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Robust optimization for intensity modulated radiation therapy treatment planning under uncertainty

Millie Chu et al 2005 Phys. Med. Biol. 50 5463-5477   doi: 10.1088/0031-9155/50/23/003  Help

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Millie Chu1, Yuriy Zinchenko1, Shane G Henderson1 and Michael B Sharpe2
1 School of Operations Research & Industrial Engineering, Cornell University, Ithaca, NY 14853, USA
2 Princess Margaret Hospital, Toronto, ON M5G 2M9, Canada
E-mail: mchu@orie.cornell.edu, yzinchen@orie.cornell.edu, sgh9@cornell.edu and michael.sharpe@rmp.uhn.on.ca

Abstract. The recent development of intensity modulated radiation therapy (IMRT) allows the dose distribution to be tailored to match the tumour's shape and position, avoiding damage to healthy tissue to a greater extent than previously possible. Traditional treatment plans assume that the target structure remains in a fixed location throughout treatment. However, many studies have shown that because of organ motion, inconsistencies in patient positioning over the weeks of treatment, etc, the tumour location is not stationary. We present a probabilistic model for the IMRT inverse problem and show that it is identical to using robust optimization techniques, under certain assumptions. For a sample prostate case, our computational results show that this method is computationally feasible and promising—compared to traditional methods, our model has the potential to find treatment plans that are more adept at sparing healthy tissue while maintaining the prescribed dose to the target.

Print publication: Issue 23 (7 December 2005)
Received 1 June 2005, in final form 29 September 2005
Published 9 November 2005

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