Impact of flow pulsatility on arterial drug distribution in stent-based therapy

Drug-eluting stents reside in a dynamic fluid environment where the extent to which drugs are distributed within the arterial wall is critically modulated by the blood flowing through the arterial lumen. Yet several factors associated with the pulsatile nature of blood flow and their impact on arterial drug deposition have not been fully investigated. We employed an integrated framework comprising bench-top and computational models to explore the factors governing the time-varying fluid dynamic environment within the vasculature and their effects on arterial drug distribution patterns. A custom-designed bench-top framework comprising a model of a single drug-eluting stent strut and a poly-vinyl alcohol-based hydrogel as a model tissue bed simulated fluid flow and drug transport under fully apposed strut settings. Bench-top experiments revealed a relative independence between drug distribution and the factors governing pulsatile flow and these findings were validated with the in silico model. Interestingly, computational models simulating suboptimal deployment settings revealed a complex interplay between arterial drug distribution, Womersley number and the extent of malapposition. In particular, for a stent strut offset from the wall, total drug deposition was sensitive to changes in the pulsatile flow environment, with this dependence increasing with greater wall displacement. Our results indicate that factors governing pulsatile luminal flow on arterial drug deposition should be carefully considered in conjunction with device deployment settings for better utilization of drug-eluting stent therapy.National Institutes of Health (U.S.) (grant NIH R01 GM-49039

Stent Thrombogenicity Early in High Risk Interventional Settings is Driven by Stent Design and Deployment, and Protected by Polymer-Drug Coatings

Author Manuscript: 2012 April 5Background—Stent thrombosis is a lethal complication of endovascular intervention. Concern has been raised about the inherent risk associated with specific stent designs and drug-eluting coatings, yet clinical and animal support is equivocal. Methods and Results—We examined whether drug-eluting coatings are inherently thrombogenic and if the response to these materials was determined to a greater degree by stent design and deployment with custom-built stents. Drug/polymer coatings uniformly reduce rather than increase thrombogenicity relative to matched bare metal counterparts (0.65-fold; P=0.011). Thick-strutted (162 μm) stents were 1.5-fold more thrombogenic than otherwise identical thin-strutted (81 μm) devices in ex vivo flow loops (P<0.001), commensurate with 1.6-fold greater thrombus coverage 3 days after implantation in porcine coronary arteries (P=0.004). When bare metal stents were deployed in malapposed or overlapping configurations, thrombogenicity increased compared with apposed, length-matched controls (1.58-fold, P=0.001; and 2.32-fold, P<0.001). The thrombogenicity of polymer-coated stents with thin struts was lowest in all configurations and remained insensitive to incomplete deployment. Computational modeling–based predictions of stent-induced flow derangements correlated with spatial distribution of formed clots. Conclusions—Contrary to popular perception, drug/polymer coatings do not inherently increase acute stent clotting; they reduce thrombosis. However, strut dimensions and positioning relative to the vessel wall are critical factors in modulating stent thrombogenicity. Optimal stent geometries and surfaces, as demonstrated with thin stent struts, help reduce the potential for thrombosis despite complex stent configurations and variability in deployment

Mining data from hemodynamic simulations via Bayesian emulation

Background: Arterial geometry variability is inevitable both within and across individuals. To ensure realistic prediction of cardiovascular flows, there is a need for efficient numerical methods that can systematically account for geometric uncertainty. Methods and results: A statistical framework based on Bayesian Gaussian process modeling was proposed for mining data generated from computer simulations. The proposed approach was applied to analyze the influence of geometric parameters on hemodynamics in the human carotid artery bifurcation. A parametric model in conjunction with a design of computer experiments strategy was used for generating a set of observational data that contains the maximum wall shear stress values for a range of probable arterial geometries. The dataset was mined via a Bayesian Gaussian process emulator to estimate: (a) the influence of key parameters on the output via sensitivity analysis, (b) uncertainty in output as a function of uncertainty in input, and (c) which settings of the input parameters result in maximum and minimum values of the output. Finally, potential diagnostic indicators were proposed that can be used to aid the assessment of stroke risk for a given patient's geometry.University of Southampton. School of Engineering Science

Luminal flow amplifies stent-based drug deposition in arterial

Background: Treatment of arterial bifurcation lesions using drug-eluting stents (DES) is now common clinical practice and yet the mechanisms governing drug distribution in these complex morphologies are incompletely understood. It is still not evident how to efficiently determine the efficacy of local drug delivery and quantify zones of excessive drug that are harbingers of vascular toxicity and thrombosis, and areas of depletion that are associated with tissue overgrowth and luminal re-narrowing. Methods and Results: We constructed two-phase computational models of stent-deployed arterial bifurcations simulating blood flow and drug transport to investigate the factors modulating drug distribution when the main-branch (MB) was treated using a DES. Simulations predicted extensive flow-mediated drug delivery in bifurcated vascular beds where the drug distribution patterns are heterogeneous and sensitive to relative stent position and luminal flow. A single DES in the MB coupled with large retrograde luminal flow on the lateral wall of the side-branch (SB) can provide drug deposition on the SB lumen-wall interface, except when the MB stent is downstream of the SB flow divider. In an even more dramatic fashion, the presence of the SB affects drug distribution in the stented MB. Here fluid mechanic effects play an even greater role than in the SB especially when the DES is across and downstream to the flow divider and in a manner dependent upon the Reynolds number. Conclusions: The flow effects on drug deposition and subsequent uptake from endovascular DES are amplified in bifurcation lesions. When only one branch is stented, a complex interplay occurs – drug deposition in the stented MB is altered by the flow divider imposed by the SB and in the SB by the presence of a DES in the MB. The use of DES in arterial bifurcations requires a complex calculus that balances vascular and stent geometry as well as luminal flow

Enhancing physiologic simulations using supervised learning on coarse mesh solutions

Computational modelling of physical and biochemical processes has emerged as a means of evaluating medical devices, offering new insights that explain current performance, inform future designs and even enable personalized use. Yet resource limitations force one to compromise with reduced order computational models and idealized assumptions that yield either qualitative descriptions or approximate, quantitative solutions to problems of interest. Considering endovascular drug delivery as an exemplary scenario, we used a supervised machine learning framework to process data generated from low fidelity coarse meshes and predict high fidelity solutions on refined mesh configurations. We considered two models simulating drug delivery to the arterial wall: (i) two-dimensional drug-coated balloons and (ii) three-dimensional drug-eluting stents. Simulations were performed on computational mesh configurations of increasing density. Supervised learners based on Gaussian process modelling were constructed from combinations of coarse mesh setting solutions of drug concentrations and nearest neighbourhood distance information as inputs, and higher fidelity mesh solutions as outputs. These learners were then used as computationally inexpensive surrogates to extend predictions using low fidelity information to higher levels of mesh refinement. The cross-validated, supervised learner-based predictions improved fidelity as compared with computational simulations performed at coarse level meshes—a result consistent across all outputs and computational models considered. Supervised learning on coarse mesh solutions can augment traditional physics-based modelling of complex physiologic phenomena. By obtaining efficient solutions at a fraction of the computational cost, this framework has the potential to transform how modelling approaches can be applied in the evaluation of medical technologies and their real-time administration in an increasingly personalized fashion.United States. Dept. of Health and Human Services/National Institutes of Health. (U.S.) (P20RR016461)American Heart Association (12FTF12080241)Charles Stark Draper Laboratory (CSDL-29414-005, CSDL-29889-001, CSDL-30716-005 & CSDL-30736-003

Heparanase Regulates Thrombosis in Vascular Injury and Stent-Induced Flow Disturbance

Objectives The purpose of this study was to examine the role of heparanase in controlling thrombosis following vascular injury or endovascular stenting. Background The use of endovascular stents are a common clinical intervention for the treatment of arteries occluded due to vascular disease. Both heparin and heparan sulfate are known to be potent inhibitors of thrombosis. Heparanase is the major enzyme that degrades heparan sulfate in mammalian cells. This study examined the role of heparanase in controlling thrombosis following vascular injury and stent-induced flow disturbance. Methods This study used mice overexpressing human heparanase and examined the time to thrombosis using a laser-induced arterial thrombosis model in combination with vascular injury. An ex vivo system was used to examine the formation of thrombus to stent-induced flow disturbance. Results In the absence of vascular injury, wild type and heparanase overexpressing (HPA Tg) mice had similar times to thrombosis in a laser-induced arterial thrombosis model. However, in the presence of vascular injury, the time to thrombosis was dramatically reduced in HPA Tg mice. An ex vivo system was used to flow blood from wild type and HPA Tg mice over stents and stented arterial segments from both animal types. These studies demonstrate markedly increased thromboses on stents with blood isolated from HPA Tg mice in comparison to blood from wild type animals. We found that blood from HPA Tg animals had markedly increased thrombosis when applied to stented arterial segments from either wild type or HPA Tg mice. Conclusions Taken together, this study's results indicate that heparanase is a powerful mediator of thrombosis in the context of vascular injury and stent-induced flow disturbance

Constraining OCT with Knowledge of Device Design Enables High Accuracy Hemodynamic Assessment of Endovascular Implants

Background: Stacking cross-sectional intravascular images permits three-dimensional rendering of endovascular implants, yet introduces between-frame uncertainties that limit characterization of device placement and the hemodynamic microenvironment. In a porcine coronary stent model, we demonstrate enhanced OCT reconstruction with preservation of between-frame features through fusion with angiography and a priori knowledge of stent design. Methods and Results: Strut positions were extracted from sequential OCT frames. Reconstruction with standard interpolation generated discontinuous stent structures. By computationally constraining interpolation to known stent skeletons fitted to 3D ‘clouds’ of OCT-Angio-derived struts, implant anatomy was resolved, accurately rendering features from implant diameter and curvature (n = 1 vessels, r2 = 0.91, 0.90, respectively) to individual strut-wall configurations (average displacement error ~15 μm). This framework facilitated hemodynamic simulation (n = 1 vessel), showing the critical importance of accurate anatomic rendering in characterizing both quantitative and basic qualitative flow patterns. Discontinuities with standard approaches systematically introduced noise and bias, poorly capturing regional flow effects. In contrast, the enhanced method preserved multi-scale (local strut to regional stent) flow interactions, demonstrating the impact of regional contexts in defining the hemodynamic consequence of local deployment errors. Conclusion: Fusion of planar angiography and knowledge of device design permits enhanced OCT image analysis of in situ tissue-device interactions. Given emerging interests in simulation-derived hemodynamic assessment as surrogate measures of biological risk, such fused modalities offer a new window into patient-specific implant environments.National Institutes of Health (U.S.) (NIH grant R01 GM-49039)American Heart Association (AHA FTF Award (12FTF12080241))Brazilian Society of Hemodynamics and Interventional Cardiology (Siguemituzo Arie Research Fellowship

Vascular Response to Experimental Stent Malapposition and Under-Expansion

Up to 80% of all endovascular stents have malapposed struts, and while some impose catastrophic events others are inconsequential. Thirteen stents were implanted in coronary arteries of seven healthy Yorkshire pigs, using specially-designed cuffed balloons inducing controlled stent malapposition and under-expansion. Optical coherence tomography (OCT) imaging confirmed that 25% of struts were malapposed (strut-wall distance <strut thickness) to variable extent (max. strut-wall distance malapposed group 0.51 ± 0.05 mm vs. apposed group 0.09 ± 0.05 mm, p = 2e−3). Imaging at follow-up revealed malapposition acutely resolved (<1% of struts remained malapposed at day 5), with strong correlation between lumen and the stent cross-sectional areas (slope = 0.86, p < 0.0001, R[superscript 2] = 0.94). OCT in three of the most significantly malapposed vessels at baseline showed high correlation of elastic lamina area and lumen area (R[superscript 2] = 0.96) suggesting all lumen loss was related to contraction of elastic lamina with negligible plaque/intimal hyperplasia growth. Simulation showed this vascular recoil could be partially explained by the non-uniform strain environment created from sub-optimal expansion of device and balloon, and the inability of stent support in the malapposed region to resist recoil. Malapposition as a result of stent under-expansion is resolved acutely in healthy normal arteries, suggesting existing animal models are limited in replicating clinically observed persistent stent malapposition.National Institutes of Health (U.S.) (R01 GM-49039)American Heart Association (FTF Award (12FTF12080241)