Multi-objective optimization of inverse planning for accurate radiotherapy

  • Rui Fen Cao
  • , Yi Can Wu
  • , Xi Pei
  • , Jia Jing
  • , Guo Li Li
  • , Meng Yun Cheng
  • , Gui Li
  • , Li Qin Hu

Research output: Contribution to journalArticlepeer-review

25 Scopus citations

Abstract

The multi-objective optimization of inverse planning based on the Pareto solution set, according to the multi-objective character of inverse planning in accurate radiotherapy, was studied in this paper. Firstly, the clinical requirements of a treatment plan were transformed into a multi-objective optimization problem with multiple constraints. Then, the fast and elitist multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) was introduced to optimize the problem. A clinical example was tested using this method. The results show that an obtained set of non-dominated solutions were uniformly distributed and the corresponding dose distribution of each solution not only approached the expected dose distribution, but also met the dosevolume constraints. It was indicated that the clinical requirements were better satisfied using the method and the planner could select the optimal treatment plan from the non-dominated solution set.

Original languageEnglish
Pages (from-to)313-317
Number of pages5
JournalChinese Physics C
Volume35
Issue number3
DOIs
StatePublished - Mar 2011

Keywords

  • Accurate radiotherapy
  • Inverse planning
  • Multi-objective optimization

Fingerprint

Dive into the research topics of 'Multi-objective optimization of inverse planning for accurate radiotherapy'. Together they form a unique fingerprint.

Cite this