Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34286
Title: Agent‑based modelling and parameter sensitivity analysis with a finite‑element method for skin contraction
Authors: PENG, Qiyao 
VERMOLEN, Fred 
Issue Date: 2020
Publisher: 
Source: Biomechanics and Modeling in Mechanobiology, 19 (6) , p. 2525 -2551
Abstract: In this paper, we extend the model of wound healing by Boon et al. (J Biomech 49(8):1388-1401, 2016). In addition to explaining the model explicitly regarding every component, namely cells, signalling molecules and tissue bundles, we categorized fibroblasts as regular fibroblasts and myofibroblasts. We do so since it is widely documented that myofibroblasts play a significant role during wound healing and skin contraction and that they are the main phenotype of cells that is responsible for the permanent deformations. Furthermore, we carried out some sensitivity tests of the model by modifying certain parameter values, and we observe that the model shows some consistency with several biological phenomena. Using Monte Carlo simulations, we found that there is a significant strong positive correlation between the final wound area and the minimal wound area. The high correlation between the wound area after 4 days and the final/minimal wound area makes it possible for physicians to predict the most probable time evolution of the wound of the patient. However, the collagen density ratio at the time when the wound area reaches its equilibrium and minimum, cannot indicate the degree of wound contractions, whereas at the 4th day post-wounding, when the collagen is accumulating from null, there is a strong negative correlation between the area and the collagen density ratio. Further, under the circumstances that we modelled, the probability that patients will end up with 5% contraction is about 0.627.
Keywords: Wound healing;Wound contractions;Monte Carlo simulations;Finite-element method;Agent-based modelling
Document URI: http://hdl.handle.net/1942/34286
ISSN: 1617-7959
e-ISSN: 1617-7940
DOI: 10.1007/s10237-020-01354-z
ISI #: WOS:000545296200001
Rights: Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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