The effect of radiotherapy on diffuse low-grade gliomas evolution: Confronting theory with clinical data

  • Léo Adenis
  • , Stéphane Plaszczynski
  • , Basile Grammaticos
  • , Johan Pallud
  • , Mathilde Badoual

Research output: Contribution to journalArticlepeer-review

Abstract

Diffuse low-grade gliomas are slowly growing tumors that always recur after treatment. In this paper, we revisit the modeling of the evolution of the tumor radius before and after the radiotherapy process and propose a novel model that is simple yet biologically motivated and that remedies some shortcomings of previously proposed ones. We confront this with clinical data consisting of time series of tumor radii from 43 patient records by using a stochastic optimization technique and obtain very good fits in all cases. Since our model describes the evolution of a tumor from the very first glioma cell, it gives access to the possible age of the tumor. Using the technique of profile likelihood to extract all of the information from the data, we build confidence intervals for the tumor birth age and confirm the fact that low-grade gliomas seem to appear in the late teenage years. Moreover, an approximate analytical expression of the temporal evolution of the tumor radius allows us to explain the correlations observed in the data.

Original languageEnglish
Article number818
JournalJournal of Personalized Medicine
Volume11
Issue number8
DOIs
Publication statusPublished - 1 Aug 2021
Externally publishedYes

Keywords

  • Data analysis
  • Gliomas
  • Mathematical modeling
  • Optimization
  • Radiotherapy

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