Print Email Facebook Twitter In silico exploration of post-burn contraction using uncertainty quantification Title In silico exploration of post-burn contraction using uncertainty quantification Author Egberts, G. (TU Delft Numerical Analysis) Contributor Vuik, Cornelis (promotor) Vermolen, F.J. (promotor) van Zuijlen, Paul P.M. (promotor) Degree granting institution Delft University of Technology Corporate name Delft University of Technology Date 2023-09-18 Abstract 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... Subject Skin BurnsPost-burn ScarsPost-burn ContractionContracture Formation, MorphoelasticityFibroblastsMyofibroblasts,Cell ProliferationSignaling MoleculesCollagen,Dermal DisplacementsDermal StrainsMoving-gridFinite Element MethodRelative Scar/Wound AreaStrain EnergyStability AnalysisSensitivity AnalysisFeasibility StudyArtificial IntelligenceMachine LearningFeed-forward Neural NetworkMedical ApplicationMonte Carlo Simulations To reference this document use: https://doi.org/10.4233/uuid:678bd7d9-8aac-4644-b058-2aa8000d7811 ISBN 978-94-6384-463-5 Embargo date 2023-09-18 Part of collection Institutional Repository Document type doctoral thesis Rights © 2023 G. Egberts Files PDF Dissertation_Egberts.pdf 12.9 MB Close viewer /islandora/object/uuid:678bd7d9-8aac-4644-b058-2aa8000d7811/datastream/OBJ/view