Please use this identifier to cite or link to this item: http://hdl.handle.net/11434/629
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dc.contributor.authorKenny, John-
dc.contributor.otherBiggs, S.-
dc.contributor.otherSobolewski, M.-
dc.contributor.otherMurry, R.-
dc.date2015-11-
dc.date.accessioned2016-05-10T06:36:22Z-
dc.date.available2016-05-10T06:36:22Z-
dc.date.issued2016-01-
dc.identifier.citationPhys Med. 2016 Jan;32(1):255-9en_US
dc.identifier.issn1120-1797en_US
dc.identifier.urihttp://hdl.handle.net/11434/629-
dc.description.abstractThere are many methods available to predict electron output factors; however, many centres still measure the factors for each irregular electron field. Creating an electron output factor prediction model that approaches measurement accuracy - but uses already available data and is simple to implement - would be advantageous in the clinical setting. This work presents an empirical spline model for output factor prediction that requires only the measured factors for arbitrary insert shapes. Equivalent ellipses of the insert shapes are determined and then parameterised by width and ratio of perimeter to area. This takes into account changes in lateral scatter, bremsstrahlung produced in the insert material, and scatter from the edge of the insert. Agreement between prediction and measurement for the 12 MeV validation data had an uncertainty of 0.4% (1SD). The maximum recorded deviation between measurement and prediction over the range of energies was 1.0%. The validation methodology showed that one may expect an approximate uncertainty of 0.5% (1SD) when as little as eight data points are used. The level of accuracy combined with the ease with which this model can be generated demonstrates its suitability for clinical use. Implementation of this method is freely available for download at https://github.com/SimonBiggs/electronfactorsen_US
dc.publisherElsevieren_US
dc.subjectIrregular Field Shapesen_US
dc.subjectData Interpolationen_US
dc.subjectElectron Output Factoren_US
dc.subjectElectron Therapyen_US
dc.subjectInsert Factoren_US
dc.subjectPrediction Modellingen_US
dc.subjectEmpirical Spline Modellingen_US
dc.subjectBivariate Spline Modellingen_US
dc.titleSpline modelling electron insert factors using routine measurements.en_US
dc.typeJournal Articleen_US
dc.identifier.doi10.1016/j.ejmp.2015en_US
dc.identifier.journaltitlePhysica Medicaen_US
dc.description.pubmedurihttp://www.ncbi.nlm.nih.gov/pubmed/26596874-
dc.description.affiliatesRiverina Cancer Care Centre, Wagga Wagga, New South Wales 2650, Australia.en_US
dc.description.affiliatesRadiation Oncology Queensland, Rockville, Queensland 4350, Australia.en_US
dc.type.studyortrialPredictive Testen_US
dc.type.contenttypeTexten_US
Appears in Collections:Radiation Oncology

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