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Glioma growth modeling based on the effect of vital nutrients and metabolic products

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Abstract

Glioma brain tumors exhibit considerably aggressive behavior leading to high mortality rates. Mathematical modeling of tumor growth aims to explore the interactions between glioma cells and tissue microenvironment, which affect tumor evolution. Leveraging this concept, we present a three-dimensional model of glioma spatio-temporal evolution based on existing continuum approaches, yet incorporating novel factors of the phenomenon. The proposed model involves the interactions between different tumor cell phenotypes and their microenvironment, investigating how tumor growth is affected by complex biological exchanges. It focuses on the separate and combined effect of vital nutrients and cellular wastes on tumor expansion, leading to the formation of cell populations with different metabolic, proliferative, and diffusive profiles. Several simulations were performed on a virtual and a real glioma, using combinations of proliferation and diffusion rates for different evolution times. The model results were validated on a glioma model available in the literature and a real case of tumor progression. The experimental observations indicate that our model estimates quite satisfactorily the expansion of each region and the overall tumor growth. Based on the individual results, the proposed model may provide an important research tool for patient-specific simulation of different tumor evolution scenarios and reliable estimation of glioma evolution.

Outline of the mathematical model functionality and application to glioma growth with indicative results

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Funding

This work is supported by the ECOSCALE project (grant agreement 671632) funded by the European Commission under the H2020 Programme.

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Authors and Affiliations

  1. Digital Image and Signal Processing Laboratory, School of Electrical and Computer Engineering, Technical University of Crete, University Campus, Akrotiri, Chania, 73100, Crete, Greece

    Maria Papadogiorgaki

  2. Department of Oncology, General Hospital of Chania “Agios Georgios”, Mournies, Chania, 73300, Crete, Greece

    Panagiotis Koliou

  3. Digital Image and Signal Processing Laboratory, School of Electrical and Computer Engineering, Technical University of Crete, Polytechnioupolis, Kounopidiana Campus, Chania, 73100, Crete, Greece

    Michalis E. Zervakis

Authors
  1. Maria Papadogiorgaki
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  2. Panagiotis Koliou
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  3. Michalis E. Zervakis
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Correspondence to Maria Papadogiorgaki.

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Papadogiorgaki, M., Koliou, P. & Zervakis, M.E. Glioma growth modeling based on the effect of vital nutrients and metabolic products. Med Biol Eng Comput 56, 1683–1697 (2018). https://doi.org/10.1007/s11517-018-1809-0

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