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- Wennberg, Berit M., et al.
(författare)
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NTCP modelling of lung toxicity after SBRT comparing the universal survival curve and the linear quadratic model for fractionation correction
- 2011
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Ingår i: Acta Oncologica. - : Informa Healthcare. - 0284-186X .- 1651-226X. ; 50:4, s. 518-527
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Tidskriftsartikel (refereegranskat)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. 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.
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| 2. |
- Wennberg, Berit
(författare)
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The effect of spatial and temporal dose distributions on radiation-induced side effects in the lung
- 2011
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- In radiotherapy (RT), the aim is to kill all malignant cells in a tumor or to render them incapable of further division and multiplication without producing damage to the normal tissues surrounding the tumor. To achieve this, both the spatial and temporal distribution of dose delivery are important for optimizing the treatment. A sufficiently high dose must be delivered to the tumor cells and as low a dose as possible to normal tissues. The number of fractional doses delivered also impacts outcome due to the time-dependent repair of sublethal radiation damage, which differs in tumor and normal cells. In patients undergoing RT for tumors located in and near the thorax, irradiation of the healthy lung may induce radiation pneumonitis (RP), which can be a serious problem. Understanding the factors involved in the onset of RP is important for reducing its incidence. The overall aim of the thesis was to determine if radiation-induced side effects in lung can be modelled in terms of the spatial and temporal distributions of the doses delivered in conventional RT for breast cancer (BC) and hypofractionated stereotactic body radiotherapy (SBRT) for lung cancer. Radiological changes in the lung were quantified with Computer Tomography (CT) after RT in 121 patients with breast cancer (BC). Their association with the spatial dose distribution as well as incidence of RP where studied. It was found that RP and radiological findings were associated with the spatial dose distribution. In a subgroup of 87 patients, data of the spatial dose distribution and incidence of RP were modelled using four different normal tissue complication probability (NTCP) models. The studied models fit quite accurately to data for the considered endpoints. Mean lung dose was shown to be a robust and simple parameter that correlated with the risk of RP. The calculated spatial dose distribution in SBRT of tumors in the lungs, including breathing motions, were assessed for accuracy. The analysis showed that the dose in the central part of the gross tumor volume (GTV) was accurate to within 2–3% for commonly used algorithms; however in the lung tissue close to the GTV the different algorithms both over- and underestimates it, depending on type. When clinically relevant breathing motions were considered, the dose calculated for a static situation remained a relatively accurate estimate of the dose in the GTV. Data of dose distributions and incidence of RP after SBRT for lung cancer were fitted to a NTCP model in a cohort of 57 patients. Correction for fractionation was done in two ways: with the Linear-Quadratic (LQ) model and the Universal Survival Curve (USC). The modelling showed that low dose volumes contributes less to NTCP and high dose volumes comparatively more with the USC model, than the LQ model. The impact of fractionation in SBRT was analyzed using the LQ- and USC models for fractionation correction. The therapeutic window was shown to increase with number of fractions for a range of regimes (2 to 20 fractions) at target doses common in SBRT. Generally, a larger gain was predicted with the USC correction. At high doses per fraction, typical in SBRT, the USC model predicted a lower sensitivity for fractionation as compared to the LQ model. In conclusion, the incidence of RP can be modelled, accounting for spatial and temporal dose distributions, especially in conventional RT of BC. In SBRT, with a more focused irradiation to very high doses, some uncertainties remain, both regarding the dependence of the spatial dose distribution and particularly of fractionation. The modelling shows that a less extreme hypo fractionation in SBRT may be a way to increase indications for SBRT. Generally, more data is needed for improved modelling.
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