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Almond Mushroom, ABM · 2025 · Journal Article

Low relevance

Plaque heterogeneity influences in-stent restenosis following drug-eluting stent implantation: Insights from patient-specific multiscale modelling.

Agaricus blazei

Immune support
SpeciesAlmond Mushroom, ABM
JournalJournal of biomechanics
Year2025

Key points

  • In-stent restenosis represents a major cause of failure of percutaneous coronary intervention with drug-eluting stent implantation
  • Computational multiscale models have recently emerged as powerful tools for investigating the mechanobiological mechanisms underlying vascular adaptation processes during in-stent restenosis
  • However, to date, the interplay between intervention-induced inflammation, drug delivery and drug retention has been under-investigated
  • The analysis revealed three significant findings: (i) calcifications substantially impeded drug transport, resulting in drug-depleted regions and reduced stent efficacy; (ii) by impacting drug transport, variations in plaque composition influenced arterial wall response, with the fully-calcific scenario showing the greatest lumen area reduction; (iii) the impact of different drug receptor saturation conditions (obtained with different plaque compositions) was particularly evident under conditions of persistent inflammatory state
  • This study represents a significant advancement in multiscale modelling of in-stent restenosis following drug-eluting stent implantation
  • The results obtained provided deeper insights into the complex interactions among patient-specific plaque composition, inflammation and drug retention, suggesting a patient-specific management of the intervention, particularly in cases of complex disease

Metadata-grounded summary

Citation abstract

In-stent restenosis represents a major cause of failure of percutaneous coronary intervention with drug-eluting stent implantation. Computational multiscale models have recently emerged as powerful tools for investigating the mechanobiological mechanisms underlying vascular adaptation processes during in-stent restenosis. However, to date, the interplay between intervention-induced inflammation, drug delivery and drug retention has been under-investigated. Here, an original patient-specific multiscale agent-based modelling framework was developed to investigate the interplay between drug release, plaque composition and intervention-induced inflammation on in-stent restenosis following drug-eluting stent implantation. The framework integrated a finite element simulation of stent expansion, with a drug transport simulation and an agent-based model of cellular dynamics. A patient-specific coronary cross-section with heterogeneous diseased tissue was considered and rigorously analyzed through a variety of scenarios, including different plaque compositions and different inflammatory responses. The analysis revealed three significant findings: (i) calcifications substantially impeded drug transport, resulting in drug-depleted regions and reduced stent efficacy; (ii) by impacting drug transport, variations in plaque composition influenced arterial wall response, with the fully-calcific scenario showing the greatest lumen area reduction; (iii) the impact of different drug receptor saturation conditions (obtained with different plaque compositions) was particularly evident under conditions of persistent inflammatory state. This study represents a significant advancement in multiscale modelling of in-stent restenosis following drug-eluting stent implantation. The results obtained provided deeper insights into the complex interactions among patient-specific plaque composition, inflammation and drug retention, suggesting a patient-specific management of the intervention, particularly in cases of complex disease.

Citation

Corti A, Dal Ferro L, Akyildiz AC, Migliavacca F, McGinty S, Chiastra C (2025). Plaque heterogeneity influences in-stent restenosis following drug-eluting stent implantation: Insights from patient-specific multiscale modelling. Journal of biomechanics https://doi.org/10.1016/j.jbiomech.2024.112485 PMID: 39736224

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