Literature DB >> 17228125

Reduced-order parameter optimization for simplifying prostate IMRT planning.

Renzhi Lu1, Richard J Radke, Laura Happersett, Jie Yang, Chen-Shou Chui, Ellen Yorke, Andrew Jackson.   

Abstract

Intensity-modulated radiotherapy (IMRT) has become an effective tool for cancer treatment with radiation. However, even expert radiation planners still need to spend a substantial amount of time manually adjusting IMRT optimization parameters such as dose limits and costlet weights in order to obtain a clinically acceptable plan. In this paper, we describe two main advances that simplify the parameter adjustment process for five-field prostate IMRT planning. First, we report the results of a sensitivity analysis that quantifies the effect of each hand-tunable parameter of the IMRT cost function on each clinical objective and the overall quality of the resulting plan. Second, we show that a recursive random search over the six most sensitive parameters as an outer loop in IMRT planning can quickly and automatically determine parameters for the cost function that lead to a plan meeting the clinical requirements. Our experiments on a ten-patient dataset show that for 70% of the cases, we can automatically determine a plan in 10 min (on the average) that is either clinically acceptable or requires only minor adjustment by the planner. The outer-loop optimization can be easily integrated into a traditional IMRT planning system.

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Year:  2007        PMID: 17228125     DOI: 10.1088/0031-9155/52/3/022

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


  10 in total

1.  A novel reduced-order prioritized optimization method for radiation therapy treatment planning.

Authors:  Georgios Kalantzis; Aditya Apte
Journal:  IEEE Trans Biomed Eng       Date:  2014-04       Impact factor: 4.538

2.  Reduced order constrained optimization (ROCO): clinical application to lung IMRT.

Authors:  Hans Stabenau; Linda Rivera; Ellen Yorke; Jie Yang; Renzhi Lu; Richard J Radke; Andrew Jackson
Journal:  Med Phys       Date:  2011-05       Impact factor: 4.071

3.  Intelligent inverse treatment planning via deep reinforcement learning, a proof-of-principle study in high dose-rate brachytherapy for cervical cancer.

Authors:  Chenyang Shen; Yesenia Gonzalez; Peter Klages; Nan Qin; Hyunuk Jung; Liyuan Chen; Dan Nguyen; Steve B Jiang; Xun Jia
Journal:  Phys Med Biol       Date:  2019-05-29       Impact factor: 3.609

4.  Reduced-order constrained optimization in IMRT planning.

Authors:  Renzhi Lu; Richard J Radke; Jie Yang; Laura Happersett; Ellen Yorke; Andrew Jackson
Journal:  Phys Med Biol       Date:  2008-11-07       Impact factor: 3.609

5.  Performance evaluation of an algorithm for fast optimization of beam weights in anatomy-based intensity modulated radiotherapy.

Authors:  Vaitheeswaran Ranganathan; V K Sathiya Narayanan; Janhavi R Bhangle; Kamlesh K Gupta; Sumit Basu; Vikram Maiya; Jolly Joseph; Amit Nirhali
Journal:  J Med Phys       Date:  2010-04

6.  Radiotherapy Planning Using an Improved Search Strategy in Particle Swarm Optimization.

Authors:  Arezoo Modiri; Xuejun Gu; Aaron M Hagan; Amit Sawant
Journal:  IEEE Trans Biomed Eng       Date:  2016-06-27       Impact factor: 4.538

7.  Operating a treatment planning system using a deep-reinforcement learning-based virtual treatment planner for prostate cancer intensity-modulated radiation therapy treatment planning.

Authors:  Chenyang Shen; Dan Nguyen; Liyuan Chen; Yesenia Gonzalez; Rafe McBeth; Nan Qin; Steve B Jiang; Xun Jia
Journal:  Med Phys       Date:  2020-03-28       Impact factor: 4.071

8.  Improving efficiency of training a virtual treatment planner network via knowledge-guided deep reinforcement learning for intelligent automatic treatment planning of radiotherapy.

Authors:  Chenyang Shen; Liyuan Chen; Yesenia Gonzalez; Xun Jia
Journal:  Med Phys       Date:  2021-02-16       Impact factor: 4.071

9.  A hierarchical deep reinforcement learning framework for intelligent automatic treatment planning of prostate cancer intensity modulated radiation therapy.

Authors:  Chenyang Shen; Liyuan Chen; Xun Jia
Journal:  Phys Med Biol       Date:  2021-06-23       Impact factor: 3.609

10.  An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

Authors:  Ting Song; Nan Li; Masoud Zarepisheh; Yongbao Li; Quentin Gautier; Linghong Zhou; Loren Mell; Steve Jiang; Laura Cerviño
Journal:  PLoS One       Date:  2016-03-01       Impact factor: 3.240

  10 in total

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