In silico exploration of post-burn contraction using uncertainty quantification

In silico exploration of post-burn contraction using uncertainty quantification

Egberts, G. (TU Delft Numerical Analysis)

Vuik, Cornelis (promotor)
Vermolen, F.J. (promotor)
van Zuijlen, Paul P.M. (promotor)

Delft University of Technology

2023-09-18

Burns can make patients’ lives quite miserable. Apart from prominent and thickened, or hypertrophic, scars, the skin may be characterized by contraction. When this contraction is so severe that the patient loses joint mobility, it is called contracture. Then a patient may have difficulties with sports or other daily activities. The consequence can be an enormous psychosocial burden for the patient. Understanding contraction mechanisms is essential to improve and optimize the treatment of contractures. This understanding can arise from clinical (in vivo) and experimental (in vitro) observations but can also be explored using mathematical models (in silico). Mathematical models describe quantitative relations and can explain specific trends and make predictions. Further, in silico models forman alternative for animal experiments. One such mathematical model is the Biomorphoelastic model for post-burn contraction [1]. This model arises from conservation laws expressed in partial differential equations on a continuous (macro) scale. We study this model’s one- and twodimensional counterparts...

Skin Burns
Post-burn Scars
Post-burn Contraction
Contracture Formation, Morphoelasticity
Fibroblasts
Myofibroblasts,
Cell Proliferation
Signaling Molecules
Collagen,
Dermal Displacements
Dermal Strains
Moving-grid
Finite Element Method
Relative Scar/Wound Area
Strain Energy
Stability Analysis
Sensitivity Analysis
Feasibility Study
Artificial Intelligence
Machine Learning
Feed-forward Neural Network
Medical Application
Monte Carlo Simulations

https://doi.org/10.4233/uuid:678bd7d9-8aac-4644-b058-2aa8000d7811

978-94-6384-463-5

2023-09-18

Institutional Repository

doctoral thesis

© 2023 G. Egberts