Radiotherapy Effects on Diffuse Low-Grade Gliomas: Confronting Theory With Clinical Data

TL;DR

This study introduces a new biologically motivated model for the growth and treatment response of diffuse low-grade gliomas, validated with clinical data, and provides insights into tumor age and growth patterns.

Contribution

The paper proposes a novel, simple tumor growth model that addresses previous shortcomings and fits clinical data well, also estimating tumor age from early development.

Findings

Model fits clinical data for all patients.

Estimated tumor age suggests gliomas often originate in late teenage years.

Analytical expression explains observed growth correlations.

Abstract

Diffuse low grade gliomas are slowly growing tumors that always recur after treatment. In this paper, we revisit the modeling of the tumor radius evolution 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 it with clinical data consisting in time-series of tumor radius for 43 patient records, using a stochastic optimization technique and obtain very good fits in all the cases. Since our model describes the evolution of the 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 the information from the data, we build confidence intervals for the tumor birth age and confirm the fact that low-grade glioma 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.