Identification of Hemodynamically Optimal Coronary Stent Designs Based on Vessel Caliber

Gundert, Timothy J.; Marsden, Alison L.; Yang, Weiguang; Marks, David; LaDisa, John F.

doi:10.1109/tbme.2012.2196275

Cited by 34 publications

(34 citation statements)

References 43 publications

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“…These tools have potential for clinical impact and have been used in optimizing coronary stent design [3] thrombotic risk stratification for Kawasaki disease [4, 5], analyzing the correlation between wall shear stress and atherosclerosis [6], and non-invasive assessment of fractional flow reserve [7]. …”

Section: Introductionmentioning

confidence: 99%

Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations

et al. 2017

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Atherosclerotic coronary artery disease, which can result in coronary artery stenosis, acute coronary artery occlusion, and eventually myocardial infarction, is a major cause of morbidity and mortality worldwide. Non-invasive characterization of coronary blood flow is important to improve understanding, prevention, and treatment of this disease. Computational simulations can now produce clinically relevant hemodynamic quantities using only non-invasive measurements, combining detailed three dimensional fluid mechanics with physiological models in a multiscale framework. These models, however, require specification of numerous input parameters and are typically tuned manually without accounting for uncertainty in the clinical data, hindering their application to large clinical studies. We propose an automatic, Bayesian, approach to parameter estimation based on adaptive Markov chain Monte Carlo sampling that assimilates non-invasive quantities commonly acquired in routine clinical care, quantifies the uncertainty in the estimated parameters and computes the confidence in local predicted hemodynamic indicators.

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Section: Introductionmentioning

confidence: 99%

Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations

et al. 2017

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“…For instance, previous studies have reported the optimization of stent strut geometry with the goal of minimizing blood flow disturbance in the arterial lumen [12–15], stresses in the stent itself [16], or stresses in the arterial wall [17]. Pant and collaborators recently reported the first attempt at including multiple design objectives and multiple physical phenomena in the optimization process with the use of a steady (time-independent) transport model to investigate the effect of DES geometric design on the homogeneity of drug distribution and its average concentration in the arterial wall [18, 19].…”

Section: Introductionmentioning

confidence: 99%

Optimization of Drug Delivery by Drug-Eluting Stents

et al. 2015

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Drug-eluting stents (DES), which release anti-proliferative drugs into the arterial wall in a controlled manner, have drastically reduced the rate of in-stent restenosis and revolutionized the treatment of atherosclerosis. However, late stent thrombosis remains a safety concern in DES, mainly due to delayed healing of the endothelial wound inflicted during DES implantation. We present a framework to optimize DES design such that restenosis is inhibited without affecting the endothelial healing process. To this end, we have developed a computational model of fluid flow and drug transport in stented arteries and have used this model to establish a metric for quantifying DES performance. The model takes into account the multi-layered structure of the arterial wall and incorporates a reversible binding model to describe drug interaction with the cells of the arterial wall. The model is coupled to a novel optimization algorithm that allows identification of optimal DES designs. We show that optimizing the period of drug release from DES and the initial drug concentration within the coating has a drastic effect on DES performance. Paclitaxel-eluting stents perform optimally by releasing their drug either very rapidly (within a few hours) or very slowly (over periods of several months up to one year) at concentrations considerably lower than current DES. In contrast, sirolimus-eluting stents perform optimally only when drug release is slow. The results offer explanations for recent trends in the development of DES and demonstrate the potential for large improvements in DES design relative to the current state of commercial devices.

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“…While regulatory requirements have certainly been met for these stents, their design attributes may not have been optimized in the strictest sense of the word. For example, we recently showed intrastrut hemodynamics are only optimized over a small range of diameters for one FDA‐approved stent studied using idealized models . Modifying the stent sizing matrix could extend this finding over a greater range of diameters and engineering metrics of interest .…”

Section: Introductionmentioning

confidence: 98%

Image‐based quantification of 3D morphology for bifurcations in the left coronary artery: Application to stent design

Ellwein

Marks

Migrino

et al. 2015

Cathet Cardio Intervent

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Background Improved strategies for stent-based treatment of coronary artery disease at bifurcations requires a greater understanding of artery morphology. Objective We developed a workflow to quantify morphology in the left main coronary (LMCA), left anterior descending (LAD), and left circumflex (LCX) artery bifurcations. Methods Computational models of each bifurcation were created for 55 patients using computed tomography images in 3D segmentation software. Metrics including cross-sectional area, length, eccentricity, taper, curvature, planarity, branching law parameters, and bifurcation angles were assessed using open-sources software and custom applications. Geometric characterization was performed by comparison of means, correlation and linear discriminant analysis (LDA). Results Differences between metrics suggest dedicated or multi-stent approaches should be tailored for each bifurcation. For example, the side branch of the LCX (i.e., obtuse marginal; OM) was longer than that of the LMCA (i.e. LCXprox) and LAD (i.e. first diagonal; D1). Bifurcation metrics for some locations (e.g. LMCA Finet ratio) provide results and confidence intervals agreeing with prior findings, while revised metric values are presented for others (e.g., LAD & LCX). LDA revealed several metrics that differentiate between artery locations (e.g., LMCA vs D1, LMCA vs OM, LADprox vs D1, and LCXprox vs D1). Conclusions These results provide a foundation for elucidating common parameters from healthy coronary arteries and could be leveraged in the future for treating diseased arteries. Collectively the current results may ultimately be used for design iterations that improve outcomes following implantation of future dedicated bifurcation stents.

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Identification of Hemodynamically Optimal Coronary Stent Designs Based on Vessel Caliber

Cited by 34 publications

References 43 publications

Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations

Automated tuning for parameter identification and uncertainty quantification in multi-scale coronary simulations

Optimization of Drug Delivery by Drug-Eluting Stents

Image‐based quantification of 3D morphology for bifurcations in the left coronary artery: Application to stent design

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