Endothelial repair process and its relevance to longitudinal neointimal tissue patterns: comparing histology with in silico modelling

Abstract

Re-establishing a functional endothelium following endovascular treatment is an important factor in arresting neointimal proliferation. In this study, both histology (in vivo) and computational simulations (in silico) are used to evaluate neointimal growth patterns within coronary arteries along the axial direction of the stent. Comparison of the growth configurations in vivo and in silico was undertaken to identify candidate mechanisms for endothelial repair. Stent, lumen and neointimal areas were measured from histological sections obtained from eight right coronary stented porcine arteries. Two reendothelialization scenarios (endothelial cell (EC) random seeding and EC growth from proximal and distal ends) were implemented in silico to evaluate their influence on the morphology of the simulated lesions. Subject to the assumptions made in the current simulations, comparison between in vivo and in silico results suggests that endothelial growth does not occur from the proximal and distal ends alone, but is more consistent with the assumption of a random seeding process. This may occur either from the patches of endothelium which survive following stent implantation or from attachment of circulating endothelial progenitor cells.

Uncertainty Quantification of a Multiscale Model for In-Stent Restenosis

“…At each step of the model, each endothelium-free SMC becomes covered by functional endothelium with a time-varying probability calculated to achieve a certain coverage scenario. 29 Figure 1c shows the model state after some growth. In this example, to the left of the top strut, the endothelium has recovered quickly and proliferation has nearly stopped.…”

“…5,31 Epistemic Uncertainty in the Model For our uncertainty quantification and sensitivity analysis of the ISR2D model, we consider the uncertainty in three input parameters (Table 1). Stent deployment depth and endothelium regeneration time were shown to strongly affect simulated neointimal area by Tahir et al, 29 and were therefore included. Additionally, we included blood flow velocity, because its effect on the behavior of the model has not yet been evaluated, and because of the potentially interesting interaction with the endothelium regeneration time.…”

“…Here, we study our two-dimensional version of the ISR model. 5,29,30 We do this to provide a proofof-concept, using a model that is computationally relatively cheap, in preparation for a more in-depth study of our later, more physiological and more computationally expensive three-dimensional ISR model. 34 Our ultimate goal was to access the model result sensitivity to the uncertainties in the inputs and stochastic parameters, in order to be aware of the result uncertainty and the inputs which cause a greater effect on it.…”

An in silico study on the role of smooth muscle cell migration in neointimal formation after coronary stenting

“…As endothelium is usually damaged or dysfunctional during the early days, shear stresses occurring from the blood flow are particularly important during the middle and later phases of ISR progression, where they mitigate ISR growth [22][23][24]. The effect of flow shear stresses on the growth and tissue morphology of ISR afflicted vessel walls has already been highlighted in our previous studies using coupled ISR models [10,16]. However, the early phases of ISR that we focus on here seem to be mainly dependent on the extent of injury to the vascular wall [3].…”

An investigation of damage mechanisms in mechanobiological models of in-stent restenosis

“…Another experimental study investigating the origin of ECs in the healed region post-stenting revealed that these cells proliferated from healthy endothelium proximal and distal to the stent, and originated from bone marrow derived cells [35]. A computational study by Tahir et al [36] modelled two mechanisms of reendothelialisation; growth from proximal and distal ends and random seeding in the denuded region. Results from these simulations showed that different patterns of neointimal growth and area are predicted by these two mechanisms.…”