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Projections onto the Pareto surface in multicriteria radiation therapy optimization
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. RaySearch Laboratories, Sweden.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory. University of Jyväskylä, Finland.
2015 (English)In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 42, no 10, 5862-5870 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To eliminate or reduce the error to Pareto optimality that arises in Pareto surface navigation when the Pareto surface is approximated by a small number of plans. Methods: The authors propose to project the navigated plan onto the Pareto surface as a postprocessing step to the navigation. The projection attempts to find a Pareto optimal plan that is at least as good as or better than the initial navigated plan with respect to all objective functions. An augmented form of projection is also suggested where dose-volume histogram constraints are used to prevent that the projection causes a violation of some clinical goal. The projections were evaluated with respect to planning for intensity modulated radiation therapy delivered by step-and-shoot and sliding window and spot-scanned intensity modulated proton therapy. Retrospective plans were generated for a prostate and a head and neck case. Results: The projections led to improved dose conformity and better sparing of organs at risk (OARs) for all three delivery techniques and both patient cases. The mean dose to OARs decreased by 3.1 Gy on average for the unconstrained form of the projection and by 2.0 Gy on average when dose-volume histogram constraints were used. No consistent improvements in target homogeneity were observed. Conclusions: There are situations when Pareto navigation leaves room for improvement in OAR sparing and dose conformity, for example, if the approximation of the Pareto surface is coarse or the problem formulation has too permissive constraints. A projection onto the Pareto surface can identify an inaccurate Pareto surface representation and, if necessary, improve the quality of the navigated plan.

Place, publisher, year, edition, pages
[Bokrantz, Rasmus; Miettinen, Kaisa] KTH Royal Inst Technol, Optimizat & Syst Theory, Dept Math, SE-10044 Stockholm, Sweden. [Bokrantz, Rasmus] RaySearch Labs, SE-10365 Stockholm, Sweden. [Miettinen, Kaisa] Univ Jyvaskyla, Dept Math Informat Technol, FI-40014 Jyvaskyla, Finland., 2015. Vol. 42, no 10, 5862-5870 p.
Keyword [en]
multicriteria, Pareto optimality, projection, radiation therapy, optimization
National Category
Radiology, Nuclear Medicine and Medical Imaging
URN: urn:nbn:se:kth:diva-176353DOI: 10.1118/1.4930252ISI: 000362570100029PubMedID: 26429260ScopusID: 2-s2.0-84941966245OAI: diva2:867073

QC 20151104

Available from: 2015-11-04 Created: 2015-11-03 Last updated: 2015-11-19Bibliographically approved

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