2021/08/08 by Szabolcs Suveges, Suveges, Szabolcs, Kismet Hossain-Ibrahim +7 · 2 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · #Advanced Mathematical Modeling in Engineering #Caveolin-1 and cellular processes #Dynamical Systems (math.DS) #FOS: Mathematics #Mathematical Biology Tumor Growth
paper · pdf · doi:10.48550/arxiv.2108.03737
openalex publication_date 2021/08/08 · openalex created_date 2022/07/25 · openalex updated_date 2026/07/28
Brain-related experiments are limited by nature, and so biological insights\nare often restricted or absent. This is particularly problematic in the context\nof brain cancers, which have very poor survival rates. To generate and test new\nbiological hypotheses, researchers started using mathematical models that can\nsimulate tumour evolution. However, most of these models focus on single-scale\n2D cell dynamics, and cannot capture the complex multi-scale tumour invasion\npatterns in 3D brains. A particular role in these invasion patterns is likely\nplayed by the distribution of micro-fibres. To investigate explicitly the role\nof brain micro-fibres in the 3D invading tumours, in this study we extend a\npreviously-introduced 2D multi-scale moving-boundary framework to take into\naccount 3D multi-scale tumour dynamics. T1 weighted and DTI scans are used as\ninitial conditions for our model, and to parametrise the diffusion tensor.\nNumerical results show that including an anisotropic diffusion term may lead in\nsome cases (for specific micro-fibre distributions) to significant changes in\ntumour morphology, while in other cases it has no effect. This may be caused by\nthe underlying brain structure and its microscopic fibre representation, which\nseems to influence cancer-invasion patterns through the underlying\ncell-adhesion process that overshadows the diffusion process.\n