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Switzerland

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Walsh L.,University of Manchester | Schneider U.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG
Radiation and Environmental Biophysics | Year: 2013

Radiation-related risks of cancer can be transported from one population to another population at risk, for the purpose of calculating lifetime risks from radiation exposure. Transfer via excess relative risks (ERR) or excess absolute risks (EAR) or a mixture of both (i.e., from the life span study (LSS) of Japanese atomic bomb survivors) has been done in the past based on qualitative weighting. Consequently, the values of the weights applied and the method of application of the weights (i.e., as additive or geometric weighted means) have varied both between reports produced at different times by the same regulatory body and also between reports produced at similar times by different regulatory bodies. Since the gender and age patterns are often markedly different between EAR and ERR models, it is useful to have an evidence-based method for determining the relative goodness of fit of such models to the data. This paper identifies a method, using Akaike model weights, which could aid expert judgment and be applied to help to achieve consistency of approach and quantitative evidence-based results in future health risk assessments. The results of applying this method to recent LSS cancer incidence models are that the relative EAR weighting by cancer solid cancer site, on a scale of 0-1, is zero for breast and colon, 0.02 for all solid, 0.03 for lung, 0.08 for liver, 0.15 for thyroid, 0.18 for bladder and 0.93 for stomach. The EAR weighting for female breast cancer increases from 0 to 0.3, if a generally observed change in the trend between female age-specific breast cancer incidence rates and attained age, associated with menopause, is accounted for in the EAR model. Application of this method to preferred models from a study of multi-model inference from many models fitted to the LSS leukemia mortality data, results in an EAR weighting of 0. From these results it can be seen that lifetime risk transfer is most highly weighted by EAR only for stomach cancer. However, the generalization and interpretation of radiation effect estimates based on the LSS cancer data, when projected to other populations, are particularly uncertain if considerable differences exist between site-specific baseline rates in the LSS and the other populations of interest. Definitive conclusions, regarding the appropriate method for transporting cancer risks, are limited by a lack of knowledge in several areas including unknown factors and uncertainties in biological mechanisms and genetic and environmental risk factors for carcinogenesis; uncertainties in radiation dosimetry; and insufficient statistical power and/or incomplete follow-up in data from radio-epidemiological studies. © 2012 Springer-Verlag Berlin Heidelberg.


Schneider U.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG
Genes | Year: 2011

In developed countries, more than half of all cancer patients receive radiotherapy at some stage in the management of their disease. However, a radiation-induced secondary malignancy can be the price of success if the primary cancer is cured or at least controlled. Therefore, there is increasing concern regarding radiation-related second cancer risks in long-term radiotherapy survivors and a corresponding need to be able to predict cancer risks at high radiation doses. Of particular interest are second cancer risk estimates for new radiation treatment modalities such as intensity modulated radiotherapy, intensity modulated arc-therapy, proton and heavy ion radiotherapy. The long term risks from such modern radiotherapy treatment techniques have not yet been determined and are unlikely to become apparent for many years, due to the long latency time for solid tumor induction. Most information on the dose-response of radiation-induced cancer is derived from data on the A-bomb survivors who were exposed to checkentity[1]/checkentity-rays and neutrons. Since, for radiation protection purposes, the dose span of main interest is between zero and one Gy, the analysis of the A-bomb survivors is usually focused on this range. With increasing cure rates, estimates of cancer risk for doses larger than one Gy are becoming more important for radiotherapy patients. Therefore in this review, emphasis was placed on doses relevant for radiotherapy with respect to radiation induced solid cancer. Simple radiation protection models should be used only with extreme care for risk estimates in radiotherapy, since they are developed exclusively for low dose. When applied to scatter radiation, such models can predict only a fraction of observed second malignancies. Better semi-empirical models include the effect of dose fractionation and represent the dose-response relationships more accurately. The involved uncertainties are still huge for most of the organs and tissues. A major reason for this is that the underlying processes of the induction of carcinoma and sarcoma are not well known. Most uncertainties are related to the time patterns of cancer induction, the population specific dependencies and to the organ specific cancer induction rates. For radiotherapy treatment plan optimization these factors are irrelevant, as a treatment plan comparison is performed for a patient of specific age, sex, etc. If a treatment plan is compared relative to another one only the shape of the dose-response curve (the so called risk-equivalent dose) is of importance and errors can be minimized. © 2011 by the authors; licensee MDPI, Basel, Switzerland.


Hartmann M.,Radiotherapy Hirslanden AG | Hartmann M.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG | Schneider U.,University of Zürich
Journal of Physics: Conference Series | Year: 2014

Second cancer risk in patients, in particular in children, who were treated with radiotherapy is an important side effect. It should be minimized by selecting an appropriate treatment plan for the patient. The objectives of this study were to integrate a risk model for radiation induced cancer into a treatment planning system which allows to judge different treatment plans with regard to second cancer induction and to quantify the potential reduction in predicted risk. A model for radiation induced cancer including fractionation effects which is valid for doses in the radiotherapy range was integrated into a treatment planning system. From the three-dimensional (3D) dose distribution the 3D-risk equivalent dose (RED) was calculated on an organ specific basis. In addition to RED further risk coefficients like OED (organ equivalent dose), EAR (excess absolute risk) and LAR (lifetime attributable risk) are computed. A risk model for radiation induced cancer was successfully integrated in a treatment planning system. Several risk coefficients can be viewed and used to obtain critical situations were a plan can be optimised. Risk-volume-histograms and organ specific risks were calculated for different treatment plans and were used in combination with NTCP estimates for plan evaluation. It is concluded that the integration of second cancer risk estimates in a commercial treatment planning system is feasible. It can be used in addition to NTCP modelling for optimising treatment plans which result in the lowest possible second cancer risk for a patient. © Published under licence by IOP Publishing Ltd.


Schneider U.,Radiotherapy Hirslanden AG | Schneider U.,University of Zürich | Sumila M.,Radiotherapy Hirslanden AG | Robotka J.,Radiotherapy Hirslanden AG
Theoretical Biology and Medical Modelling | Year: 2011

Background and Purpose. Most information on the dose-response of radiation-induced cancer is derived from data on the A-bomb survivors. Since, for radiation protection purposes, the dose span of main interest is between zero and one Gy, the analysis of the A-bomb survivors is usually focused on this range. However, estimates of cancer risk for doses larger than one Gy are becoming more important for radiotherapy patients. Therefore in this work, emphasis is placed on doses relevant for radiotherapy with respect to radiation induced solid cancer. Materials and methods. For various organs and tissues the analysis of cancer induction was extended by an attempted combination of the linear-no-threshold model from the A-bomb survivors in the low dose range and the cancer risk data of patients receiving radiotherapy for Hodgkin's disease in the high dose range. The data were fitted using organ equivalent dose (OED) calculated for a group of different dose-response models including a linear model, a model including fractionation, a bell-shaped model and a plateau-dose-response relationship. Results: The quality of the applied fits shows that the linear model fits best colon, cervix and skin. All other organs are best fitted by the model including fractionation indicating that the repopulation/repair ability of tissue is neither 0 nor 100% but somewhere in between. Bone and soft tissue sarcoma were fitted well by all the models. In the low dose range beyond 1 Gy sarcoma risk is negligible. For increasing dose, sarcoma risk increases rapidly and reaches a plateau at around 30 Gy. Conclusions: In this work OED for various organs was calculated for a linear, a bell-shaped, a plateau and a mixture between a bell-shaped and plateau dose-response relationship for typical treatment plans of Hodgkin's disease patients. The model parameters ( and R) were obtained by a fit of the dose-response relationships to these OED data and to the A-bomb survivors. For any three-dimensional inhomogenous dose distribution, cancer risk can be compared by computing OED using the coefficients obtained in this work. © 2011 Schneider et al; licensee BioMed Central Ltd.


Schneider U.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG | Pedroni E.,Paul Scherrer Institute | Hartmann M.,Radiotherapy Hirslanden AG | And 2 more authors.
Zeitschrift fur Medizinische Physik | Year: 2012

Purpose: Proton radiography and tomography was investigated since the early 1970s because of its low radiation dose, high density resolution and ability to image directly proton stopping power. However, spatial resolution is still a limiting factor and as a consequence experimental methods and image reconstruction should be optimized to improve position resolution. Methods: Spatial resolution of proton radiography and tomography is given by multiple Coloumb scattering (MCS) of the protons in the patient. In this paper we employ an improved MCS model to study the impact of various proton tomographic set-ups on the spatial resolution, such as different combinations of entrance and exit coordinate and angle measurements, respectively, initial particle energy and angular confusion of the incident proton field. Results: It was found that best spatial resolution is obtained by measuring in addition to the entrance and exit coordinates also the entrance and exit angles. However, by applying partial backprojection and by using a perfect proton fan beam a sufficient spatial resolution can be achieved with less experimental complexity (measuring only exit angles). It was also shown that it is essential to use the most probable proton trajectory to improve spatial resolution. A simple straight line connection for image reconstruction results in a spatial resolution which is not clinically sufficient. The percentage deterioration of spatial resolution due to the angular confusion of the incident proton field is less than the phase space in mrad. A clinically realistic proton beam with 10 mrad angular confusion results in a less than 10% loss of spatial resolution. Conclusions: Clinically sufficient spatial resolution can be either achieved with a full measurement of entrance and exit coordinates and angles, but also by using a fan beam with small angular confusion and an exit angle measurement. It is necessary to use the most probable proton path for image reconstruction. A simple straight line connection is in general not sufficient. Increasing proton energy improves spatial resolution of an object of constant size. This should be considered in the design of proton therapy facilities. © 2011 .


Schneider U.,Radiotherapy Hirslanden AG | Schneider U.,University of Zürich | Schafer B.,Kantonsspital Baden
Radiation and Environmental Biophysics | Year: 2012

Recent findings demonstrate that accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks in cells, which escaped apoptosis due to proliferative stress. In this work, proliferative stress and inflammation-based carcinogenesis at large dose were included in a cancer induction model considering fractionation. At large dose, tissue injury due to irradiation could be so severe that under the regenerative proliferative stress induced by cell loss, the genomic unstable cells generated during irradiation and/or inflammation escape senescence or apoptosis and reenter the cell cycle, triggering enhanced carcinogenesis. This accelerationmodeled to be proportional to the number of repopulated cellsis only significant, however, when tissue injury is severe and thus proportional to the cell loss in the tissue. The general solutions to the resulting differential equations for carcinoma induction were computed. In case of full repopulation or acute low-dose irradiation, the acceleration term disappears from the equation describing cancer induction. The acceleration term is affecting the dose-response curve for carcinogenesis only at large doses. An example for bladder cancer is shown. An existing model for cancer induction after fractionated radiotherapy which is based on cell mutations was extended here by including the effects of inflammation and proliferative stress, and an additional model parameter was established which describes acceleration. The new acceleration parameter affects the dose-response model only at large dose and is only effective when the tissue is not capable of fully repopulating between dose fractions. © 2012 Springer-Verlag.


Halg R.A.,City Hospital Triemli | Besserer J.,Radiotherapy Hirslanden AG | Schneider U.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG
Medical Physics | Year: 2011

Purpose: In the clinical environment phantom materials are usually used to simulate the patient for neutron dosimetric measurements. It is not clear that the results of such phantom measurements represent the actual neutron dose in the patient. The aim of this study was to compare the difference in secondary neutron equivalent dose for different phantom materials to that in human tissue, for both proton and carbon ion radiation therapy.Methods: In order to compare the neutron equivalent dose induced by primary particles in different materials, Monte Carlo simulations were performed using the FLUKA Monte Carlo package. The scored dosimetric quantities were absorbed dose and neutron ambient dose equivalent for monoenergetic proton and carbon ion beams of clinically relevant energies. It was shown that neutron equivalent dose, for which no scoring routine exists in the current FLUKA release, can be approximated by neutron ambient dose equivalent within 4 for the investigated energies of proton and carbon ion beams.Results: The Monte Carlo simulations performed in this work showed differences in neutron ambient dose equivalent in radiation therapy phantom materials compared to ICRP soft tissue for primary proton and carbon ion beams. For Alderson soft tissue the maximum deviation was 11 for protons and 8 for carbon ions. For water the maximum deviation was 10 for protons and 9 for carbon ions. In the case of RW3 solid water, the maximum deviation compared to ICRP soft tissue was as large as 28 and 21 for protons and carbon ions, respectively.Conclusions: Alderson soft tissue and water are suitable phantom materials for neutron dosimetry for the accuracy which is achievable. When using solid water phantoms, the chemical and therefore nuclear composition of the phantom material has to be accounted for. © 2011 American Association of Physicists in Medicine.


Schneider U.,Radiotherapy Hirslanden AG | Schneider U.,University of Zürich | Besserer J.,Radiotherapy Hirslanden AG | MacK A.,Radiotherapy Hirslanden AG
Theoretical Biology and Medical Modelling | Year: 2010

Background and Purpose. A model for carcinoma and sarcoma induction was used to study the dependence of carcinogenesis after radiotherapy on fractionation. Materials and methods. A cancer induction model for radiotherapy doses including fractionation was used to model carcinoma and sarcoma induction after a radiation treatment. For different fractionation schemes the dose response relationships were obtained. Tumor induction was studied as a function of dose per fraction. Results. If it is assumed that the tumor is treated up to the same biologically equivalent dose it was found that large dose fractions could decrease second cancer induction. The risk decreases approximately linear with increasing fraction size and is more pronounced for sarcoma induction. Carcinoma induction decreases by around 10% per 1 Gy increase in fraction dose. Sarcoma risk is decreased by about 15% per 1 Gy increase in fractionation. It is also found that tissue which is irradiated using large dose fractions to dose levels lower than 10% of the target dose potentially develop less sarcomas when compared to tissues irradiated to all dose levels. This is not observed for carcinoma induction. Conclusions. It was found that carcinoma as well as sarcoma risk decreases with increasing fractionation dose. The reduction of sarcoma risk is even more pronounced than carcinoma risk. Hypofractionation is potentially beneficial with regard to second cancer induction. © 2010 Schneider et al; licensee BioMed Central Ltd.


Schneider U.,University of Zürich | Schneider U.,Radiotherapy Hirslanden AG | Stipper A.,Radiotherapy Hirslanden AG | Besserer J.,Radiotherapy Hirslanden AG
Zeitschrift fur Medizinische Physik | Year: 2010

Cancer induction after radiation therapy is a severe side effect. It is therefore of interest to predict the probability of second cancer appearance for the treated patient. Currently there is large uncertainty about the shape of the dose-response relationship for carcinogenesis for most cancer types at high dose levels. In this work a dose-response relationship for lung cancer is derived based on (i) the analysis of lung cancer induction after Hodgkin's disease,. (ii) a cancer risk model developed for high doses including fractionation based on the linear quadratic model, and. (iii) the reconstruction of treatment plans for Hodgkin's patients treated with radiotherapy. The fitted model parameters for an α/β=3 Gy were α=0.061Gy-1 and R=0.84. The value for α is in agreement with analysis of normal tissue complications of the lung after radiation therapy. The repopulation/repair parameter R is large, but seems to be characteristic for lung tissue which is sensitive with regard to fractionation. Lung cancer risk is according to this model for small doses consistent with the finding of the A-bomb survivors, has a maximum at doses of around 15 Gy and drops off only slightly at larger doses. The predicted EAR for lung after radiotherapy of Hodgkin's disease is 18.4/10000PY which can be compared to the findings of several epidemiological studies were EAR for lung varies between 9.7 and 21.5/10000PY. © 2010.


PubMed | Radiotherapy Hirslanden AG
Type: Journal Article | Journal: Radiation and environmental biophysics | Year: 2014

Recent findings demonstrate that accelerated carcinogenesis following liver regeneration is associated with chronic inflammation-induced double-strand DNA breaks in cells, which escaped apoptosis due to proliferative stress. In this work, proliferative stress and inflammation-based carcinogenesis at large dose were included in a cancer induction model considering fractionation. At large dose, tissue injury due to irradiation could be so severe that under the regenerative proliferative stress induced by cell loss, the genomic unstable cells generated during irradiation and/or inflammation escape senescence or apoptosis and reenter the cell cycle, triggering enhanced carcinogenesis. This acceleration-modeled to be proportional to the number of repopulated cells-is only significant, however, when tissue injury is severe and thus proportional to the cell loss in the tissue. The general solutions to the resulting differential equations for carcinoma induction were computed. In case of full repopulation or acute low-dose irradiation, the acceleration term disappears from the equation describing cancer induction. The acceleration term is affecting the dose-response curve for carcinogenesis only at large doses. An example for bladder cancer is shown. An existing model for cancer induction after fractionated radiotherapy which is based on cell mutations was extended here by including the effects of inflammation and proliferative stress, and an additional model parameter was established which describes acceleration. The new acceleration parameter affects the dose-response model only at large dose and is only effective when the tissue is not capable of fully repopulating between dose fractions.

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