Literature DB >> 18367797

Worst case optimization: a method to account for uncertainties in the optimization of intensity modulated proton therapy.

D Pflugfelder1, J J Wilkens, U Oelfke.   

Abstract

The sharp dose gradients which are possible in intensity modulated proton therapy (IMPT) not only offer the possibility of generating excellent target coverage while sparing neighbouring organs at risk, but can also lead to treatment plans which are very sensitive to uncertainties in treatment variables such as the range of individual Bragg peaks. We developed a method to account for uncertainties of treatment variables in the optimization based on a worst case dose distribution. The worst case dose distribution is calculated using several possible realizations of the uncertainties. This information is used by the objective function of the inverse treatment planning system to generate treatment plans which are acceptable under all considered realizations of the uncertainties. The worst case optimization method was implemented in our in-house treatment planning software KonRad in order to demonstrate the usefulness of this approach for clinical cases. In this paper, we investigated range uncertainties, setup uncertainties and a combination of both uncertainties. Using our method the sensitivity of the resulting treatment plans to these uncertainties is considerably reduced.

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Year:  2008        PMID: 18367797     DOI: 10.1088/0031-9155/53/6/013

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  67 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

3.  Visualization of a variety of possible dosimetric outcomes in radiation therapy using dose-volume histogram bands.

Authors:  Alexei Trofimov; Jan Unkelbach; Thomas F DeLaney; Thomas Bortfeld
Journal:  Pract Radiat Oncol       Date:  2011-09-09

Review 4.  Robust Proton Treatment Planning: Physical and Biological Optimization.

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

5.  Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning.

Authors:  Jan Unkelbach; Thomas Bortfeld; Benjamin C Martin; Martin Soukup
Journal:  Med Phys       Date:  2009-01       Impact factor: 4.071

6.  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

7.  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

8.  Intensity modulated proton therapy.

Authors:  H M Kooy; C Grassberger
Journal:  Br J Radiol       Date:  2015-05-27       Impact factor: 3.039

Review 9.  Treatment planning optimisation in proton therapy.

Authors:  S E McGowan; N G Burnet; A J Lomax
Journal:  Br J Radiol       Date:  2013-01       Impact factor: 3.039

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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