Inference on an interacting diffusion system with application to in vitro glioblastoma migration
Journal article, 2024

Glioblastoma multiforme is a highly aggressive form of brain cancer, with a median survival time for diagnosed patients of 15 months. Treatment of this cancer is typically a combination of radiation, chemotherapy and surgical removal of the tumour. However, the highly invasive and diffuse nature of glioblastoma makes surgical intrusions difficult, and the diffusive properties of glioblastoma are poorly understood. In this paper, we introduce a stochastic interacting particle system as a model of in vitro glioblastoma migration, along with a maximum likelihood-algorithm designed for inference using microscopy imaging data. The inference method is evaluated on in silico simulation of cancer cell migration, and then applied to a real data set. We find that the inference method performs with a high degree of accuracy on the in silico data, and achieve promising results given the in vitro data set.

glioblastoma

diffusion

statistical inference

agent based modelling

mathematical biology

Author

Gustav Lindwall

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Philip Gerlee

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

Mathematical Medicine and Biology

1477-8599 (ISSN) 14778602 (eISSN)

Vol. 41 3

Focus on glioblastoma: using patient-derived cell lines to decipher tumour expansion and evaluate new treatments

Swedish Foundation for Strategic Research (SSF) (SB16-0066), 2019-01-01 -- 2021-12-31.

Subject Categories

Cell Biology

Computational Mathematics

Probability Theory and Statistics

Areas of Advance

Health Engineering

DOI

10.1093/imammb/dqae010

More information

Created

12/12/2024