Abstract

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Title:: Non-knowledge-based auto-planning of volumetric modulated arc therapy for gastric cancer

Author(s):: LIU Junyi1; HE Ling2; WEI Zhigong2; XIAO Jianghong1; 1. Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China 2. Department of Biotherapy, Cancer Center, West China Hospital, Sichuan University, Chengdu 610041, China

Keywords:: Keywords: gastric cancer non-knowledge-based auto-planning volumetric modulated arc therapy

Abstract:: Abstract: Objective To evaluate the feasibility of non-knowledge-based auto-planning of volumetric modulated arc therapy (VMAT) in radiotherapy for gastric cancer. Methods Thirty cases of gastric cancer receiving postoperative radiotherapy were collected retrospectively. The automatic VMAT planning program developed based on Python language was used to design the radiotherapy plan of gastric cancer. The objective parameters setting and optimization were based on prescription and objective function values instead of historical plans. Then, the dosimetric parameters and planning time of automatic plans and manual plans were compared. Results Both of manual and automatic plans could meet the target dose coverage. Compared with those in manual plans, the absorbed dose of spinal cord, small intestine and kidney in automatic plans were significantly decreased (P<0.05). However, there was trivial difference in absorbed dose between two kinds of plans for the organs-at-risk close to the target area such as duodenum and liver (P>0.05). In addition, the median planning time of auto-planning was 23.9 min less than that of manual planning (P<0.05). Conclusion For gastric cancer, the non-knowledge-based auto-planning can not only meet the target dose coverage, but also significantly reduce the radiation dose to organs-at-risk far away from the target area and improve the planning efficiency.