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dc.contributor.authorBokrantz, Rasmus
dc.contributor.authorMiettinen, Kaisa
dc.date.accessioned2015-10-01T09:14:40Z
dc.date.available2016-11-01T22:45:06Z
dc.date.issued2015
dc.identifier.citationBokrantz, R., & Miettinen, K. (2015). Projections onto the Pareto surface in multicriteria radiation therapy optimization. <i>Medical Physics</i>, <i>42</i>(10), 5862-5870. <a href="https://doi.org/10.1118/1.4930252" target="_blank">https://doi.org/10.1118/1.4930252</a>
dc.identifier.otherCONVID_24903601
dc.identifier.otherTUTKAID_67227
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/47235
dc.description.abstractPurpose: 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.fi
dc.language.isoeng
dc.publisherAmerican Association of Physicists in Medicine
dc.relation.ispartofseriesMedical Physics
dc.subject.othermulticriteria
dc.subject.otherPareto optimality
dc.subject.otherradiation therapy
dc.subject.otheroptimization
dc.titleProjections onto the Pareto surface in multicriteria radiation therapy optimization
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-201510013292
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.date.updated2015-10-01T06:15:02Z
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange5862-5870
dc.relation.issn0094-2405
dc.relation.numberinseries10
dc.relation.volume42
dc.type.versionacceptedVersion
dc.rights.copyright© American Association of Physicists in Medicine 2015. This is a final draft version of an article whose final and definitive form has been published by American Association of Physicists in Medicine.
dc.rights.accesslevelopenAccessfi
dc.subject.ysoprojektio (mallinnus)
jyx.subject.urihttp://www.yso.fi/onto/yso/p8992
dc.relation.doi10.1118/1.4930252
dc.type.okmA1


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