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dc.creatorTsougos, I.en
dc.creatorMavroidis, P.en
dc.creatorTheodorou, K.en
dc.creatorRajala, J.en
dc.creatorPitkänen, M. A.en
dc.creatorHolli, K.en
dc.creatorOjala, A. T.en
dc.creatorHyödynmaa, S.en
dc.creatorJärvenpää, R.en
dc.creatorLind, B. K.en
dc.creatorKappas, C.en
dc.date.accessioned2015-11-23T10:52:23Z
dc.date.available2015-11-23T10:52:23Z
dc.date.issued2006
dc.identifier10.1088/0031-9155/51/3/L01
dc.identifier.issn319155
dc.identifier.urihttp://hdl.handle.net/11615/34067
dc.description.abstractThe choice of the appropriate model and parameter set in determining the relation between the incidence of radiation pneumonitis and dose distribution in the lung is of great importance, especially in the case of breast radiotherapy where the observed incidence is fairly low. From our previous study based on 150 breast cancer patients, where the fits of dose-volume models to clinical data were estimated (Tsougos et al 2005 Evaluation of dose-response models and parameters predicting radiation induced pneumonitis using clinical data from breast cancer radiotherapy Phys. Med. Biol. 50 3535-54), one could get the impression that the relative seriality is significantly better than the LKB NTCP model. However, the estimation of the different NTCP models was based on their goodness-of-fit on clinical data, using various sets of published parameters from other groups, and this fact may provisionally justify the results. Hence, we sought to investigate further the LKB model, by applying different published parameter sets for the very same group of patients, in order to be able to compare the results. It was shown that, depending on the parameter set applied, the LKB model is able to predict the incidence of radiation pneumonitis with acceptable accuracy, especially when implemented on a sub-group of patients (120) receiving D=|EUD higher than 8 Gy. In conclusion, the goodness-of-fit of a certain radiobiological model on a given clinical case is closely related to the selection of the proper scoring criteria and parameter set as well as to the compatibility of the clinical case from which the data were derived. © 2006 IOP Publishing Ltd.en
dc.source.urihttp://www.scopus.com/inward/record.url?eid=2-s2.0-31344445928&partnerID=40&md5=3fb1a01570602fb5af863a65ae3a1b17
dc.subjectClinical laboratoriesen
dc.subjectDiseasesen
dc.subjectParameter estimationen
dc.subjectPatient monitoringen
dc.subjectRadiotherapyen
dc.subjectRespiratory systemen
dc.subjectAcceptable accuracyen
dc.subjectBreast cancer radiotherapyen
dc.subjectClinical validationen
dc.subjectRadiation-induced pneumonitisen
dc.subjectTumorsen
dc.subjectaccuracyen
dc.subjectarticleen
dc.subjectbreast canceren
dc.subjectcancer radiotherapyen
dc.subjecthumanen
dc.subjectincidenceen
dc.subjectMonte Carlo methoden
dc.subjectpredictionen
dc.subjectpriority journalen
dc.subjectradiation dose distributionen
dc.subjectradiation pneumoniaen
dc.subjecttheoretical modelen
dc.subjectAbnormalities, Radiation-Induceden
dc.subjectBreast Neoplasmsen
dc.subjectDose-Response Relationship, Radiationen
dc.subjectHumansen
dc.subjectLungen
dc.subjectModels, Statisticalen
dc.subjectModels, Theoreticalen
dc.subjectRadiation Pneumonitisen
dc.subjectRadiometryen
dc.subjectRadiotherapy Dosageen
dc.subjectROC Curveen
dc.titleClinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapyen
dc.typejournalArticleen


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