title: The use of risk estimation models for the induction of secondary cancers following radiotherapy.
abstract: Theoretical predictions of cancer risk from radiotherapy may be used as a complementary criterion for the selection of successful treatment plans together with the classical approach of estimating the possible deterministic effects. However, any such attempts must take into consideration the specific features of radiation treatment. This paper explores several possible methods for estimating the risk of cancer following radiotherapy in order to investigate the influences of the fractionation and the non-uniformity of the dose to the irradiated organ. The results indicate that dose inhomogeneity plays an important role in predicting the risk for secondary cancer and therefore for predictive purposes it must be taken into account through the use of the dose volume histograms. They also suggest that the competition between cell killing and the induction of carcinogenic mutations has to be taken into consideration for more realistic risk estimations. Furthermore, more realistic parameters could be obtained if this competition is also included in analyses of epidemiological data from radiotherapy applications.
authors.affiliation: Department of Radiation Sciences, Umeå University, 901 87 Umeå, Sweden. alexandru.dasu@radfys.umu.se
authors.forename: Alexandru
authors.initials: A
authors.lastname: Daşu
authors.forename: Iuliana
authors.initials: I
authors.lastname: Toma-Daşu
authors.forename: Jörgen
authors.initials: J
authors.lastname: Olofsson
authors.forename: Mikael
authors.initials: M
authors.lastname: Karlsson
mesh_terms: D004307:Dose-Response Relationship, Radiation; D006801:Humans; D015994:Incidence; D008175:Lung Neoplasms / Q000532:radiotherapy; D008962:Models, Theoretical; D009381:Neoplasms, Radiation-Induced / Q000453:epidemiology* / Q000209:etiology; D016609:Neoplasms, Second Primary / Q000453:epidemiology* / Q000209:etiology; D009928:Organ Specificity / Q000528:radiation effects; D011836:Radiation Tolerance; D011880:Radiotherapy Planning, Computer-Assisted; D012004:Rectal Neoplasms / Q000532:radiotherapy; D012307:Risk Factors; D001749:Urinary Bladder Neoplasms / Q000532:radiotherapy