Literature DB >> 21520880

Minimax optimization for handling range and setup uncertainties in proton therapy.

Albin Fredriksson1, Anders Forsgren, Björn Hårdemark.   

Abstract

PURPOSE: Intensity modulated proton therapy (IMPT) is sensitive to errors, mainly due to high stopping power dependency and steep beam dose gradients. Conventional margins are often insufficient to ensure robustness of treatment plans. In this article, a method is developed that takes the uncertainties into account during the plan optimization.
METHODS: Dose contributions for a number of range and setup errors are calculated and a minimax optimization is performed. The minimax optimization aims at minimizing the penalty of the worst case scenario. Any optimization function from conventional treatment planning can be utilized by the method. By considering only scenarios that are physically realizable, the unnecessary conservativeness of other robust optimization methods is avoided. Minimax optimization is related to stochastic programming by the more general minimax stochastic programming formulation, which enables accounting for uncertainties in the probability distributions of the errors.
RESULTS: The minimax optimization method is applied to a lung case, a paraspinal case with titanium implants, and a prostate case. It is compared to conventional methods that use margins, single field uniform dose (SFUD), and material override (MO) to handle the uncertainties. For the lung case, the minimax method and the SFUD with MO method yield robust target coverage. The minimax method yields better sparing of the lung than the other methods. For the paraspinal case, the minimax method yields more robust target coverage and better sparing of the spinal cord than the other methods. For the prostate case, the minimax method and the SFUD method yield robust target coverage and the minimax method yields better sparing of the rectum than the other methods.
CONCLUSIONS: Minimax optimization provides robust target coverage without sacrificing the sparing of healthy tissues, even in the presence of low density lung tissue and high density titanium implants. Conventional methods using margins, SFUD, and MO do not utilize the full potential of IMPT and deliver unnecessarily high doses to healthy tissues.

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Year:  2011        PMID: 21520880     DOI: 10.1118/1.3556559

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  93 in total

1.  Robust optimization of intensity modulated proton therapy.

Authors:  Wei Liu; Xiaodong Zhang; Yupeng Li; Radhe Mohan
Journal:  Med Phys       Date:  2012-02       Impact factor: 4.071

2.  Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques.

Authors:  Wei Liu; Yupeng Li; Xiaoqiang Li; Wenhua Cao; Xiaodong Zhang
Journal:  Med Phys       Date:  2012-06       Impact factor: 4.071

Review 3.  Robust Proton Treatment Planning: Physical and Biological Optimization.

Authors:  Jan Unkelbach; Harald Paganetti
Journal:  Semin Radiat Oncol       Date:  2018-04       Impact factor: 5.934

4.  Robust optimization for intensity-modulated proton therapy with soft spot sensitivity regularization.

Authors:  Wenbo Gu; Dan Ruan; Daniel O'Connor; Wei Zou; Lei Dong; Min-Yu Tsai; Xun Jia; Ke Sheng
Journal:  Med Phys       Date:  2019-01-21       Impact factor: 4.071

5.  Robust treatment planning with conditional value at risk chance constraints in intensity-modulated proton therapy.

Authors:  Yu An; Jianming Liang; Steven E Schild; Martin Bues; Wei Liu
Journal:  Med Phys       Date:  2017-01-03       Impact factor: 4.071

6.  Multiple anatomy optimization of accumulated dose.

Authors:  W Tyler Watkins; Joseph A Moore; James Gordon; Geoffrey D Hugo; Jeffrey V Siebers
Journal:  Med Phys       Date:  2014-11       Impact factor: 4.071

7.  Effectiveness of robust optimization in volumetric modulated arc therapy using 6 and 10 MV flattening filter-free beam therapy planning for lung stereotactic body radiation therapy with a breath-hold technique.

Authors:  Hideharu Miura; Shuichi Ozawa; Yoshiko Doi; Minoru Nakao; Katsumaro Kubo; Masahiko Kenjo; Yasushi Nagata
Journal:  J Radiat Res       Date:  2020-07-06       Impact factor: 2.724

8.  PTV-based IMPT optimization incorporating planning risk volumes vs robust optimization.

Authors:  Wei Liu; Steven J Frank; Xiaoqiang Li; Yupeng Li; Ron X Zhu; Radhe Mohan
Journal:  Med Phys       Date:  2013-02       Impact factor: 4.071

9.  Robust optimization in IMPT using quadratic objective functions to account for the minimum MU constraint.

Authors:  Jie Shan; Yu An; Martin Bues; Steven E Schild; Wei Liu
Journal:  Med Phys       Date:  2017-12-05       Impact factor: 4.071

10.  Impact of Spot Size and Spacing on the Quality of Robustly Optimized Intensity Modulated Proton Therapy Plans for Lung Cancer.

Authors:  Chenbin Liu; Steven E Schild; Joe Y Chang; Zhongxing Liao; Shawn Korte; Jiajian Shen; Xiaoning Ding; Yanle Hu; Yixiu Kang; Sameer R Keole; Terence T Sio; William W Wong; Narayan Sahoo; Martin Bues; Wei Liu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-02-14       Impact factor: 7.038

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