Multi-objective optimization of inverse planning for accurate radiotherapy

CAO Rui-Fen; WU Yi-Can; PEI Xi; JING Jia; LI Guo-Li; CHENG Meng-Yun; LI Gui; HU Li-Qin

doi:10.1088/1674-1137/35/3/019

Chinese Physics C> 2011, Vol. 35> Issue(3) : 313-317 DOI: 10.1088/1674-1137/35/3/019

Multi-objective optimization of inverse planning for accurate radiotherapy

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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 dose-volume 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.

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CAO Rui-Fen, WU Yi-Can, PEI Xi, JING Jia, LI Guo-Li, CHENG Meng-Yun, LI Gui and HU Li-Qin. Multi-objective optimization of inverse planning for accurate radiotherapy[J]. Chinese Physics C, 2011, 35(3): 313-317. doi: 10.1088/1674-1137/35/3/019

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Received: 2009-05-04
Revised: 2010-11-09

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通讯作者: 陈斌, bchen63@163.com

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沈阳化工大学材料科学与工程学院沈阳 110142

Multi-objective optimization of inverse planning for accurate radiotherapy

Received Date: 2009-05-04

Accepted Date: 2010-11-09

Available Online: 2011-03-05

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 dose-volume 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.

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Multi-objective optimization of inverse planning for accurate radiotherapy

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