FOTELP-VOX-GA: Integrating Genetic Algorithms into Monte Carlo Dose Calculation for Prostate Cancer

Abstract

Achieving optimal dose distribution is essential in prostate radiotherapy, particularly with hypofractionated regimens. In this study, we present an AI-assisted dose optimisation framework, FOTELP-VOX-GA, integrating Monte Carlo simulation with a Genetic Algorithm. Comparing to a patient-specific VMAT (Volumetric Modulated Arc Therapy) plan, the method yielded dose estimates for the iliac bones, showing lower mean doses (1977.51 cGy) than those calculated by the Eclipse TPS (2092.1 cGy and 2085.3 cGy). The genetic optimization process achieved clinically acceptable deviations (2–10%) from prescribed doses to the tumor and surrounding tissues. These findings highlight the value of FOTELP-VOX-GA in supporting safe and personalized radiotherapy planning.