TY - JOUR
T1 - A predictive multiscale model of in-stent restenosis in femoral arteries
T2 - linking haemodynamics and gene expression with an agent-based model of cellular dynamics
AU - Corti, Anna
AU - Colombo, Monika
AU - Rozowsky, Jared M.
AU - Casarin, Stefano
AU - He, Yong
AU - Carbonaro, Dario
AU - Migliavacca, Francesco
AU - Matas, Jose F.Rodriguez
AU - Berceli, Scott A.
AU - Chiastra, Claudio
N1 - Funding Information:
This work has been supported by Fondazione Cariplo, Italy (grant no. 2017-0792, TIME). F.M. and C.C. have been also partially supported by the Italian Ministry of Education, University and Research (FISR2019_03221, CECOMES).
Publisher Copyright:
© 2022 The Author(s).
PY - 2022
Y1 - 2022
N2 - In-stent restenosis (ISR) is a maladaptive inflammatory-driven response of femoral arteries to percutaneous transluminal angioplasty and stent deployment, leading to lumen re-narrowing as consequence of excessive cellular proliferative and synthetic activities. A thorough understanding of the underlying mechanobiological factors contributing to ISR is still lacking. Computational multiscale models integrating both continuous- and agent-based approaches have been identified as promising tools to capture key aspects of the complex network of events encompassing molecular, cellular and tissue response to the intervention. In this regard, this work presents a multiscale framework integrating the effects of local haemodynamics and monocyte gene expression data on cellular dynamics to simulate ISR mechanobiological processes in a patient-specific model of stented superficial femoral artery. The framework is based on the coupling of computational fluid dynamics simulations (haemodynamics module) with an agent-based model (ABM) of cellular activities (tissue remodelling module). Sensitivity analysis and surrogate modelling combined with genetic algorithm optimization were adopted to explore the model behaviour and calibrate the ABM parameters. The proposed framework successfully described the patient lumen area reduction from baseline to one-month follow-up, demonstrating the potential capabilities of this approach in predicting the short-term arterial response to the endovascular procedure.
AB - In-stent restenosis (ISR) is a maladaptive inflammatory-driven response of femoral arteries to percutaneous transluminal angioplasty and stent deployment, leading to lumen re-narrowing as consequence of excessive cellular proliferative and synthetic activities. A thorough understanding of the underlying mechanobiological factors contributing to ISR is still lacking. Computational multiscale models integrating both continuous- and agent-based approaches have been identified as promising tools to capture key aspects of the complex network of events encompassing molecular, cellular and tissue response to the intervention. In this regard, this work presents a multiscale framework integrating the effects of local haemodynamics and monocyte gene expression data on cellular dynamics to simulate ISR mechanobiological processes in a patient-specific model of stented superficial femoral artery. The framework is based on the coupling of computational fluid dynamics simulations (haemodynamics module) with an agent-based model (ABM) of cellular activities (tissue remodelling module). Sensitivity analysis and surrogate modelling combined with genetic algorithm optimization were adopted to explore the model behaviour and calibrate the ABM parameters. The proposed framework successfully described the patient lumen area reduction from baseline to one-month follow-up, demonstrating the potential capabilities of this approach in predicting the short-term arterial response to the endovascular procedure.
KW - agent-based modelling
KW - computational fluid dynamics
KW - lower-limb peripheral arteries
KW - mechanobiology
KW - multiscale modelling
KW - restenosis
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U2 - 10.1098/rsif.2021.0871
DO - 10.1098/rsif.2021.0871
M3 - Article
C2 - 35350882
AN - SCOPUS:85127274601
VL - 19
JO - Journal of the Royal Society Interface
JF - Journal of the Royal Society Interface
SN - 1742-5689
IS - 188
M1 - 20210871
ER -