Tumour growth: An approach to calibrate parameters of a multiphase porous media model based on in vitro observations of Neuroblastoma spheroid growth in a hydrogel microenvironment

Silvia Hervas-Raluy, Barbara Wirthl, Pedro E. Guerrero, Gil Robalo Rei, Jonas Nitzler, Esther Coronado, Jaime Font de Mora Sainz, Bernhard A. Schrefler, Maria Jose Gomez-Benito, Jose Manuel Garcia-Aznar, Wolfgang A. Wall

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

To unravel processes that lead to the growth of solid tumours, it is necessary to link knowledge of cancer biology with the physical properties of the tumour and its interaction with the surrounding microenvironment. Our understanding of the underlying mechanisms is however still imprecise. We therefore developed computational physics-based models, which incorporate the interaction of the tumour with its surroundings based on the theory of porous media. However, the experimental validation of such models represents a challenge to its clinical use as a prognostic tool. This study combines a physics-based model with in vitro experiments based on microfluidic devices used to mimic a three-dimensional tumour microenvironment. By conducting a global sensitivity analysis, we identify the most influential input parameters and infer their posterior distribution based on Bayesian calibration. The resulting probability density is in agreement with the scattering of the experimental data and thus validates the proposed workflow. This study demonstrates the huge challenges associated with determining precise parameters with usually only limited data for such complex processes and models, but also demonstrates in general how to indirectly characterise the mechanical properties of neuroblastoma spheroids that cannot feasibly be measured experimentally.

Original languageEnglish (US)
Article number106895
Pages (from-to)106895
JournalComputers in Biology and Medicine
Volume159
DOIs
StatePublished - Jun 2023

Keywords

  • Bayesian calibration
  • Gaussian processes
  • Global sensitivity analysis
  • Multiphase model
  • Neuroblastoma spheroids
  • Hydrogels
  • Humans
  • Bayes Theorem
  • Tumor Microenvironment
  • Porosity
  • Neuroblastoma

ASJC Scopus subject areas

  • Health Informatics
  • Computer Science Applications

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