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  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
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  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
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Clinical validation of the LKB model and parameter sets for predicting radiation-induced pneumonitis from breast cancer radiotherapy

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Auteur
Tsougos, I.; Mavroidis, P.; Theodorou, K.; Rajala, J.; Pitkänen, M. A.; Holli, K.; Ojala, A. T.; Hyödynmaa, S.; Järvenpää, R.; Lind, B. K.; Kappas, C.
Date
2006
DOI
10.1088/0031-9155/51/3/L01
Sujet
Clinical laboratories
Diseases
Parameter estimation
Patient monitoring
Radiotherapy
Respiratory system
Acceptable accuracy
Breast cancer radiotherapy
Clinical validation
Radiation-induced pneumonitis
Tumors
accuracy
article
breast cancer
cancer radiotherapy
human
incidence
Monte Carlo method
prediction
priority journal
radiation dose distribution
radiation pneumonia
theoretical model
Abnormalities, Radiation-Induced
Breast Neoplasms
Dose-Response Relationship, Radiation
Humans
Lung
Models, Statistical
Models, Theoretical
Radiation Pneumonitis
Radiometry
Radiotherapy Dosage
ROC Curve
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Résumé
The 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.
URI
http://hdl.handle.net/11615/34067
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  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]

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