A stochastic frontier analysis for enhanced treatment quality of high-dose-rate brachytherapy plans

The purpose of the present study is to develop patient specific unbiased quality control (QC) models for high dose rate (HDR) brachytherapy plans. The proposed models are based on the stochastic frontier analysis formalism, a method of economic modeling. They act as a QC tool by predicting before the treatment planning process starts, the dosimetric coverage achievable for a HDR brachytherapy prostate plan. The geometric parameters considered in developing the models were: patient clinical target volume (CTV), organs at risk (OAR) volume, the bidirectional Hausdorff distance between CTV and OARs, and a fourth parameter measuring the catheters degree of non-parallelism within the target volume. Dosimetry parameters of interest are V₁₀₀ for the CTV, V₇₅ (bladder, rectum) and D₁₀ (urethra). Results show that the built models can provide valuable information on the personalization of the optimization process based on the patient geometric parameters. The impact on the quality plan due to the planner's experience variability and judgment can be reduced by using those models, since the planner will attempt to achieve dosimetric parameters predicted by the models. Furthermore, the models provide information on the better trade-off between the target volume coverage and OARs sparing that can be achieved, regardless of the planner's experience; the latter being achieved by moving each plan at least around their respective frontier for V₁₀₀, V₇₅ and D₁₀. The shortfall of the dosimetric parameters values computed by the treatment planning system (TPS) from those predicted by the models for a proportion of plans in the dataset reveals that optimized plans from a TPS, even clinically acceptable, are not necessarily the best that could be achieved. These represent 83% of plans in the training set for the target volume coverage (V₁₀₀), ∼50% for the bladder (V₇₅) and  ∼72% for the urethra (D₁₀).