RENEB Inter-Laboratory comparison 2017: limits and pitfalls of ILCs

Abstract Purpose In case of a mass-casualty radiological event, there would be a need for networking to overcome surge limitations and to quickly obtain homogeneous results (reported aberration frequencies or estimated doses) among biodosimetry laboratories. These results must be consistent within such network. Inter-laboratory comparisons (ILCs) are widely accepted to achieve this homogeneity. At the European level, a great effort has been made to harmonize biological dosimetry laboratories, notably during the MULTIBIODOSE and RENEB projects. In order to continue the harmonization efforts, the RENEB consortium launched this intercomparison which is larger than the RENEB network, as it involves 38 laboratories from 21 countries. In this ILC all steps of the process were monitored, from blood shipment to dose estimation. This exercise also aimed to evaluate the statistical tools used to compare laboratory performance. Materials and methods Blood samples were irradiated at three different doses, 1.8, 0.4 and 0 Gy (samples A, C and B) with 4-MV X-rays at 0.5 Gy min−1, and sent to the participant laboratories. Each laboratory was requested to blindly analyze 500 cells per sample and to report the observed frequency of dicentric chromosomes per metaphase and the corresponding estimated dose. Results This ILC demonstrates that blood samples can be successfully distributed among laboratories worldwide to perform biological dosimetry in case of a mass casualty event. Having achieved a substantial harmonization in multiple areas among the RENEB laboratories issues were identified with the available statistical tools, which are not capable to advantageously exploit the richness of results of a large ILCs. Even though Z- and U-tests are accepted methods for biodosimetry ILCs, setting the number of analyzed metaphases to 500 and establishing a tests’ common threshold for all studied doses is inappropriate for evaluating laboratory performance. Another problem highlighted by this ILC is the issue of the dose-effect curve diversity. It clearly appears that, despite the initial advantage of including the scoring specificities of each laboratory, the lack of defined criteria for assessing the robustness of each laboratory’s curve is a disadvantage for the ‘one curve per laboratory’ model. Conclusions Based on our study, it seems relevant to develop tools better adapted to the collection and processing of results produced by the participant laboratories. We are confident that, after an initial harmonization phase reached by the RENEB laboratories, a new step toward a better optimization of the laboratory networks in biological dosimetry and associated ILC is on the way.AFRRI’s-RBB44313 y AFR-B4-431

Multiparametric radiobiological assays show that variation of X-ray energy strongly impacts relative biological effectiveness: comparison between 220 kV and 4 MV

International audienceBased on classic clonogenic assay, it is accepted by the scientific community that, whatever the energy, the relative biological effectiveness of X-rays is equal to 1. However, although X-ray beams are widely used in diagnosis, interventional medicine and radiotherapy, comparisons of their energies are scarce. We therefore assessed in vitro the effects of low- and high-energy X-rays using Human umbilical vein endothelial cells (HUVECs) by performing clonogenic assay, measuring viability/mortality, counting γ-H2AX foci, studying cell proliferation and cellular senescence by flow cytometry and by performing gene analysis on custom arrays. Taken together, excepted for γ-H2AX foci counts, these experiments systematically show more adverse effects of high energy X-rays, while the relative biological effectiveness of photons is around 1, whatever the quality of the X-ray beam. These results strongly suggest that multiparametric analysis should be considered in support of clonogenic assay

Twenty-two years later: Consistent dose estimation of an accidental overexposure by retrospective biological dosimetry

International audienceAs the chromosomal translocation rate increases with age in the non-exposed population, the translocation-based dose estimation of an external radiation exposure victim needs to take into consideration such background. We sought to retrospectively estimate the dose of exposure of a victim from the Lilo radiological accident in Georgia twenty-two years afterwards and compare it to the original biological dosimetry-based dose calculation performed in our laboratory. Similar types of studies have retrospectively estimated a radiation dose, notably involving victims of the Chernobyl, Goiânia and Tammiku accidents [1][2][3]. Nevertheless, their estimations were done after shorter periods of time post-exposure and in some cases, the exposure might not have been exclusively of an external nature [1][2].In this study, we used Fluorescence In Situ Hybridization (FISH) to detect and score chromosomal translocations in lymphocytes from a recent blood sample of the victim. We performed the analysis using our laboratory’s updated FISH dose-effect curve and taking into account translocation data from a large panel of unexposed individuals. We found the mean exposure dose to be similar to the original assessment obtained by the dicentric chromosome assay (DCA) more than 22 years ago. Furthermore, the confidence interval from the DCA analysis was contained within our FISH confidence interval, which as expected, was slightly larger. Altogether these observations confirm a comparable dose estimation.In conclusion, retrospective biological dosimetry by FISH allowed us to estimate a dose that is consistent with the original assessment 22 years prior. This suggests that our current dose-effect curve could be used for relative dose estimations long time after external exposure

Analysis Methods for the preservation of Bologna Municipal Palace \u2013 Metodi di analisi per il restauro del palazzo Comunale di Bologna

Preservation requires a deep understanding of the artefact, using critical awareness to guide every intervention, from conservation to functional updating. Within the study of the complex organism of the Municipal Palace of Bologna, historic seat of political power, the deepening into the architectural history of the XIII-century reveals the opportunity to experience complex methods of analysis, which integrate a variety of direct and indirect readings. The highly articulated score of the fa\ue7ade shows an intimate superposition of various traces, openings, consolidations, extensions, floor divisions, turning the leitmotiv of a diachronic reconstruction of the entire artifact portion. The analysis of the results of trilaterations, laser scans, building site and notarial documents, drawings, literature sources, all is systematized elaborating a diachronic matrix of archaeological inspiration. Such results enable the interpretation of the unknown signs with physical and chronological relations up to reveal historical passages and constructive vulnerability, without invasive methods: each sign reveals itself as precious testimony, and it is compulsory to be enhanced by aware preservatio

Dosimetry for cell irradiation using orthovoltage (40-300 kv) x-ray facilities

International audienceNowadays, the importance of dosimetry protocols and formalisms for radiobiology studies is no longer to be demonstrated. Several protocols were proposed for dose determination on low energy X-rays facilities, but depending on irradiation configurations, samples, materials or beam quality, it is sometimes difficult to know which protocol is the most appropriate. Here, we proposed a new dosimetry protocol for cell irradiations on a low energy X-rays facility. The aim of this method is to perform the dose estimation at the level of the cell monolayer so as close as possible to the real cell irradiation conditions. The different steps of the protocol are the following: i) determination of irradiation parameters (high voltage, intensity, cell container….), ii) determination of the beam quality index (high voltage – half value layer couple), iii) Dose rate measurement with ionization chamber calibrated in air kerma in free in air conditions, iv) quantification of the attenuation of the cell culture medium with EBT3 radiochromic films, v) determination of the dose rate at the cell level. This methodology has to be performed for each new cell irradiation configuration as the modification of only one parameter can strongly impact the real dose deposition at the level of cell monolayer especially considering low energy X-rays

New Bayesian contributions to radiation dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven or suspected radiation exposure. On the one hand, dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of proven radiation exposure. In this context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what were the estimated absorbed dose and its associated uncertainty?" and 2) "Was the radiation exposure total or partial?" On the other hand, dose estimation from dicentric counts can also be crucial to clarify unclear radiation exposure scenarios. In this context, one important additional question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems. Bayesian statistical approaches have also been recently proposed but, up to our knowledge, they do not allow answering question 3) and do not highlight clearly the pros and cons of using Bayesian statistics in biological retrospective dosimetry. Finally, no consensus has been reached so far on the best way to proceed to answer the above questions. In this work, we propose an alternative approach - based on the full Bayesian inference of a Poisson mixture model – that allows providing, in a unique and coherent framework, some rich probabilistic answers to the above three questions, simultaneously. Using simulation studies and cytogenetic data from real radiation accident victims and suspected exposed individuals, we highlight the pros and cons of using Bayesian statistics in biological retrospective dosimetry. A sensitivity analysis to the prior choice on the unknown quantities (e.g., the dose) is performed. Our work show that the benefits from using our Bayesian Poisson mixture model are more pronounced for small doses than for high doses

A Bayesian Poisson mixture model for model selection and dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven radiation accidents. In this specific context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what are the estimated absorbed dose and its associated uncertainty?"and 2) "Was the radiation exposure total or partial?" Dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of radiation exposure. Moreover, dose estimation from dicentric counts can be crucial to clarify unclear radiation exposure scenarios. In this context, one important question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems but no consensus has been reached so far on the best way to proceed. In this work, we propose an alternative approach based on the Bayesian inference of a Poisson mixture model. This approach allows providing, in a unique and coherent framework, some rich and simultaneous probabilistic answers to the above three questions. Particularly, our mixture model is used as a Bayesian model selection tool that is relevant to answer questions 2) and 3). A specific adaptive Metropolis-Hastings algorithm was implemented to avoid potential convergence difficulties when estimating the mixture weights. Using simulation studies and cytogenetic data from real radiation accident victims, we discuss the advantages of the proposed Bayesian approach compared to the classical ones. A sensitivity analysis to the prior choice on the unknown dose and the mixture weights was also performed

A Bayesian Poisson mixture model for model selection and dose estimation in biological retrospective dosimetry

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven radiation accidents. In this specific context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what are the estimated absorbed dose and its associated uncertainty?"and 2) "Was the radiation exposure total or partial?" Dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of radiation exposure. Moreover, dose estimation from dicentric counts can be crucial to clarify unclear radiation exposure scenarios. In this context, one important question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems but no consensus has been reached so far on the best way to proceed. In this work, we propose an alternative approach based on the Bayesian inference of a Poisson mixture model. This approach allows providing, in a unique and coherent framework, some rich and simultaneous probabilistic answers to the above three questions. Particularly, our mixture model is used as a Bayesian model selection tool that is relevant to answer questions 2) and 3). A specific adaptive Metropolis-Hastings algorithm was implemented to avoid potential convergence difficulties when estimating the mixture weights. Using simulation studies and cytogenetic data from real radiation accident victims, we discuss the advantages of the proposed Bayesian approach compared to the classical ones. A sensitivity analysis to the prior choice on the unknown dose and the mixture weights was also performed

Bayesian contributions to radiation dose estimation in biological retrospective dosimetry.

International audienceScoring of dicentric chromosome aberrations in peripheral blood lymphocytes is considered to be the "gold-standard" biological method to estimate the radiation dose received by individuals after proven or suspected radiation exposure. On the one hand, dose estimation is highly relevant to optimize patient-centered care and predict the health consequences of proven radiation exposure. In this context, two main questions arise: 1) "Given the number of dicentrics observed in some blood lymphocytes of a given individual, what were the estimated absorbed dose and its associated uncertainty?" and 2) "Was the radiation exposure total or partial?" On the other hand, dose estimation from dicentric counts can also be crucial to clarify unclear radiation exposure scenarios. In this context, one important additional question is: 3) "Given the number of dicentrics observed, was the individual really exposed to ionizing radiation?" Frequentist statistical approaches are commonly used to answer the above questions that are then formalized as hypotheses testing and inverse regression problems. Bayesian statistical approaches have also been recently proposed but, up to our knowledge, they do not allow answering question 3) and do not highlight clearly the pros and cons of using Bayesian statistics in biological retrospective dosimetry. Finally, no consensus has been reached so far on the best way to proceed to answer the above questions. In this work, we propose an alternative approach - based on the full Bayesian inference of a Poisson mixture model – that allows providing, in a unique and coherent framework, some rich probabilistic answers to the above three questions, simultaneously. Using simulation studies and cytogenetic data from real radiation accident victims and suspected exposed individuals, we highlight the pros and cons of using Bayesian statistics in biological retrospective dosimetry. A sensitivity analysis to the prior choice on the unknown quantities (e.g., the dose) is performed. Our work show that the benefits from using our Bayesian Poisson mixture model are more pronounced for small doses than for high doses