Predicting 1-year in-stent restenosis in superficial femoral arteries through multiscale computational modelling. Issue 201 (5th April 2023)
- Record Type:
- Journal Article
- Title:
- Predicting 1-year in-stent restenosis in superficial femoral arteries through multiscale computational modelling. Issue 201 (5th April 2023)
- Main Title:
- Predicting 1-year in-stent restenosis in superficial femoral arteries through multiscale computational modelling
- Authors:
- Corti, Anna
Migliavacca, Francesco
Berceli, Scott A.
Chiastra, Claudio - Abstract:
- Abstract : In-stent restenosis in superficial femoral arteries (SFAs) is a complex, multi-factorial and multiscale vascular adaptation process whose thorough understanding is still lacking. Multiscale computational agent-based modelling has recently emerged as a promising approach to decipher mechanobiological mechanisms driving the arterial response to the endovascular intervention. However, the long-term arterial response has never been investigated with this approach, although being of fundamental relevance. In this context, this study investigates the 1-year post-operative arterial wall remodelling in three patient-specific stented SFA lesions through a fully coupled multiscale agent-based modelling framework. The framework integrates the effects of local haemodynamics and monocyte gene expression data on cellular dynamics through a bi-directional coupling of computational fluid dynamics simulations with an agent-based model of cellular activities. The framework was calibrated on the follow-up data at 1 month and 6 months of one stented SFA lesion and then applied to the other two lesions. The calibrated framework successfully captured (i) the high lumen area reduction occurring within the first post-operative month and (ii) the stabilization of the median lumen area from 1-month to 1-year follow-ups in all the stented lesions, demonstrating the potentialities of the proposed approach for investigating patient-specific short- and long-term responses to endovascularAbstract : In-stent restenosis in superficial femoral arteries (SFAs) is a complex, multi-factorial and multiscale vascular adaptation process whose thorough understanding is still lacking. Multiscale computational agent-based modelling has recently emerged as a promising approach to decipher mechanobiological mechanisms driving the arterial response to the endovascular intervention. However, the long-term arterial response has never been investigated with this approach, although being of fundamental relevance. In this context, this study investigates the 1-year post-operative arterial wall remodelling in three patient-specific stented SFA lesions through a fully coupled multiscale agent-based modelling framework. The framework integrates the effects of local haemodynamics and monocyte gene expression data on cellular dynamics through a bi-directional coupling of computational fluid dynamics simulations with an agent-based model of cellular activities. The framework was calibrated on the follow-up data at 1 month and 6 months of one stented SFA lesion and then applied to the other two lesions. The calibrated framework successfully captured (i) the high lumen area reduction occurring within the first post-operative month and (ii) the stabilization of the median lumen area from 1-month to 1-year follow-ups in all the stented lesions, demonstrating the potentialities of the proposed approach for investigating patient-specific short- and long-term responses to endovascular interventions. … (more)
- Is Part Of:
- Journal of the Royal Society interface. Volume 20:Issue 201(2023)
- Journal:
- Journal of the Royal Society interface
- Issue:
- Volume 20:Issue 201(2023)
- Issue Display:
- Volume 20, Issue 201 (2023)
- Year:
- 2023
- Volume:
- 20
- Issue:
- 201
- Issue Sort Value:
- 2023-0020-0201-0000
- Page Start:
- Page End:
- Publication Date:
- 2023-04-05
- Subjects:
- lower-limb peripheral arteries -- in-stent restenosis -- computational modelling -- agent-based modelling -- computational fluid dynamics -- mechanobiology
Physical sciences -- Research -- Periodicals
Life sciences -- Research -- Periodicals
Interdisciplinary research -- Periodicals
570.5 - Journal URLs:
- https://royalsocietypublishing.org/journal/rsif ↗
- DOI:
- 10.1098/rsif.2022.0876 ↗
- Languages:
- English
- ISSNs:
- 1742-5689
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library STI - ELD Digital store
- Ingest File:
- 26790.xml