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dc.contributor.authorTsang, HS
dc.contributor.authorKamerling, CP
dc.contributor.authorZiegenhein, P
dc.contributor.authorNill, S
dc.contributor.authorOelfke, U
dc.date.accessioned2017-07-19T11:59:34Z
dc.date.issued2017-06
dc.identifier.citationPhysics in medicine and biology, 2017, 62 (12), pp. 4917 - 4928
dc.identifier.issn0031-9155
dc.identifier.urihttps://repository.icr.ac.uk/handle/internal/713
dc.identifier.eissn1361-6560
dc.identifier.doi10.1088/1361-6560/aa6b90
dc.description.abstractRadiotherapy treatment planning for use with high-energy photon beams currently employs a binary approach in defining the planning target volume (PTV). We propose a margin concept that takes the beam directions into account, generating beam-dependent PTVs (bdPTVs) on a beam-by-beam basis. The resulting degree of overlaps between the bdPTVs are used within the optimisation process; the optimiser effectively considers the same voxel to be both target and organ at risk (OAR) with fractional contributions. We investigate the impact of this novel approach when applied to prostate radiotherapy treatments, and compare treatment plans generated using beam dependent margins to conventional margins. Five prostate patients were used in this planning study, and plans using beam dependent margins improved the sparing of high doses to target-surrounding OARs, though a trade-off in delivering additional low dose to the OARs can be observed. Plans using beam dependent margins are observed to have a slightly reduced target coverage. Nevertheless, all plans are able to satisfy 90% population coverage with the target receiving at least 95% of the prescribed dose to [Formula: see text].
dc.formatPrint-Electronic
dc.format.extent4917 - 4928
dc.languageeng
dc.language.isoeng
dc.rights.urihttps://creativecommons.org/licenses/by/4.0
dc.subjectHumans
dc.subjectProstatic Neoplasms
dc.subjectRadiotherapy Dosage
dc.subjectRadiotherapy Planning, Computer-Assisted
dc.subjectProbability
dc.subjectPhotons
dc.subjectMale
dc.subjectOrgans at Risk
dc.titleA novel probabilistic approach to generating PTV with partial voxel contributions.
dc.typeJournal Article
dcterms.dateAccepted2017-04-05
rioxxterms.versionofrecord10.1088/1361-6560/aa6b90
rioxxterms.licenseref.urihttps://creativecommons.org/licenses/by/4.0
rioxxterms.licenseref.startdate2017-06
rioxxterms.typeJournal Article/Review
dc.relation.isPartOfPhysics in medicine and biology
pubs.issue12
pubs.notesNo embargo
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.organisational-group/ICR
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Radiotherapy and Imaging/Radiotherapy Physics Modelling
pubs.organisational-group/ICR/Primary Group/Royal Marsden Clinical Units
pubs.publication-statusPublished
pubs.volume62
pubs.embargo.termsNo embargo
icr.researchteamRadiotherapy Physics Modellingen_US
dc.contributor.icrauthorTsang, Shui-Heng Henryen
dc.contributor.icrauthorOelfke, Uween
dc.contributor.icrauthorNill, Simeonen
dc.contributor.icrauthorMarsden,en


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