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Maximizing the probability of satisfying the planning criteria in radiation therapy under setup uncertainty
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.ORCID iD: 0000-0002-6252-7815
(RaySearch Laboratories)
2013 (English)Manuscript (preprint) (Other academic)
Abstract [en]

We consider intensity-modulated photon and proton therapy in the presence of setup uncertainty. The uncertainty is accounted for by worst case optimization, in which the planning criteria are constrained to be satisfied under all setup errors from a specified set. To handle that the set may contain errors under which the planning criteria cannot be satisfied, a method is introduced that includes the magnitudes of the setup errors within the set as variables in the optimization, which is aimed at making these magnitudes as large as possible (within specified bounds) while satisfying all planning criteria under the errors. This is equivalent to maximizing the probability of satisfying the planning criteria.

The method is studied with respect to photon and proton therapy applied to a prostate case and a lung case, and compared to worst case optimization with respect to an a priori determined set of errors. For both modalities, slight reductions of the magnitudes of the considered setup errors resulted in plans that satisfied a substantially larger number of planning criteria under the retracted errors, and also a larger number of criteria under the a priori errors: for the prostate case, the plans accounting for retracted errors satisfied 1.5 (photons) and 1.2 (protons) times as many planning criteria as the method accounting for a priori errors, and for the lung case, the numbers were 2.7 (photons) and 1.6 (protons).

Place, publisher, year, edition, pages
2013. , 21 p.
National Category
URN: urn:nbn:se:kth:diva-122195OAI: diva2:621308

QC 20130516

Available from: 2013-05-14 Created: 2013-05-14 Last updated: 2013-11-28Bibliographically approved
In thesis
1. Robust optimization of radiation therapy accounting for geometric uncertainty
Open this publication in new window or tab >>Robust optimization of radiation therapy accounting for geometric uncertainty
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Geometric errors may compromise the quality of radiation therapy treatments. Optimization methods that account for errors can reduce their effects.

The first paper of this thesis introduces minimax optimization to account for systematic range and setup errors in intensity-modulated proton therapy. The minimax method optimizes the worst case outcome of the errors within a given set. It is applied to three patient cases and shown to yield improved target coverage robustness and healthy structure sparing compared to conventional methods using margins, uniform beam doses, and density override. Information about the uncertainties enables the optimization to counterbalance the effects of errors.

In the second paper, random setup errors of uncertain distribution---in addition to the systematic range and setup errors---are considered in a framework that enables scaling between expected value and minimax optimization. Experiments on a phantom show that the best and mean case tradeoffs between target coverage and critical structure sparing are similar between the methods of the framework, but that the worst case tradeoff improves with conservativeness.

Minimax optimization only considers the worst case errors. When the planning criteria cannot be fulfilled for all errors, this may have an adverse effect on the plan quality. The third paper introduces a method for such cases that modifies the set of considered errors to maximize the probability of satisfying the planning criteria. For two cases treated with intensity-modulated photon and proton therapy, the method increased the number of satisfied criteria substantially. Grasping for a little less sometimes yields better plans.

In the fourth paper, the theory for multicriteria optimization is extended to incorporate minimax optimization. Minimax optimization is shown to better exploit spatial information than objective-wise worst case optimization, which has previously been used for robust multicriteria optimization.

The fifth and sixth papers introduce methods for improving treatment plans: one for deliverable Pareto surface navigation, which improves upon the Pareto set representations of previous methods; and one that minimizes healthy structure doses while constraining the doses of all structures not to deteriorate compared to a reference plan, thereby improving upon plans that have been reached with too weak planning goals.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2013. xvii, 39 p.
Trita-MAT. OS, ISSN 1401-2294 ; 13:06
Optimization, intensity-modulated proton therapy, uncertainty, robust planning, setup error, range error, intensity-modulated radiation therapy, multicriteria optimization
National Category
urn:nbn:se:kth:diva-122262 (URN)978-91-7501-771-6 (ISBN)
Public defence
2013-06-05, F3, Lindstedtsvägen 26, KTH, Stockholm, 10:00 (English)
Swedish Research Council, VR 2007-4794

QC 20130516

Available from: 2013-05-16 Created: 2013-05-15 Last updated: 2013-05-16Bibliographically approved

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