In silico reproduction of the pathophysiology of in-stent restenosis

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.