Research and realization of automatic evaluation of stereotactic radiotherapy plan for early non-small cell lung cancer
Huang Shixiong1,2, Yang Songhua1, Zeng Degao1,2, Zeng Biao1,2
1Department of Radiological Physics and Technology, Hunan Cancer Hospital, Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha 410013, China; 2Key Laboratory of Translational Radiation Oncology of Hunan Province,Changsha 410013, China
Abstract:Objective To realize the automatic evaluation of the target conformity, dose overflow, dose drop and other indicators in stereotactic body radiation therapy (SBRT) plan for the early non-small cell lung cancer (NSCLC) in the Eclipse planning system. Methods Eclipse Scripting API application development interface and C# programming language were used to develop it with script plug-ins combined with independent programs. According to the requirements of the NSCLC SBRT plan in Radiation Therapy Oncology Group (RTOG) 0915 report, the automatic evaluation of related indicators was realized. A rule of equal interval sampling and double thresholds was designed during the period,which could more accurately and conveniently evaluate the dose drop outside the target area. Results 13 clinical cases of NSCLC SBRT plans were randomly selected, the method in this study and the module equipped with the Eclipse system to were utilized to evaluate and compare the results. It was concluded that the results of the two methods were in line with the clinical requirements, and the former was more efficient (P<0.05). Conclusions The NSCLC SBRT plan evaluation software in this article has a friendly interface. It can not only realize the automatic evaluation of target conformity, dose overflow and dose drop, but also effectively improve work efficiency and better serve the clinical and scientific research work of radiotherapy.
Huang Shixiong,Yang Songhua,Zeng Degao et al. Research and realization of automatic evaluation of stereotactic radiotherapy plan for early non-small cell lung cancer[J]. Chinese Journal of Radiation Oncology, 2022, 31(4): 352-358.
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