Show simple item record

Costlets: A Generalized Approach to Cost Functions for Automated Optimization of IMRT Treatment Plans

dc.contributor.authorEpelman, Marina A.en_US
dc.contributor.authorVineberg, Karen A.en_US
dc.contributor.authorEisbruch, Avrahamen_US
dc.contributor.authorLawrence, Theodore S.en_US
dc.contributor.authorKessler, Marc L.en_US
dc.contributor.authorMcshan, Daniel L.en_US
dc.contributor.authorFraass, Benedick A.en_US
dc.date.accessioned2006-09-11T19:01:55Z
dc.date.available2006-09-11T19:01:55Z
dc.date.issued2005-12en_US
dc.identifier.citationKessler, Marc L.; Mcshan, Daniel L.; Epelman, Marina A.; Vineberg, Karen A.; Eisbruch, Avraham; Lawrence, Theodore S.; Fraass, Benedick. A.; (2005). "Costlets: A Generalized Approach to Cost Functions for Automated Optimization of IMRT Treatment Plans." Optimization and Engineering 6(4): 421-448. <http://hdl.handle.net/2027.42/47484>en_US
dc.identifier.issn1389-4420en_US
dc.identifier.issn1573-2924en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/47484
dc.description.abstractWe present the creation and use of a generalized cost function methodology based on costlets for automated optimization for conformal and intensity modulated radiotherapy treatment plans. In our approach, cost functions are created by combining clinically relevant “costlets”. Each costlet is created by the user, using an “evaluator” of the plan or dose distribution which is incorporated into a function or “modifier” to create an individual costlet. Dose statistics, dose-volume points, biological model results, non-dosimetric parameters, and any other information can be converted into a costlet. A wide variety of different types of costlets can be used concurrently. Individual costlet changes affect not only the results for that structure, but also all the other structures in the plan (e.g., a change in a normal tissue costlet can have large effects on target volume results as well as the normal tissue). Effective cost functions can be created from combinations of dose-based costlets, dose-volume costlets, biological model costlets, and other parameters. Generalized cost functions based on costlets have been demonstrated, and show potential for allowing input of numerous clinical issues into the optimization process, thereby helping to achieve clinically useful optimized plans. In this paper, we describe and illustrate the use of the costlets in an automated planning system developed and used clinically at the University of Michigan Medical Center. We place particular emphasis on the flexibility of the system, and its ability to discover a variety of plans making various trade-offs between clinical goals of the treatment that may be difficult to meet simultaneously.en_US
dc.format.extent1189434 bytes
dc.format.extent3115 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherKluwer Academic Publishers; Springer Science + Business Media, Inc.en_US
dc.subject.otherMathematicsen_US
dc.subject.otherAgricultureen_US
dc.subject.otherSystems Theory, Controlen_US
dc.subject.otherOptimizationen_US
dc.subject.otherEngineering, Generalen_US
dc.subject.otherEnvironmental Managementen_US
dc.subject.otherOperations Research/Decision Theoryen_US
dc.subject.otherOptimizationen_US
dc.subject.otherCanceren_US
dc.subject.otherRadiation Therapyen_US
dc.subject.otherMathematical Programmingen_US
dc.subject.otherIntensity Modulated Radiation Therapyen_US
dc.subject.otherTreatment Planningen_US
dc.titleCostlets: A Generalized Approach to Cost Functions for Automated Optimization of IMRT Treatment Plansen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumDepartment of Industrial and Operations Engineering, The University of Michigan, Ann Arbor, MI, 48109-2117en_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumDepartment of Radiation Oncology, The University of Michigan Medical School, Ann Arbor, MI, 48109-0010en_US
dc.contributor.affiliationumcampusAnn Arboren_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/47484/1/11081_2005_Article_2066.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1007/s11081-005-2066-2en_US
dc.identifier.sourceOptimization and Engineeringen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.