Dongwei Ye, Pavel Zun, Valeria Krzhizhanovskaya and Alfons G. Hoekstra have published a new paper on the uncertainty quantification of a 3D in-stent restenosis model in the Journal of the Royal Society Interface.

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. With the powerful statistical tools, we investigated the uncertainty propagation of four biological uncertain parameters through our 3D In-Stent Restenosis model. Two quantities of interest were studied, namely the average cross-sectional area and the maximum relative area loss in a vessel. To further reduce the computational cost, a data-driven surrogate model was developed and subsequently applied in the uncertainty quantification. A detailed analysis of the uncertainty propagation and sensitivity analysis is presented.

For more details see the publication here.