Abstract

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Author(s):: WANG Mingli1; GU Huikuan1; HU Jiang1; GAO Xingwang2; 1. Department of Radiation Oncology, Sun Yat-sen University Cancer Center/State Key Laboratory of Oncology in South China/Collaborative Innovation Center for Cancer Medicine, Guangzhou 510060, China 2. Department of Radiation Oncology, Guangdong Provincial Peoples Hospital/Guangdong Academy of Medical Sciences, Guangzhou 510060, China

Keywords:: Keywords: cervical cancer volumetric modulated arc therapy dose-volume histogram prediction model

Abstract:: Abstract: Objective To take cervical cancer as an example for exploring the feasibility and outcomes of using dose-volume histogram (DVH) prediction model to train the radiotherapy physicists for volumetric modulated arc therapy (VMAT) planning. Methods Twenty cervical cancer cases were randomly selected to carry out two stages of training (15 cases in the first stage and the other 5 cases in the second stage) for 3 trainee physicists. Each trainee physicist was required to design VMAT plan in two ways, obtaining manual plan (MP) and knowledge-based plan (KBP) which was planned based on DVH prediction model. The dosimetric parameters of target areas and organs-at-risk between two kinds of plans were compared and analyzed. Results Compared with MP, KBP significantly reduced the radiation doses delivered to the most of normal tissues such as bladder (P<0.001), rectum (P<0.001), left and right kidneys (P=0.001, P<0.001), and left and right femoral heads (P<0.001, P<0.001), while improving the V60 of PGTV (P<0.001) and enhancing high dose control (V66) (P=0.027). The KBP based on DVH prediction model not only increased the passing rate of VMAT plan, but also minimized inter-planner diversity. Conclusion DVH prediction model helps to deepen the physicists understanding on the setting of the initial optimization parameters of VMAT plan, speed up the training schedule and improve the VMAT planning skills.