  In-Stent Restenosis is a recurrence of coronary artery narrowing due to
vascular injury caused by balloon dilation and stent placement. It may lead to
the relapse of angina symptoms or to an acute coronary syndrome. An uncertainty
quantification of a model for In-Stent Restenosis with four uncertain
parameters (endothelium regeneration time, the threshold strain for smooth
muscle cells bond breaking, blood flow velocity and the percentage of
fenestration in the internal elastic lamina) is presented. Two quantities of
interest were studied, namely the average cross-sectional area and the maximum
relative area loss in a vessel. Due to the computational intensity of the model
and the number of evaluations required in the uncertainty quantification, a
surrogate model, based on Gaussian process regression with proper orthogonal
decomposition, was developed which subsequently replaced the original In-Stent
Restenosis model in the uncertainty quantification. A detailed analysis of the
uncertainty propagation and sensitivity analysis is presented. Around 11% and
16% of uncertainty are observed on the average cross-sectional area and maximum
relative area loss respectively, and the uncertainty estimates show that a
higher fenestration mainly determines uncertainty in the neointimal growth at
the initial stage of the process. On the other hand, the uncertainty in blood
flow velocity and endothelium regeneration time mainly determine the
uncertainty in the quantities of interest at the later, clinically relevant
stages of the restenosis process. The uncertainty in the threshold strain is
relatively small compared to the other uncertain parameters.
