Skip to main content
Erschienen in: Radiation Oncology 1/2017

Open Access 01.12.2017 | Research

Quantitative assessment of radiation dose and fractionation effects on normal tissue by utilizing a novel lung fibrosis index model

verfasst von: Cheng Zhou, Bleddyn Jones, Mahmoud Moustafa, Christian Schwager, Julia Bauer, Bing Yang, Liji Cao, Min Jia, Andrea Mairani, Ming Chen, Longhua Chen, Juergen Debus, Amir Abdollahi

Erschienen in: Radiation Oncology | Ausgabe 1/2017

Abstract

Background

Normal lung tissue tolerance constitutes a limiting factor in delivering the required dose of radiotherapy to cure thoracic and chest wall malignancies. Radiation-induced lung fibrosis (RILF) is considered a critical determinant for late normal tissue complications. While RILF mouse models are frequently approached e.g., as a single high dose thoracic irradiation to investigate lung fibrosis and candidate modulators, a systematic radiobiological characterization of RILF mouse model is urgently needed to compare relative biological effectiveness (RBE) of particle irradiation with protons, helium-, carbon and oxygen ions now available at HIT. We aimed to study the dose-response relationship and fractionation effect of photon irradiation in development of pulmonary fibrosis in C57BL/6 mouse.

Methods

Lung fibrosis was evaluated 24 weeks after single and fractionated whole thoracic irradiation by quantitative assessment of lung alterations using CT. The fibrosis index (FI) was determined based on 3D-segmentation of the lungs considering the two key fibrosis parameters affected by ionizing radiation i.e., a dose/fractionation dependent reduction of the total lung volume and increase of the mean lung density.

Results

The effective dose required to induce 50% of the maximal possible fibrosis (ED 50 ) was 14.55 ± 0.34Gy and 27.7 ± 1.22Gy, for single and five- fractions irradiation, respectively. Applying a deterministic model an α/β = 4.49 ± 0.38 Gy for the late lung radiosensitivity was determined. Intriguingly, we found that a linear-quadratic model could be applied to in-vivo log transformed fibrosis (FI) vs. irradiation doses. The LQ model revealed an α/β for lung radiosensitivity of 4.4879 Gy for single fraction and 3.9474 for 5-fractions. Our FI based data were in good agreement with a meta-analysis of previous lung radiosensitivity data derived from different clinical endpoints and various mouse strains. The effect of fractionation on RILF development was further estimated by the biologically effective dose (BED) model with threshold BED (BED Tr ) = 30.33 Gy and BED ED50  = 61.63 Gy, respectively.

Conclusion

The systematic radiobiological characterization of RILF in the C57BL/6 mouse reported in this study marks an important step towards precise estimation of dose-response for development of lung fibrosis. These radiobiological parameters combined with a large repertoire of genetically engineered C57BL/6 mouse models, build a solid foundation for further biologically individualized risk assessment of RILF and functional RBE prediction on novel of particle qualities.
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s13014-017-0912-y) contains supplementary material, which is available to authorized users.
Abkürzungen
BED
biologically effective dose
BPM
breaths per minute
CT
computed tomography
DVH
dose volume histogram
FI
fibrosis index
HU
Hounsfield unit
LET
linear energy transfer
LQ
linear quadratic model
MLD
mean lung dose
NSCLC
non-small cell lung cancer
PMMA
Polymethylmethacrylat
RBE
relative biological effectiveness
RILF
Radiation-induced lung fibrosis
SBRT or SABR
hypofractionated stereotactic body or ablative radiation therapy
V20
% total lung volume receiving ≥20Gy
α/β
alpha/beta ratio

Background

Radiotherapy is an integral component for treatment of thoracic tumors and breast cancer, however, the high sensitivity of normal lung tissue to ionizing radiation (IR) leading to long term sequela such as development of pulmonary fibrosis constitutes a major dose limiting constraint for a curative treatment [1]. More recently, hypofractionated stereotactic body or ablative radiation therapy (SBRT, SABR) is increasingly used for e.g., early stage non-small cell lung cancer (NSCLC) and oligometastatic diseases [2, 3]. SBRT is characterized by intensified deposition of radiation doses into one or few circumscribed regions in a single or few fractions [4]. In NSCLC e.g., a biologically effective dose (BED) of ≥ 100Gy is aimed in 1-8 fractions (based on tumor localization) with excellent local control rates [5, 6]. The high focused dose is delivered at the expense of a relatively high prescribed dose to the normal lung tissue. Therefore, several approaches are undertaken to estimate the region at risk for long term lung tissue complications after SABR/SBRT [7, 8]. To minimize normal tissue toxicity, dose volume histogram (DVH) based evaluation are considered, e.g., mean lung dose (MLD ≤ 20Gy) and total lung V20 dose-volume constraints being ≤35% according to the recommendation of National Comprehensive Cancer Network (NCCN v4.2016). These dose-volume constraints are mostly empirically based and lack of rigorous preclinical validation. Therefore, there is an urgent need for a systematic characterization and radiobiological modeling of radiation induced pulmonary fibrosis in experimental- and clinical settings for a better understanding and estimation of lung tolerance to ionizing radiation.
The clinical sequelae of radiation injury consist of a subacute onset of radiation-induced inflammation (pneumonitis) with later activation of the fibrogenesis processes [9, 10]. Preclinical studies of radiation-induced lung toxicity in different mouse models [1115] has improved our understanding of the pathophysiology of radiation lung toxicity and led to the development of biophysical models [1622]. Among those classical studies, two physiological parameters were most frequently applied for surrogating lung damages induced by ionizing radiation, breathing rate (breaths per minute, BPM) and the lethality (LD 50 ). By integrating computer assisted radiology, the present study utilized a novel CT imaging based surrogate, fibrosis index (FI) algorithm for the quantitative assessment of lung fibrosis. C57BL/6 mice is among the most frequently studied experimental models of lung fibrosis [23], however, the key parameters determining the lung tissue radiosensitivity were missing. Our data now provide radiobiological estimates for α/β ratio and BEDs for the endpoint of radiation induced pulmonary fibrosis in this important preclinical model.
This work was conducted in frame of German Research Foundation (DFG) “clinical research group heavy ion therapy (KFO-214)” in collaboration between the project TP5 and the central platform (ZP1). It builds the conceptual basis for accurate estimation of relative biological effectiveness (RBE) for carbon ions. Data on RBE variation as a function of fractionation and linear energy transfer (LET) utilizing the here presented frame work are in preparation for publication.

Methods

Irradiation and animals

Whole thoracic irradiation was administrated to female C57BL/6 mice (Charles River Breeding Laboratories, MA) aged between 8 and 10 weeks. All animal work was approved and performed in compliance with rules outlined by the local and governmental animal care committee instituted by the German government (Regierungspraesidium, Karlsruhe). Photon irradiation was delivered by a 6 MeV Artist Linac (Siemens, Germany) at a dose rate of 3 Gy/min. Prior to thoracic irradiation, mice were anaesthetized by an intraperitoneal application of 0.36 ml/kg Rompun 2% (Bayer HealthCare) and 0.54 ml/kg ketamine 10% (Pfizer). Ten anesthetized mice were placed in a specially constructed Polymethylmethacrylat (PMMA) holder for immobilization and irradiated simultaneously. To ensure full coverage of the lung field with breathing motion and sparing neighboring tissues at the maximum, the irradiation plans were adjusted by anatomical and radiological measurement. Dosimetry was used to confirm the dose uniformity in advance.

Experimental design

A wide range of dose series were included in the dose-escalation trials, single fractions (1-fx) arm of: 0, 10.5, 12.5, 14.5, 17.5, 20 Gy; five fractions (5-fx) arm of: 0, 2, 4, 6, 7, 8.5 Gy per fraction. Fractions were given once a day. Each dose group contained 12 randomly grouped mice. Quantitative CT imaging was performed every 4 weeks post irradiation. Based on our previous experiments week 24 was revealed as a suitable interval after radiation to determine late fibrosis development in terms of radiological, histological findings and lethality [1, 2426]. Mice with signs of severe dermatitis were sacrificed according to the ethics of local governmental animal care committee.

Assessment of lung fibrosis by computed tomography (CT)

A clinical PET/CT scanner (Biograph mCT, Siemens) was applied for quantitative CT imaging pre- and post-irradiation. The standard protocol employed for the CT portion of PET/CT was as follows: 80 kV with 80 mAs, a pitch of 0.6 mm, slice thickness of 0.6 mm and acquisition time of 32 s. X-ray exposure is approximately 4.14 mGy per scan. Images were reconstructed using the filter kernel H50s into a transaxial FOV of 138 × 138 mm2 as a 512 × 512 matrix. Images acquired from the clinical CT scanner were viewed and analyzed in MITK software. The lung tissue density was measured by average Hounsfield unit (HU) intensities. The lung, together with all the micro-structures, was thereby segmented using a 3D regional growing algorithm with a lower threshold of −900 HU and an upper threshold of −100 HU. Trachea and primary bronchi were manually resected upon segmentation. Volume sizes and mean HU values within the segmented area were calculated for quantitative assessment of pulmonary toxicity. The fibrosis index was employed to assess the extent of fibrosis as the major endpoint. Briefly, the FI model is based on two critical parameters derived from CT segmented data: the relative increase in mean lung density (∆HU) and decreased lung volume (∆V) when compared to the mean of an age-matched reference mice cohort. Biologically, the augmented ΔHU is an overall representation of collagen deposition and increased cellularity; whereas ∆V reflects the nature of fibrosis as a restrictive lung disease. The calculation of FI is based on the proposed equation as:
$$ \mathrm{Fibrosisindex}\left(\mathrm{FI}\right)=\sqrt{\varDelta \overline{\mathrm{HU}\uparrow}\times \varDelta \overline{\mathrm{V}\downarrow }} $$
(1)
The presence of radiation fibrosis at 24 weeks post irradiation was determined at the endpoint using delta HU and delta V via the segmentation of the entire lung (Fig. 1). Caution is warranted in the case of combined pulmonary fibrosis and emphysema syndrome (CPFE) or pleural effusions. The mean lung density as well as lung volume based on CT measurements might be biased due to the presence of emphysema (air) or effusions (fluids). A supplemented CT histograms analysis, ‘peak position of smoothened histogram (PPSH)’ was used for a differential diagnosis (see Additional file 1: Appendix).

Analysis of data

Single and fractionated FIs data were fitted by a modified probit model derived from Kallman et al. [27] using OriginPro 8.0 and Mathematica Software 9.0.
$$ \mathrm{FI}\left(\mathrm{D}\right)=\frac{1}{2}\mathrm{A}\left\{1-\operatorname{erf}\left(\sqrt{\uppi}\upgamma\ \left(1-\frac{\mathrm{D}}{{\mathrm{ED}}_{50}}\right)\right)\right\} $$
(2)
where A is the saturation constant for maximal development of fibrosis measured experimentally to be 7.20 (equal to 100% fibrosis), serving to quantize all FIs. Of note, the FIs versus dose data set used here was continuous rather than event data, hence a deterministic model was applied. Therefore, unlike ED 50 applied in probabilistic models corresponding to the probability for half (50%) of the population (animals) to develop an event, the fibrosis ED 50 could be here interpretated as the dose where the whole population experiences an average 50% increase of the FI (FI = 3.60) relative to maximum possible effect (FI = 7.20). γ is the maximum value of the normalized dose-response gradient. By integrating FIs into the late lung toxicity analysis, eq. (2) was proposed as FI-model for short.
The parameter for fractionation sensitivity α/β ratio was derived from the concept of biologically effective dose (BED) [28]. Equivalent BEDs can be achieved by different isoeffective fractionation regimens as:
$$ {\mathrm{D}}_1\left(1+\frac{{\mathrm{d}}_1}{\upalpha /\upbeta}\right)={\mathrm{D}}_2\left(1+\frac{{\mathrm{d}}_2}{\upalpha /\upbeta}\right) $$
(3)
Solving eq. (3), we get α/β as:
$$ \frac{\upalpha}{\upbeta}=\frac{{\mathrm{D}}_2{\mathrm{d}}_2-{\mathrm{D}}_1{\mathrm{d}}_1}{{\mathrm{D}}_1-{\mathrm{D}}_2} $$
(4)
Hence, the value of α/β can be obtained by two paired dose values, D 1 and D 2 giving rise to the same biological effect (namely the equal FI). According to the FI-model, any D X can be determined by the inverse function of eq. (3):
$$ {\mathrm{D}}^{-1}(FI)={ED}_{50}\left[1-\frac{1}{\sqrt{\uppi}\upgamma}{\operatorname{erf}}^{-1}\left(1-\frac{2 FI}{\mathrm{A}}\right)\right] $$
(5)
As a result, for any given FI value (0.05 ≤ FI ≤ 7.20), we can derive corresponding D 1 and D 2 values with reference to single and five fractionation schedules. The estimation of α/β was eventually made by referring to eq. (4) within the effective range of FIs.
The FIs data was also analysed as a function of BED doses by logistic regression as:
$$ \mathrm{FI}\left(\mathrm{BED}\right)=\mathrm{A}2+\frac{\left(A1-A2\right)}{\left[1+\left({\left( BED/k\right)}^p\right)\right]} $$
(6)
The threshold of BED to initiating fibrosis (BED Tr ) was defined mathematically as the maximum curvature of the curve; whereas the cut-off dose was derived from the maximum slope.
The simulated data of α/β ratios as well as iso-effect doses were fitted with an exponential decay function. For a determination of radiobiological parameters (i.e., α, β, α/β), the FI data were Log transformed and fitted to the linear-quadratic (LQ) model [18].

Literature review and statistical analysis

Literature studies were reviewed with reference to radiobiological modeling of late lung damage in mouse models. A total of 13 articles were included and the detailed parameters (i.e. author, publication year, animal, α/β ratio, endpoint, follow-up time) were extracted. Forest plots were applied to interpret the values of α/β ratio in all studies (R software v1.5.1). Data is presented as mean ± SD or otherwise stated. P < 0.05 is considered as statistically significant.

Results

Dose-response curves and fibrosis ED 50

The dose-response curves of RILF using the FI-model is demonstrated (Fig. 2). The radiation effect curve of single dose was much steeper compared to fractionated irradiation (γ = 1.64 ± 0.24, 1.41 ± 0.32, respectively; Adj. R 2 =0.97, 0.97, respectively). Fibrosis development, as surrogated by FI was markedly enhanced above a threshold dose of 11 Gy. In contrast, normal lung tissue was better spared from radiation injury using fractionated schedules (5-fx). The fibrosis ED 50 (effective dose for 50% fibrosis or FI = 3.60) for single- and five- fractions irradiations were identified to be 14.55 ± 0.34 Gy and 27.7 ± 1.22 Gy, respectively. This indicates an elevated tolerance of normal lung tissue to fractionated photons exposure, in that increasing physical doses were required for the same effectiveness.

α/β, isoeffect curves and threshold BED

The fractionation sensitivity related parameter, the α/β ratio of lung was estimated using biologically effective dose (BED) equations [28]. The obtained value of α/β ratio appears to vary with doses, and was found to be 4.49 ± 0.38 Gy based on FI-model (Fig. 3a). The α/β ratio gradually approaches to 4.26 Gy (at fibrosis ED 75 ) and even 4.20 Gy (at fibrosis ED 90 ) at severe fibrosis level. According to this analysis, using simulated data by the “direct quantal” method [19], the α/β ratio obtained at fibrosis ED 50 was estimated to be 4.38 Gy (Additional file 1: Figure S1). The iso-effect dose curve with reference to the median, first and third quartiles of the α/β ratios are provided (Fig. 3b).
On the other hand, by fitting to LQ model, the principle radiobiological parameters, α/β, α, β were also obtained approximately as α/β = 4.4879 Gy, α = 0.0480 Gy−1 and β = 0.0107 Gy−2 for single dose and α/β = 3.9474 Gy, α = 0.0150 Gy−1 and β = 0.0038 Gy−2 for 5 fractionated irradiation (Fig. 4).
BEDs with respect to all irradiated doses were predicted based on the derived α/β of 4.49 Gy. The dose-response relationship between fibrosis development and BEDs is shown (Fig. 5). The threshold BED (BED Tr ) to trigger or initiate lung fibrosis was identified as 30.33 Gy. The cut-off BED dose was 54.23 Gy. The BED ED50 (BED results in 50% of fibrosis) was determined as 61.63 Gy.

Systematic review of lung α/β ratios

A meta-analysis of experimentally derived lung α/β ratios from published studies is shown as a forest plot (Fig. 6). Detailed characteristics of the 13 studies included are provided (Additional file 1: Table S1) [15, 16, 21, 22, 2937]. The value of α/β ratio may vary with different functional assays, endpoints, follow-up time and biophysical models. The α/β ratio discovered by the FI-model in our study was consistent with the estimated α/β of 4.38 ± 1.06 derived from this pooled analysis. Given that different physiological parameters were utilized in the reports included in the meta-analysis, e.g., breath rate and LD 50 , the high agreement of the α/β values underscores the robustness of our CT based FI-model to assess lung radiosensitivity.

Discussion

The high sensitivity of lung tissue to ionizing radiation induced damage constitutes a major obstacle for curative radiotherapy of thoracic tumor. Therefore, a better characterization of radiation induced late effects in lung tissue is of utmost interest for the field of radiotherapy. Lung is featured as a late-responding tissue. In accordance with clinical observations, our data suggest a great sensitivity of late responses to changes in fractional dose. Late toxicity was significantly attenuated after 5-fractionated doses and the determined fibrosis index changes could be fitted by the LQ model. Preclinical data are limited in evaluating the late lung toxicity occurred with the intent of deriving isoeffective doses. The isoeffect curves presented here imply that the size of dose per fraction (or the fraction number) plays an essential role in sparing late lung injury. Taken together, our data clearly indicated an unfavourable toxicity profile for delivering a large fractionated dose to normal lung, unless the total dose is carefully selected.
Quantitative estimates of radiobiological characteristics for late phase of pulmonary fibrosis are urgently needed for a better experimental design of translational research in this area. A rough estimate of murine lung α/β ranging from 2.4-6.3 Gy was given by Fowler [38]. The α/β determined in the present study is 4.49 ± 0.38 Gy; While at the dose of fibrosis ED 50 , the α/β was estimated ~ 4.38 Gy. Intriguingly, pooled analysis from the past literature indicates a consensus of α/β at 4.38 ± 1.06 Gy. Furthermore, the precise dose-response relationship between BED and fibrosis development in mouse was firstly illustrated in this paper. The high comparability of the here presented late lung toxicity data with current empirically derived clinical BED data suggest further exploration of this model including other known key modulators of pulmonary sensitivity to ionizing irradiation such as combination regimens (e.g. radiochemotherapy) or partial volume effects.
Knowledge of the precise value of the average human lung α/β ratio is clinically essential, but there is no clear consensus. As reviewed by Bentzen et al., a wide range of α/β ratios from 0.9 to 8.5 Gy was reported by different clinical studies based on conventional radiotherapy [39]. In the setting of SBRT, an α/β ratio of 3 Gy is most frequently used [40]. Discrepancies between the ~4.4 α/β ratio obtained under experimentally controlled mouse condition vs. different human data may be explained by variability of numerous parameters, i.e., variable lung volumes and positions, cardiac exposure, different surrogates (e.g., pneumonitis or radiographic changes) and species specific responses. It is also possible that the α/β ratios could vary with age, cigarette smoking and other air pollution histories.
Among potential limitations of this study could be the restriction of quantitative CT-scan parameters such as lung density to discriminate between lung fibrosis vs. inflammation, lung damage induced secondary to cardiac dose, or breathing motions. However, these CT-derived parameters were found to correlate well with a broad spectrum of histopathological and molecular surrogates of lung fibrosis [1, 24, 26]. Further, lethality as a function of irradiation doses was not investigated in this study. Prediction of α/β ratio based on LQ model requires a more solid mechanistic basis, as this model so far links the radiation dose with cell survival and repopulation effects.
With advance of particle beam irradiation, the biological evaluation of (sub-) cellular and tissue response to photons, protons and carbon-ions irradiation is urgently needed [4144]. However, preclinical in-vivo comparison of normal tissue effects such as RILF as a function of different radiation qualities are missing. Hence, the proposed FI-model builds a solid bio-math-physical foundation for experimental RBE modeling.

Conclusion

In conclusion, we have introduced CT imaging based FI-model, providing a quantitative description of radiobiological characteristics as well as the dose-sparing effect of fractionation in a murine model. The α/β ratio for fibrosis induction was extracted, in parallel with a pooled analysis from a literature review. Significant sparing of late lung toxicity was illustrated in a fractionated dose regime and threshold “tolerance BED dose” was also determined. Given the spectrum of genetic mouse models available in the here employed C57BL/6 background, our data will impact design and development of personalized normal tissue toxicity estimation and targeted therapeutic interventions. The here reported radiobiological characterization of this model further provides a starting point for determining the RBE for RILF of novel raster scanning proton, helium, carbon and oxygen ions available at HIT.

Acknowledgements

We thank Hanning Dai, Physics Institute University of Heidelberg for his support and scientific discussion on data analysis. We thank Barbara Schwager, Claudia Rittmüller and Christine Schmidt for their excellent technical assistance.

Funding

This work was supported by German Research Council (DFG-KFO214, TP5 and ZP1). It was in part also supported by the Deutsche Krebshilfe (Max-Eder 108,876), intramural grants from National Center for Tumor diseases (NCT 3.0-2015.22 BioDose and DKTK/DKFZ) and the NSFC (No. 81703166/H2201). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

Availability of data and materials

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
All animal work was approved and performed in compliance with rules outlined by the local and governmental animal care committee instituted by the German government (Regierungspraesidium, Karlsruhe).
Not applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.
Literatur
1.
Zurück zum Zitat Abdollahi A, Li M, Ping G, Plathow C, Domhan S, Kiessling F, Lee LB, McMahon G, Grone HJ, Lipson KE, Huber PE. Inhibition of platelet-derived growth factor signaling attenuates pulmonary fibrosis. J Exp Med. 2005;201:925–35.CrossRefPubMedPubMedCentral Abdollahi A, Li M, Ping G, Plathow C, Domhan S, Kiessling F, Lee LB, McMahon G, Grone HJ, Lipson KE, Huber PE. Inhibition of platelet-derived growth factor signaling attenuates pulmonary fibrosis. J Exp Med. 2005;201:925–35.CrossRefPubMedPubMedCentral
2.
Zurück zum Zitat Rusthoven KE, Kavanagh BD, Burri SH, Chen C, Cardenes H, Chidel MA, Pugh TJ, Kane M, Gaspar LE, Schefter TE. Multi-institutional phase I/II trial of stereotactic body radiation therapy for lung metastases. J Clin Oncol. 2009;27:1579–84.CrossRefPubMed Rusthoven KE, Kavanagh BD, Burri SH, Chen C, Cardenes H, Chidel MA, Pugh TJ, Kane M, Gaspar LE, Schefter TE. Multi-institutional phase I/II trial of stereotactic body radiation therapy for lung metastases. J Clin Oncol. 2009;27:1579–84.CrossRefPubMed
3.
Zurück zum Zitat Eriguchi T, Takeda A, Sanuki N, Nishimura S, Takagawa Y, Enomoto T, Saeki N, Yashiro K, Mizuno T, Aoki Y, et al. Stereotactic body radiotherapy for T3 and T4N0M0 non-small cell lung cancer. J Radiat Res. 2016;57:265–72.CrossRefPubMedPubMedCentral Eriguchi T, Takeda A, Sanuki N, Nishimura S, Takagawa Y, Enomoto T, Saeki N, Yashiro K, Mizuno T, Aoki Y, et al. Stereotactic body radiotherapy for T3 and T4N0M0 non-small cell lung cancer. J Radiat Res. 2016;57:265–72.CrossRefPubMedPubMedCentral
4.
Zurück zum Zitat Popp I, Grosu AL, Niedermann G, Duda DG. Immune modulation by hypofractionated stereotactic radiation therapy: therapeutic implications. Radiother Oncol. 2016;120:185–94.CrossRefPubMed Popp I, Grosu AL, Niedermann G, Duda DG. Immune modulation by hypofractionated stereotactic radiation therapy: therapeutic implications. Radiother Oncol. 2016;120:185–94.CrossRefPubMed
5.
Zurück zum Zitat Timmerman R, Paulus R, Galvin J, Michalski J, Straube W, Bradley J, Fakiris A, Bezjak A, Videtic G, Johnstone D, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303:1070–6.CrossRefPubMedPubMedCentral Timmerman R, Paulus R, Galvin J, Michalski J, Straube W, Bradley J, Fakiris A, Bezjak A, Videtic G, Johnstone D, et al. Stereotactic body radiation therapy for inoperable early stage lung cancer. JAMA. 2010;303:1070–6.CrossRefPubMedPubMedCentral
6.
Zurück zum Zitat Solda F, Lodge M, Ashley S, Whitington A, Goldstraw P, Brada M. Stereotactic radiotherapy (SABR) for the treatment of primary non-small cell lung cancer; systematic review and comparison with a surgical cohort. Radiother Oncol. 2013;109:1–7.CrossRefPubMed Solda F, Lodge M, Ashley S, Whitington A, Goldstraw P, Brada M. Stereotactic radiotherapy (SABR) for the treatment of primary non-small cell lung cancer; systematic review and comparison with a surgical cohort. Radiother Oncol. 2013;109:1–7.CrossRefPubMed
7.
Zurück zum Zitat Defraene G, van Elmpt W, Crijns W, Slagmolen P, De Ruysscher D. CT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage. Radiother Oncol. 2015;117:29–35.CrossRefPubMed Defraene G, van Elmpt W, Crijns W, Slagmolen P, De Ruysscher D. CT characteristics allow identification of patient-specific susceptibility for radiation-induced lung damage. Radiother Oncol. 2015;117:29–35.CrossRefPubMed
8.
Zurück zum Zitat Chaudhuri AA, Binkley MS, Rigdon J, Carter JN, Aggarwal S, Dudley SA, Qian Y, Kumar KA, Hara WY, Gensheimer M, et al. Pre-treatment non-target lung FDG-PET uptake predicts symptomatic radiation pneumonitis following stereotactic ablative radiotherapy (SABR). Radiother Oncol. 2016;119:454–60.CrossRefPubMed Chaudhuri AA, Binkley MS, Rigdon J, Carter JN, Aggarwal S, Dudley SA, Qian Y, Kumar KA, Hara WY, Gensheimer M, et al. Pre-treatment non-target lung FDG-PET uptake predicts symptomatic radiation pneumonitis following stereotactic ablative radiotherapy (SABR). Radiother Oncol. 2016;119:454–60.CrossRefPubMed
9.
Zurück zum Zitat Marks L, Yu X, Vujaskovic Z, Smalljr W, Folz R, Anscher M. Radiation-induced lung injury. Semin Radiat Oncol. 2003;13:333–45.CrossRefPubMed Marks L, Yu X, Vujaskovic Z, Smalljr W, Folz R, Anscher M. Radiation-induced lung injury. Semin Radiat Oncol. 2003;13:333–45.CrossRefPubMed
10.
Zurück zum Zitat Tsoutsou PG, Koukourakis MI. Radiation pneumonitis and fibrosis: mechanisms underlying its pathogenesis and implications for future research. Int J Radiat Oncol Biol Phys. 2006;66:1281–93.CrossRefPubMed Tsoutsou PG, Koukourakis MI. Radiation pneumonitis and fibrosis: mechanisms underlying its pathogenesis and implications for future research. Int J Radiat Oncol Biol Phys. 2006;66:1281–93.CrossRefPubMed
11.
Zurück zum Zitat Fowler JF, Parkins CS, Denekamp J, Terry NH, Maughan RL, Travis EL. Early and late effects in mouse lung and rectum. Int J Radiat Oncol Biol Phys. 1982;8:2089–93.CrossRefPubMed Fowler JF, Parkins CS, Denekamp J, Terry NH, Maughan RL, Travis EL. Early and late effects in mouse lung and rectum. Int J Radiat Oncol Biol Phys. 1982;8:2089–93.CrossRefPubMed
12.
Zurück zum Zitat Thames HD, Hendry JH, Moore JV, Ang KK, Travis EL. The high steepness of dose-response curves for late-responding normal tissues. Radiother Oncol. 1989;15:49–53.CrossRefPubMed Thames HD, Hendry JH, Moore JV, Ang KK, Travis EL. The high steepness of dose-response curves for late-responding normal tissues. Radiother Oncol. 1989;15:49–53.CrossRefPubMed
13.
Zurück zum Zitat Thames HD Jr, Rozell ME, Tucker SL, Ang KK, Fisher DR, Travis EL. Direct analysis of quantal radiation response data. Int J Radiat Biol Relat Stud Phys Chem Med. 1986;49:999–1009.CrossRefPubMed Thames HD Jr, Rozell ME, Tucker SL, Ang KK, Fisher DR, Travis EL. Direct analysis of quantal radiation response data. Int J Radiat Biol Relat Stud Phys Chem Med. 1986;49:999–1009.CrossRefPubMed
14.
Zurück zum Zitat Travis EL. Early indicators of radiation injury in the lung: are they useful predictors for late changes? Int J Radiat Oncol Biol Phys. 1980;6:1267–9.CrossRefPubMed Travis EL. Early indicators of radiation injury in the lung: are they useful predictors for late changes? Int J Radiat Oncol Biol Phys. 1980;6:1267–9.CrossRefPubMed
15.
Zurück zum Zitat Parkins CS, Fowler JF, Maughan RL, Roper MJ. Repair in mouse lung for up to 20 fractions of X rays or neutrons. Br J Radiol. 1985;58:225–41.CrossRefPubMed Parkins CS, Fowler JF, Maughan RL, Roper MJ. Repair in mouse lung for up to 20 fractions of X rays or neutrons. Br J Radiol. 1985;58:225–41.CrossRefPubMed
16.
Zurück zum Zitat Wara WM, Phillips TL, Margolis LW, Smith V. Radiation pneumonitis: a new approach to the derivation of time-dose factors. Cancer. 1973;32:547–52.CrossRefPubMed Wara WM, Phillips TL, Margolis LW, Smith V. Radiation pneumonitis: a new approach to the derivation of time-dose factors. Cancer. 1973;32:547–52.CrossRefPubMed
17.
Zurück zum Zitat Douglas BG, Fowler JF. The effect of multiple small doses of x rays on skin reactions in the mouse and a basic interpretation. Radiat Res. 1976;66:401–26.CrossRefPubMed Douglas BG, Fowler JF. The effect of multiple small doses of x rays on skin reactions in the mouse and a basic interpretation. Radiat Res. 1976;66:401–26.CrossRefPubMed
18.
Zurück zum Zitat Barendsen GW. Dose fractionation, dose rate and iso-effect relationships for normal tissue responses. Int J Radiat Oncol Biol Phys. 1982;8:1981–97.CrossRefPubMed Barendsen GW. Dose fractionation, dose rate and iso-effect relationships for normal tissue responses. Int J Radiat Oncol Biol Phys. 1982;8:1981–97.CrossRefPubMed
19.
Zurück zum Zitat Thames HD, Jr., Withers HR, Peters LJ, Fletcher GH: Changes in early and late radiation responses with altered dose fractionation: implications for dose-survival relationships. Int J Radiat Oncol Biol Phys 1982, 8:219-226. Thames HD, Jr., Withers HR, Peters LJ, Fletcher GH: Changes in early and late radiation responses with altered dose fractionation: implications for dose-survival relationships. Int J Radiat Oncol Biol Phys 1982, 8:219-226.
20.
Zurück zum Zitat Thames HD. An ‘incomplete-repair’ model for survival after fractionated and continuous irradiations. Int J Radiat Biol Relat Stud Phys Chem Med. 1985;47:319–39.CrossRefPubMed Thames HD. An ‘incomplete-repair’ model for survival after fractionated and continuous irradiations. Int J Radiat Biol Relat Stud Phys Chem Med. 1985;47:319–39.CrossRefPubMed
21.
Zurück zum Zitat Field SB, Hornsey S, Kutsutani Y. Effects of fractionated irradiation on mouse lung and a phenomenon of slow repair. Br J Radiol. 1976;49:700–7.CrossRefPubMed Field SB, Hornsey S, Kutsutani Y. Effects of fractionated irradiation on mouse lung and a phenomenon of slow repair. Br J Radiol. 1976;49:700–7.CrossRefPubMed
22.
Zurück zum Zitat Van Dyk J, Mah K, Keane TJ. Radiation-induced lung damage: dose-time-fractionation considerations. Radiother Oncol. 1989;14:55–69.CrossRefPubMed Van Dyk J, Mah K, Keane TJ. Radiation-induced lung damage: dose-time-fractionation considerations. Radiother Oncol. 1989;14:55–69.CrossRefPubMed
23.
Zurück zum Zitat BM B, Lawson WE, Oury TD, Sisson TH, Raghavendran K, Hogaboam CM. Animal models of fibrotic lung disease. Am J Respir Cell Mol Biol. 2013;49:167–79.CrossRef BM B, Lawson WE, Oury TD, Sisson TH, Raghavendran K, Hogaboam CM. Animal models of fibrotic lung disease. Am J Respir Cell Mol Biol. 2013;49:167–79.CrossRef
24.
Zurück zum Zitat Plathow C, Li M, Gong P, Zieher H, Kiessling F, Peschke P, Kauczor HU, Abdollahi A, Huber PE. Computed tomography monitoring of radiation-induced lung fibrosis in mice. Investig Radiol. 2004;39:600–9.CrossRef Plathow C, Li M, Gong P, Zieher H, Kiessling F, Peschke P, Kauczor HU, Abdollahi A, Huber PE. Computed tomography monitoring of radiation-induced lung fibrosis in mice. Investig Radiol. 2004;39:600–9.CrossRef
25.
Zurück zum Zitat Flechsig P, Hartenstein B, Teurich S, Dadrich M, Hauser K, Abdollahi A, Grone HJ, Angel P, Huber PE. Loss of matrix metalloproteinase-13 attenuates murine radiation-induced pulmonary fibrosis. Int J Radiat Oncol Biol Phys. 2010;77:582–90.CrossRefPubMed Flechsig P, Hartenstein B, Teurich S, Dadrich M, Hauser K, Abdollahi A, Grone HJ, Angel P, Huber PE. Loss of matrix metalloproteinase-13 attenuates murine radiation-induced pulmonary fibrosis. Int J Radiat Oncol Biol Phys. 2010;77:582–90.CrossRefPubMed
26.
Zurück zum Zitat Li M, Abdollahi A, Grone HJ, Lipson KE, Belka C, Huber PE. Late treatment with imatinib mesylate ameliorates radiation-induced lung fibrosis in a mouse model. Radiat Oncol. 2009;4:66.CrossRefPubMedPubMedCentral Li M, Abdollahi A, Grone HJ, Lipson KE, Belka C, Huber PE. Late treatment with imatinib mesylate ameliorates radiation-induced lung fibrosis in a mouse model. Radiat Oncol. 2009;4:66.CrossRefPubMedPubMedCentral
27.
Zurück zum Zitat Kallman P, Agren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol. 1992;62:249–62.CrossRefPubMed Kallman P, Agren A, Brahme A. Tumour and normal tissue responses to fractionated non-uniform dose delivery. Int J Radiat Biol. 1992;62:249–62.CrossRefPubMed
28.
Zurück zum Zitat Jones B, Dale RG, Deehan C, Hopkins KI, Morgan DA. The role of biologically effective dose (BED) in clinical oncology. Clin Oncol (R Coll Radiol). 2001;13:71–81. Jones B, Dale RG, Deehan C, Hopkins KI, Morgan DA. The role of biologically effective dose (BED) in clinical oncology. Clin Oncol (R Coll Radiol). 2001;13:71–81.
29.
Zurück zum Zitat Hornsey S, Kutsutani Y, Field SB. Damage to mouse lung with fractionated neutrons and x rays. Radiology. 1975;116:171–4.CrossRefPubMed Hornsey S, Kutsutani Y, Field SB. Damage to mouse lung with fractionated neutrons and x rays. Radiology. 1975;116:171–4.CrossRefPubMed
30.
Zurück zum Zitat Travis EL, Parkins CS, Down JD, Fowler JF, Thames HD Jr. Repair in mouse lung between multiple small doses of X rays. Radiat Res. 1983;94:326–39.CrossRefPubMed Travis EL, Parkins CS, Down JD, Fowler JF, Thames HD Jr. Repair in mouse lung between multiple small doses of X rays. Radiat Res. 1983;94:326–39.CrossRefPubMed
31.
Zurück zum Zitat Parkins CS, Fowler JF. Repair in mouse lung of multifraction X rays and neutrons: extension to 40 fractions. Br J Radiol. 1985;58:1097–103.CrossRefPubMed Parkins CS, Fowler JF. Repair in mouse lung of multifraction X rays and neutrons: extension to 40 fractions. Br J Radiol. 1985;58:1097–103.CrossRefPubMed
32.
Zurück zum Zitat Vegesna V, Withers HR, Thames HD Jr, Mason K. Multifraction radiation response of mouse lung. Int J Radiat Biol Relat Stud Phys Chem Med. 1985;47:413–22.CrossRefPubMed Vegesna V, Withers HR, Thames HD Jr, Mason K. Multifraction radiation response of mouse lung. Int J Radiat Biol Relat Stud Phys Chem Med. 1985;47:413–22.CrossRefPubMed
33.
Zurück zum Zitat Travis EL, Thames HD, Watkins TL, Kiss I. The kinetics of repair in mouse lung after fractionated irradiation. Int J Radiat Biol Relat Stud Phys Chem Med. 1987;52:903–19.CrossRefPubMed Travis EL, Thames HD, Watkins TL, Kiss I. The kinetics of repair in mouse lung after fractionated irradiation. Int J Radiat Biol Relat Stud Phys Chem Med. 1987;52:903–19.CrossRefPubMed
34.
Zurück zum Zitat Travis EL, Curtis SB, Howard J, Fowler JF. Repair but not potentiation observed in mouse lung irradiated with neon ions. Radiat Res. 1987;112:500–7.CrossRefPubMed Travis EL, Curtis SB, Howard J, Fowler JF. Repair but not potentiation observed in mouse lung irradiated with neon ions. Radiat Res. 1987;112:500–7.CrossRefPubMed
35.
Zurück zum Zitat van der Kogel AJ, Martin JC, Smith AR, Raju MR. Late effects of fractionated pi-mesons compared to X rays on mouse lung. Int J Radiat Oncol Biol Phys. 1988;14:1175–84.CrossRefPubMed van der Kogel AJ, Martin JC, Smith AR, Raju MR. Late effects of fractionated pi-mesons compared to X rays on mouse lung. Int J Radiat Oncol Biol Phys. 1988;14:1175–84.CrossRefPubMed
36.
Zurück zum Zitat van Rongen E, Thames HD Jr, Travis EL. Recovery from radiation damage in mouse lung: interpretation in terms of two rates of repair. Radiat Res. 1993;133:225–33.CrossRefPubMed van Rongen E, Thames HD Jr, Travis EL. Recovery from radiation damage in mouse lung: interpretation in terms of two rates of repair. Radiat Res. 1993;133:225–33.CrossRefPubMed
37.
Zurück zum Zitat Van Dyk J, Keane TJ. Determination of parameters for the linear-quadratic model for radiation-induced lung damage. Int J Radiat Oncol Biol Phys. 1989;17:695.CrossRefPubMed Van Dyk J, Keane TJ. Determination of parameters for the linear-quadratic model for radiation-induced lung damage. Int J Radiat Oncol Biol Phys. 1989;17:695.CrossRefPubMed
38.
Zurück zum Zitat Fowler JF. Fractionated radiation therapy after Strandqvist. Acta Radiol Oncol. 1984;23:209–16.CrossRefPubMed Fowler JF. Fractionated radiation therapy after Strandqvist. Acta Radiol Oncol. 1984;23:209–16.CrossRefPubMed
39.
Zurück zum Zitat Bentzen SM, Skoczylas JZ, Bernier J. Quantitative clinical radiobiology of early and late lung reactions. Int J Radiat Biol. 2000;76:453–62.CrossRefPubMed Bentzen SM, Skoczylas JZ, Bernier J. Quantitative clinical radiobiology of early and late lung reactions. Int J Radiat Biol. 2000;76:453–62.CrossRefPubMed
40.
Zurück zum Zitat Fowler JF, Tome WA, Fenwick JD, Mehta MP. A challenge to traditional radiation oncology. Int J Radiat Oncol Biol Phys. 2004;60:1241–56.CrossRefPubMed Fowler JF, Tome WA, Fenwick JD, Mehta MP. A challenge to traditional radiation oncology. Int J Radiat Oncol Biol Phys. 2004;60:1241–56.CrossRefPubMed
41.
Zurück zum Zitat Chiblak S, Tang Z, Campos B, Gal Z, Unterberg A, Debus J, Herold-Mende C, Abdollahi A. Radiosensitivity of patient-derived Glioma stem cell 3-dimensional cultures to photon, proton, and carbon irradiation. Int J Radiat Oncol Biol Phys. 2016;95:112–9.CrossRefPubMed Chiblak S, Tang Z, Campos B, Gal Z, Unterberg A, Debus J, Herold-Mende C, Abdollahi A. Radiosensitivity of patient-derived Glioma stem cell 3-dimensional cultures to photon, proton, and carbon irradiation. Int J Radiat Oncol Biol Phys. 2016;95:112–9.CrossRefPubMed
42.
Zurück zum Zitat Winter M, Dokic I, Schlegel J, Warnken U, Debus J, Abdollahi A, Schnolzer M. Deciphering the acute cellular phosphoproteome response to irradiation with X-rays, protons and carbon ions. Mol Cell Proteomics. 2017. Winter M, Dokic I, Schlegel J, Warnken U, Debus J, Abdollahi A, Schnolzer M. Deciphering the acute cellular phosphoproteome response to irradiation with X-rays, protons and carbon ions. Mol Cell Proteomics. 2017.
43.
Zurück zum Zitat Niklas M, Abdollahi A, Akselrod MS, Debus J, Jakel O, Greilich S. Subcellular spatial correlation of particle traversal and biological response in clinical ion beams. Int J Radiat Oncol Biol Phys. 2013;87:1141–7.CrossRefPubMed Niklas M, Abdollahi A, Akselrod MS, Debus J, Jakel O, Greilich S. Subcellular spatial correlation of particle traversal and biological response in clinical ion beams. Int J Radiat Oncol Biol Phys. 2013;87:1141–7.CrossRefPubMed
44.
Zurück zum Zitat Dokic I, Mairani A, Niklas M, Zimmermann F, Chaudhri N, Krunic D, Tessonnier T, Ferrari A, Parodi K, Jakel O, et al. Next generation multi-scale biophysical characterization of high precision cancer particle radiotherapy using clinical proton, helium-, carbon- and oxygen ion beams. Oncotarget. 2016;7:56676–89.CrossRefPubMedPubMedCentral Dokic I, Mairani A, Niklas M, Zimmermann F, Chaudhri N, Krunic D, Tessonnier T, Ferrari A, Parodi K, Jakel O, et al. Next generation multi-scale biophysical characterization of high precision cancer particle radiotherapy using clinical proton, helium-, carbon- and oxygen ion beams. Oncotarget. 2016;7:56676–89.CrossRefPubMedPubMedCentral
Metadaten
Titel
Quantitative assessment of radiation dose and fractionation effects on normal tissue by utilizing a novel lung fibrosis index model
verfasst von
Cheng Zhou
Bleddyn Jones
Mahmoud Moustafa
Christian Schwager
Julia Bauer
Bing Yang
Liji Cao
Min Jia
Andrea Mairani
Ming Chen
Longhua Chen
Juergen Debus
Amir Abdollahi
Publikationsdatum
01.12.2017
Verlag
BioMed Central
Erschienen in
Radiation Oncology / Ausgabe 1/2017
Elektronische ISSN: 1748-717X
DOI
https://doi.org/10.1186/s13014-017-0912-y

Weitere Artikel der Ausgabe 1/2017

Radiation Oncology 1/2017 Zur Ausgabe

Update Onkologie

Bestellen Sie unseren Fach-Newsletter und bleiben Sie gut informiert.