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  Exploring chronomodulated radiotherapy strategies in a chaotic population model

Ramírez-Ávila, G. M., Kurths, J., Gonze, D., Dupont, G. (2023): Exploring chronomodulated radiotherapy strategies in a chaotic population model. - Chaos, Solitons and Fractals, 173, 113743.
https://doi.org/10.1016/j.chaos.2023.113743

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 Creators:
Ramírez-Ávila, Gonzalo Marcelo1, Author
Kurths, Jürgen2, Author              
Gonze, Didier1, Author
Dupont, Geneviève1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: We present a simple nonlinear model describing the population dynamics of cancerous, healthy, and effector cells submitted to ionizing radiation. We examine the situations in which intermittently high doses of radiation affect the cells as it occurs in radiotherapy. We characterize the effect of various irradiation parameters, such as the total delivered dose for a given standard dose rate and the number of treatment sessions seeking situations that optimize normal cells survival. In other words, we are interested in enhancing the effectiveness of a radiotherapy treatment by adjusting the temporal pattern of the dose deliverance through an exhaustive dynamical characterization of the system. This includes the study of the parameter planes, the populations’ dynamical behavior going from fixed points to chaotic oscillations, and the basins of attraction. This work leads to counter-intuitive predictions and constitutes a step towards a model of chronomodulated radiotherapy.

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Language(s): eng - English
 Dates: 2023-07-012023-08-01
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.chaos.2023.113743
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Health
Research topic keyword: Nonlinear Dynamics
Model / method: Nonlinear Data Analysis
 Degree: -

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Title: Chaos, Solitons and Fractals
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 173 Sequence Number: 113743 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/190702
Publisher: Elsevier