In silico reproduction of the pathophysiology of in-stent restenosis

TL;DR

This paper presents a comprehensive computational framework that simulates the complex biological, chemical, and mechanical processes involved in in-stent restenosis, aiming to improve patient-specific diagnosis and treatment planning.

Contribution

It introduces an integrated in silico model capturing multiple physical phenomena related to restenosis, advancing computational tools for personalized clinical decision-making.

Findings

Effective simulation of chemical, mechanical, and biological interactions in restenosis

Development of computational methods for hemodynamic indicator extraction

Facilitation of computer-assisted clinical procedures

Abstract

The occurrence of in-stent restenosis following percutaneous coronary intervention highlights the need for the creation of computational tools that can extract pathophysiological insights and optimize interventional procedures on a patient-specific basis. In light of this, a comprehensive framework encompassing multiple physical phenomena is introduced in this work. This framework effectively captures the intricate interplay of chemical, mechanical, and biological factors. In addition, computational approaches for the extraction of hemodynamic indicators that modulate the severity of the restenotic process are devised. Thus, this marks a significant stride towards facilitating computer-assisted clinical methodologies.