Optimization of Radiation Therapy Fractionation Schedules in the Presence of Tumor Repopulation

TL;DR

This paper develops a dynamic programming model to optimize radiation therapy schedules considering tumor repopulation, showing that faster tumor growth favors shorter treatments and larger doses later in therapy.

Contribution

It introduces a novel optimization framework incorporating tumor growth dynamics to improve radiation therapy fractionation schedules.

Findings

Faster tumor growth leads to shorter treatment durations.

Accelerated repopulation suggests increasing dose fractions over time.

Numerical results show potential for improved treatment effectiveness.

Abstract

We analyze the effect of tumor repopulation on optimal dose delivery in radiation therapy. We are primarily motivated by accelerated tumor repopulation towards the end of radiation treatment, which is believed to play a role in treatment failure for some tumor sites. A dynamic programming framework is developed to determine an optimal fractionation scheme based on a model of cell kill due to radiation and tumor growth in between treatment days. We find that faster tumor growth suggests shorter overall treatment duration. In addition, the presence of accelerated repopulation suggests larger dose fractions later in the treatment to compensate for the increased tumor proliferation. We prove that the optimal dose fractions are increasing over time. Numerical simulations indicate potential for improvement in treatment effectiveness.