Minimax optimization for handling range and setup uncertainties in proton therapy
2011 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 38, no 3, 1672-1684 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
2011. Vol. 38, no 3, 1672-1684 p.
IMPT optimization, minimax optimization, robust planning, uncertainty
Radiology, Nuclear Medicine and Medical Imaging Computational Mathematics
IdentifiersURN: urn:nbn:se:kth:diva-31612DOI: 10.1118/1.3556559ISI: 000287879400057ScopusID: 2-s2.0-79952141736OAI: oai:DiVA.org:kth-31612DiVA: diva2:406106
FunderSwedish Research Council
QC 201103242011-03-242011-03-212013-05-16Bibliographically approved