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A characterization of robust radiation therapy treatment planning methods-from expected value to worst case optimization
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
2012 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 39, no 8, 5169-5181 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To characterize a class of optimization formulations used to handle systematic and random errors in radiation therapy, and to study the differences between the methods within this class. Methods: The class of robust methods that can be formulated as minimax stochastic programs is studied. This class generalizes many previously used methods, ranging between optimization of the expected and the worst case objective value. The robust methods are used to plan intensity-modulated proton therapy (IMPT) treatments for a case subject to systematic setup and range errors, random setup errors with and without uncertain probability distribution, and combinations thereof. As reference, plans resulting from a conventional method that uses a margin to account for errors are shown. Results: For all types of errors, target coverage robustness increased with the conservativeness of the method. For systematic errors, best case organ at risk (OAR) doses increased and worst case doses decreased with the conservativeness. Accounting for random errors of fixed probability distribution resulted in heterogeneous dose. The heterogeneities were reduced when uncertainty in the probability distribution was accounted for. Doing so, the OAR doses decreased with the conservativeness. All robust methods studied resulted in more robust target coverage and lower OAR doses than the conventional method. Conclusions: Accounting for uncertainties is essential to ensure plan quality in complex radiation therapy such as IMPT. The utilization of more information than conventional in the optimization can lead to robust target coverage and low OAR doses. Increased target coverage robustness can be achieved by more conservative methods.

Place, publisher, year, edition, pages
2012. Vol. 39, no 8, 5169-5181 p.
Keyword [en]
IMPT, optimization, robust planning, uncertainty
National Category
Computational Mathematics
URN: urn:nbn:se:kth:diva-101542DOI: 10.1118/1.4737113ISI: 000307917600055ScopusID: 2-s2.0-84864718284OAI: diva2:549654
Swedish Research Council

QC 20120905

Available from: 2012-09-05 Created: 2012-08-30 Last updated: 2013-05-16Bibliographically 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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