors of in-stent restenosis. This contributed to enhance the current knowledge of the fluid dynamic-related mechanisms of post-stenting lumen remodeling. However, given the multiscale and multifactorial nature of in-stent restenosis, multiscale mechanobiological modeling relating the intervention-induced mechanical stimuli to the complex network of biological events has recently emerged as a fundamental approach to decipher the underlying pathological pathways. This involves the analysis of interactions, cause-effect relationships, feedback mechanisms and cascade signaling pathways across different spatial and temporal scales, thus allowing tracking the effect of the interventioninduced perturbation to the molecular, cellular and finally tissue response. The present chapter examines the state-of-the-art of computational fluid dynamics studies of in-stent restenosis in femoral arteries and provides an overview on the emerging field of multiscale mechanobiological modeling of arterial adaptation following endovascular procedures

Semi-Automatic Reconstruction of Patient-Specific Stented Coronaries based on Data Assimilation and Computer Aided Design

Purpose The interplay between geometry and hemodynamics is a significant factor in the development of cardiovascular diseases. This is particularly true for stented coronary arteries. To elucidate this factor, an accurate patient-specific analysis requires the reconstruction of the geometry following the stent deployment for a computational fluid dynamics (CFD) investigation. The image-based reconstruction is troublesome for the different possible positions of the stent struts in the lumen and the coronary wall. However, the accurate inclusion of the stent footprint in the hemodynamic analysis is critical for detecting abnormal stress conditions and flow disturbances, particularly for thick struts like in bioresorbable scaffolds. Here, we present a novel reconstruction methodology that relies on Data Assimilation and Computer Aided Design. Methods The combination of the geometrical model of the undeployed stent and image-based data assimilated by a variational approach allows the highly automated reconstruction of the skeleton of the stent. A novel approach based on computational mechanics defines the map between the intravascular frame of reference (called L-view) and the 3D geometry retrieved from angiographies. Finally, the volumetric expansion of the stent skeleton needs to be self-intersection free for the successive CFD studies; this is obtained by using implicit representations based on the definition of Nef-polyhedra. Results We assessed our approach on a vessel phantom, with less than 10% difference (properly measured) vs. a customized manual (and longer) procedure previously published, yet with a significant higher level of automation and a shorter turnaround time. Computational hemodynamics results were even closer. We tested the approach on two patient-specific cases as well. Conclusions The method presented here has a high level of automation and excellent accuracy performances, so it can be used for larger studies involving patient-specific geometries

Automatic segmentation of optical coherence tomography pullbacks of coronary arteries treated with bioresorbable vascular scaffolds: Application to hemodynamics modeling

Automatic algorithms for stent struts segmentation in optical coherence tomography (OCT) images of coronary arteries have been developed over the years, particularly with application on metallic stents. The aim of this study is three-fold: (1) to develop and to validate a segmentation algorithm for the detection of both lumen contours and polymeric bioresorbable scaffold struts from 8-bit OCT images, (2) to develop a method for automatic OCT pullback quality assessment, and (3) to demonstrate the applicability of the segmentation algorithm for the creation of patient-specific stented coronary artery for local hemodynamics analysis