Evaluation of fully automated volumetric modulated arc therapy planning of cervical cancer in RayStation treatment planning system

Abstract

Objective To evaluate the feasibility of an in-room automated volumetric arc therapy (VMAT) planning engine based on dose volume histogram (DVH) prediction model in RayStation treatment planning system. Methods A total of 40 VMAT plans of cervix cancer, planned by experts, were chosen to build DVH estimation model by principal component regression analytic method. An in-room automated VMAT planning program based on IroPython scripting language combined with DVH prediction model was performed in RayStation treatment planning system. The DVH estimation model was applied to Another 10 testing cases of cervical cancer and the feasibility was evaluated by comparing the automatic plans with manual plans. Results The predicted DVH of organs at risk showed a good fit with real DVH in the ten testing cases. There were no statistically significant differences between manual and automatic plans in PTV conformal index (CI) and homogeneity index (HI) (P> 0.05). V40 and V50 of bladder were significantly decreased by 4.3% and 1.6% in automatic plans (t=2.75, 5.26, P< 0.05). V30, V40 and V50 of rectum were also decreased by 6.8%, 5.8% and 2.1%(t=2.26, 3.55, 5.19, P< 0.05). Both left and right femoral heads were better spared in automatic plans with average doses decreased by 380 and 322 cGy(t=5.55, 7.25, P< 0.05). The time of creating a treatment plan was 36 min for automatic plan and 53 min for manual plan. Conclusions The fully automated VMAT treatment plan program can create a VMAT plan of cervix cancer with high efficiency and good quality. Key words: Automatic planning; DVH estimation; RayStation TPS; IronPython language