Modelling and optimisation of treatment parameters in high-dose-rate mono brachytherapy for localised prostate...

High-dose-rate mono brachytherapy (HDR-MB) is employed in the treatment of prostate carcinoma (CaP). As an ideal plan of CaP brachytherapy cannot be created, it is necessary to identify a reliable tool to optimise the parameters of HDR-MB. This paper applies a multilayer artificial neural network (MANN) and a genetic algorithm (GA) to optimise brachytherapy parameters based on an individual dose-volumetric analysis.

Patients with localised CaP of various risks were treated with HDR-MB. Consecutive levels of the biochemical control parameter (prostate specific antigen (PSA) nadir) have been collected after completion of HDR-MB in the range 2-9 years. The Kaplan-Meier regression analysis of biochemical-free survival (BFS) was applied. The clinical risk of recurrent CaP (RCaP), the therapy dose (TD), TD coverage index (CI_100%) and PSA nadir were modelled using the MANN and GA.

In the low-risk group, BFS was achieved in 100% of treated patients, while in the group of patients with high risk, BFS was achieved in 95.8% of treated patients. The MANN-GA model optimises a TD of 47.3 Gy and CI_100% of 1.14 as well as a TD of 50.4 Gy and CI_100% of 1.6 for the low-risk group and high-risk group, respectively, of localised CaP. The optimised PSA nadir was 0.047 and 0.25 ng cm^-3 for low-risk group and high-risk group, respectively.

The developed MANN-GA model presents a method for optimising the treatment parameters in radiation therapy, which could be a valuable tool in planning of the HDR-MB.