A mathematical aid decision tool for RT planning

TL;DR

This paper introduces a mathematical decision tool that optimizes radiation doses in radiotherapy by extending a population dynamics model to variable session protocols, aiding treatment planning and resource management.

Contribution

It develops an extended model allowing variable session numbers and doses, enabling personalized and optimized radiotherapy treatment planning.

Findings

Optimized radiation dose per session can be determined for different protocols.

The model supports adjusting treatment plans based on tissue tolerance and facility capacity.

It offers a practical tool for RT service management and personalized treatment optimization.

Abstract

It is possible to find the optimized radiation dose per session for a radiotherapy (RT) treatment, using a population dynamics model. This has already been done in a previous work for a protocol with 30 sessions and a fixed dose per session. Extending this model to other protocols, with a variable number of sessions, we could change the radiation dosage while keeping the success probability of treatment at its maximum value. This could help the RT oncology service managers to plan the sequence of patients and treatments adapting it to the facilities of the oncology service. Besides, if tumor surrounding tissue is not able to afford a high dosage, it could be useful to extend the treatment to a higher number of low dose radiation sessions, keeping an optimal treatment.