ABSTRACT
AIMS: Interstitial high-dose-rate brachytherapy (HDR-BT) is an effective therapy modality for patients with localized prostate carcinoma. The objectives of the study were to optimise the therapy regime variables using two models: response surface methodology (RSM) and artificial neural network (ANN). MATERIALS AND METHODS: Thirty-one studies with 5651 patients were included (2078 patients presented as low-risk, 3077 patients with intermediate-risk, and 496 patients with high-risk). A comparison of these therapy schedules was carried out using an effective biologically effective dose (BEDef) that was calculated assuming the number of treatment days and dose (D) per day. The modelling and optimization of therapy parameters (BEDef and risk level) in order to obtain the maximum biochemical free survival (BFS) were carried out by the RSM and ANN models. RESULTS: An optimal treatment schedule (BFS = 97%) for patients presented with low-risk biochemical recurrence would be D = 26 Gy applied in one application, 2 fractions at least 6 h apart, within an overall treatment time of 1 day (BEDef = 251 Gy) by the RSM and ANN model. For patients presented with intermediate- or high-risk an optimal treatment regime (BFS = 94% and 90%, respectively) would be D = 38 Gy applied in one application, 4 fractions at least 6 h apart, with an overall treatment time of 2 days (BEDef = 279 Gy) by the RSM and ANN models. CONCLUSIONS: The RSM and ANN models determine almost the same optimal values for the set of predicted therapy parameters that make a feasible selection of an optimal treatment regime.
