Abstract：The design of a conventional radiotherapy plan is a time-consuming and labor-intensive process, and relevant parameters need to be continuously adjusted in the plan optimization to identify the optimal plan. In addition, experience differences between planners, time invested in plan design, and institutional standards all affect the quality of the plan, which in turn influences clinical outcomes and patient prognosis. In recent years, automatic planning has developed rapidly, which can improve the efficiency of planning design while ensuring the quality of the plan. At present, there are several methods dedicated to the automation of radiotherapy planning design, such as the Rapid Plan and Auto-Planning functions in Eclipse and Pinnacle commercial treatment planning systems, and there are also studies applying artificial intelligence technology in dose prediction to achieve automatic planning. In this article, the research progress on automatic radiotherapy planning was reviewed, and the realization principles, clinical efficacy and existing problems of various automatic planning methods were illustrated.
Zhang Qilin,Zhang Shuming,Wang Mingqing et al. Research progress on automatic treatment planning methods for radiotherapy[J]. Chinese Journal of Radiation Oncology, 2021, 30(3): 316-320.
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2021, Vol. 30 
