Patient-specific coronary angioplasty simulations -- a mixed-dimensional finite element modeling approach
<|reference_start|>Patient-specific coronary angioplasty simulations -- a mixed-dimensional finite element modeling approach: Coronary angioplasty with stent implantation is the most frequently used interventional treatment for coronary artery disease. However, reocclusion within the stent, referred to as in-stent restenosis, occurs in up to 10% of lesions. It is widely accepted that mechanical loads on the vessel wall strongly affect adaptive and maladaptive mechanisms. Yet, the role of procedural and lesion-specific influence on restenosis risk remains understudied. Computational modeling of the stenting procedure can provide new mechanistic insights, such as local stresses, that play a significant role in tissue growth and remodeling. Previous simulation studies often featured simplified artery and stent geometries and cannot be applied to real-world examples. Realistic simulations were computationally expensive since they featured fully resolved stenting device models. The aim of this work is to develop and present a mixed-dimensional formulation to simulate the patient-specific stenting procedure with a reduced-dimensional beam model for the stent and 3D models for the artery. In addition to presenting the numerical approach, we apply it to realistic cases to study the intervention's mechanical effect on the artery and correlate the findings with potential high-risk locations for in-stent restenosis. We found that high artery wall stresses develop during the coronary intervention in severely stenosed areas and at the stent boundaries. Herewith, we lay the groundwork for further studies towards preventing in-stent restenosis after coronary angioplasty.<|reference_end|>
@article{datz2024patient-specific,
    title={Patient-specific coronary angioplasty simulations -- a mixed-dimensional
  finite element modeling approach},
    author={Janina C. Datz, Ivo Steinbrecher, Christoph Meier, Nora Hagmeyer,
  Leif-Christopher Engel, Alexander Popp, Martin R. Pfaller, Heribert
  Schunkert, Wolfgang A. Wall},
    journal={arXiv preprint arXiv:2407.13276},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.13276},
    primaryClass={cs.CE}
}