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Histology-guided mathematical model of tumor oxygenation: sensitivity analysis of physical and computational parameters.
Ojwang', Awino Maureiq E; Bazargan, Sarah; Johnson, Joseph O; Pilon-Thomas, Shari; Rejniak, Katarzyna A.
Afiliación
  • Ojwang' AME; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
  • Bazargan S; Department of Immunology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
  • Johnson JO; Analytic Microscopy Core, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
  • Pilon-Thomas S; Department of Immunology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
  • Rejniak KA; Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA.
bioRxiv ; 2024 Mar 10.
Article en En | MEDLINE | ID: mdl-38496532
ABSTRACT
A hybrid off-lattice agent-based model has been developed to reconstruct the tumor tissue oxygenation landscape based on histology images and simulated interactions between vasculature and cells with microenvironment metabolites. Here, we performed a robustness sensitivity analysis of that model's physical and computational parameters. We found that changes in the domain boundary conditions, the initial conditions, and the Michaelis constant are negligible and, thus, do not affect the model outputs. The model is also not sensitive to small perturbations of the vascular influx or the maximum consumption rate of oxygen. However, the model is sensitive to large perturbations of these parameters and changes in the tissue boundary condition, emphasizing an imperative aim to measure these parameters experimentally.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos