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NTCP modelling of lung toxicity after SBRT comparing the universal survival curve and the linear quadratic model for fractionation correction
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2011 (English)In: Acta Oncologica, ISSN 0284-186X, E-ISSN 1651-226X, Vol. 50, no 4, 518-527 p.Article in journal (Refereed) Published
Abstract [en]

Background. In SBRT of lung tumours no established relationship between dose-volume parameters and the incidence of lung toxicity is found. The aim of this study is to compare the LQ model and the universal survival curve (USC) to calculate biologically equivalent doses in SBRT to see if this will improve knowledge on this relationship. Material and methods. Toxicity data on radiation pneumonitis grade 2 or more (RP2+) from 57 patients were used, 10.5% were diagnosed with RP2+. The lung DVHs were corrected for fractionation (LQ and USC) and analysed with the Lyman-Kutcher-Burman (LKB) model. In the LQ-correction alpha/beta = 3 Gy was used and the USC parameters used were: alpha/beta = 3 Gy, D-0 = 1.0 Gy, (n) over bar = 10, alpha = 0.206 Gy(-1) and d(T) = 5.8 Gy. In order to understand the relative contribution of different dose levels to the calculated NTCP the concept of fractional NTCP was used. This might give an insight to the questions of whether "high doses to small volumes" or "low doses to large volumes" are most important for lung toxicity. Results and Discussion. NTCP analysis with the LKB-model using parameters m = 0.4, D-50 = 30 Gy resulted for the volume dependence parameter (n) with LQ correction n = 0.87 and with USC correction n = 0.71. Using parameters m = 0.3, D-50 = 20 Gy n = 0.93 with LQ correction and n = 0.83 with USC correction. In SBRT of lung tumours, NTCP modelling of lung toxicity comparing models (LQ, USC) for fractionation correction, shows that low dose contribute less and high dose more to the NTCP when using the USC-model. Comparing NTCP modelling of SBRT data and data from breast cancer, lung cancer and whole lung irradiation implies that the response of the lung is treatment specific. More data are however needed in order to have a more reliable modelling.

Place, publisher, year, edition, pages
2011. Vol. 50, no 4, 518-527 p.
National Category
Medical and Health Sciences
URN: urn:nbn:se:uu:diva-154126DOI: 10.3109/0284186X.2010.543695ISI: 000290105200003PubMedID: 21198416OAI: oai:DiVA.org:uu-154126DiVA: diva2:419298
Available from: 2011-05-26 Created: 2011-05-26 Last updated: 2015-06-09

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Nilsson, Kristina
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OncologyDepartment of Radiology, Oncology and Radiation Science
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