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In-Stent Restenosis is a recurrence of coronary artery narrowing due tovascular injury caused by balloon dilation and stent placement. It may lead tothe relapse of angina symptoms or to an acute coronary syndrome. An uncertaintyquantification of a model for In-Stent Restenosis with four uncertainparameters (endothelium regeneration time, the threshold strain for smoothmuscle cells bond breaking, blood flow velocity and the percentage offenestration in the internal elastic lamina) is presented. Two quantities ofinterest were studied, namely the average cross-sectional area and the maximumrelative area loss in a vessel. Due to the computational intensity of the modeland the number of evaluations required in the uncertainty quantification, asurrogate model, based on Gaussian process regression with proper orthogonaldecomposition, was developed which subsequently replaced the original In-StentRestenosis model in the uncertainty quantification. A detailed analysis of theuncertainty propagation and sensitivity analysis is presented. Around 11% and16% of uncertainty are observed on the average cross-sectional area and maximumrelative area loss respectively, and the uncertainty estimates show that ahigher fenestration mainly determines uncertainty in the neointimal growth atthe initial stage of the process. On the other hand, the uncertainty in bloodflow velocity and endothelium regeneration time mainly determine theuncertainty in the quantities of interest at the later, clinically relevantstages of the restenosis process. The uncertainty in the threshold strain isrelatively small compared to the other uncertain parameters.

Uncertainty quantification of a three-dimensional in-stent restenosis model with surrogate modelling