The model training of knowledge-based radiotherapy treatment planning and its preliminary application

Abstract

Objective Knowledge-based radiotherapy (KBRT) can reduce the plan quality variability induced by different experiences between physicians and improve the quality of treatment plans. Methods The Varian Rapid Plan system was used to train a dose-volume histogram (DVH) prediction model. The obtained model was preliminarily applied to semi-automatic design of the preoperative treatment plans for rectal cancer. Eighty high-quality volumetric modulated arc therapy plans were imported into the model training set of the Rapid Plan system. The structures of the plans were matched to the corresponding labels and codes as listed in the library. The training started after the verification of prescription. The residual plots, regression curves, geometric plots for organ at risk (OAR), in-field DVH plots, and model training logs were examined. After removal of the mismatch, the original plans were assessed to rule out outliers and influential data points. More similar plans may be added for another round of training. Ten KBRT plans were designed using the final model and compared with the clinical plans. Results For the two major OARs, the femoral head and bladder, the average goodness of fit of the principal component were 0.999415/1.0 and 0.999963/1.0 for the DVH model, and 0.999651/1.0 and 0.999945/1.0 for geometry-based expected dose model, respectively. In all the plans, 11 had Cook’s distance values exceeding the tolerance and 4 had studentized residual values exceeding the tolerance. The outliers were all kept in the training set to generalize the scope of the model. The 10 KBRT plans had significantly improved homogeneity indices for PGTV and PTV than the original plans (P=0.00, 0.04). The 10 KBRT plans also had significantly reduced D50% to the femoral head and bladder as well as significantly reduced mean doses to the bladder than the original plans (P=0.042, 0.000, 0.005). Conclusions In this study, the Rapid Plan system is used to train a KBRT model for design of preoperative radiotherapy plans for rectal cancer. The results of preliminary application meet the clinical requirements. Key words: Radiotherapy planning; Model training; Model verification