title: NTCP modelling of lung toxicity after SBRT comparing the universal survival curve and the linear quadratic model for fractionation correction.
abstract: 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.
  
  
  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 α/β = 3 Gy was used and the USC parameters used were: α/β = 3 Gy, D(0) = 1.0 Gy, [Formula: see text] = 10, α = 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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Medical Physics, Karolinska University Hospital and the Karolinska Institute, Stockholm, Sweden. berit.wennberg@karolinska.se
authors.forename: Berit M
authors.initials: BM
authors.lastname: Wennberg
authors.forename: Pia
authors.initials: P
authors.lastname: Baumann
authors.forename: Giovanna
authors.initials: G
authors.lastname: Gagliardi
authors.forename: Jan
authors.initials: J
authors.lastname: Nyman
authors.forename: Ninni
authors.initials: N
authors.lastname: Drugge
authors.forename: Morten
authors.initials: M
authors.lastname: Hoyer
authors.forename: Anders
authors.initials: A
authors.lastname: Traberg
authors.forename: Kristina
authors.initials: K
authors.lastname: Nilsson
authors.forename: Elisabeth
authors.initials: E
authors.lastname: Morhed
authors.forename: Lars
authors.initials: L
authors.lastname: Ekberg
authors.forename: Lena
authors.initials: L
authors.lastname: Wittgren
authors.forename: Jo-Åsmund
authors.initials: JÅ
authors.lastname: Lund
authors.forename: Nina
authors.initials: N
authors.lastname: Levin
authors.forename: Christer
authors.initials: C
authors.lastname: Sederholm
authors.forename: Rolf
authors.initials: R
authors.lastname: Lewensohn
authors.forename: Ingmar
authors.initials: I
authors.lastname: Lax
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D017322:Clinical Trials, Phase II as Topic; D019583:Dose Fractionation, Radiation; D005260:Female; D006801:Humans; D016014:Linear Models; D008168:Lung / Q000473:pathology / Q000528:radiation effects*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology / Q000532:radiotherapy*; D008297:Male; D008875:Middle Aged; D015337:Multicenter Studies as Topic; D011379:Prognosis; D011832:Radiation Injuries / Q000209:etiology*; D011859:Radiography; D016634:Radiosurgery / Q000009:adverse effects*; D015996:Survival Rate