RENEB intercomparisons applying the conventional Dicentric Chromosome Assay (DCA).

PURPOSE: Two quality controlled inter-laboratory exercises were organized within the EU project 'Realizing the European Network of Biodosimetry (RENEB)' to further optimize the dicentric chromosome assay (DCA) and to identify needs for training and harmonization activities within the RENEB network. MATERIALS AND METHODS: The general study design included blood shipment, sample processing, analysis of chromosome aberrations and radiation dose assessment. After manual scoring of dicentric chromosomes in different cell numbers dose estimations and corresponding 95% confidence intervals were submitted by the participants. RESULTS: The shipment of blood samples to the partners in the European Community (EU) were performed successfully. Outside the EU unacceptable delays occurred. The results of the dose estimation demonstrate a very successful classification of the blood samples in medically relevant groups. In comparison to the 1st exercise the 2nd intercomparison showed an improvement in the accuracy of dose estimations especially for the high dose point. CONCLUSIONS: In case of a large-scale radiological incident, the pooling of ressources by networks can enhance the rapid classification of individuals in medically relevant treatment groups based on the DCA. The performance of the RENEB network as a whole has clearly benefited from harmonization processes and specific training activities for the network partners.

Review of Bayesian statistical analysis methods for cytogenetic radiation biodosimetry, with a practical example.

Classical methods of assessing the uncertainty associated with radiation doses estimated using cytogenetic techniques are now extremely well defined. However, several authors have suggested that a Bayesian approach to uncertainty estimation may be more suitable for cytogenetic data, which are inherently stochastic in nature. The Bayesian analysis framework focuses on identification of probability distributions (for yield of aberrations or estimated dose), which also means that uncertainty is an intrinsic part of the analysis, rather than an 'afterthought'. In this paper Bayesian, as well as some more advanced classical, data analysis methods for radiation cytogenetics are reviewed that have been proposed in the literature. A practical overview of Bayesian cytogenetic dose estimation is also presented, with worked examples from the literature.

CytoBayesJ: software tools for Bayesian analysis of cytogenetic radiation dosimetry data.

A number of authors have suggested that a Bayesian approach may be most appropriate for analysis of cytogenetic radiation dosimetry data. In the Bayesian framework, probability of an event is described in terms of previous expectations and uncertainty. Previously existing, or prior, information is used in combination with experimental results to infer probabilities or the likelihood that a hypothesis is true. It has been shown that the Bayesian approach increases both the accuracy and quality assurance of radiation dose estimates. New software entitled CytoBayesJ has been developed with the aim of bringing Bayesian analysis to cytogenetic biodosimetry laboratory practice. CytoBayesJ takes a number of Bayesian or 'Bayesian like' methods that have been proposed in the literature and presents them to the user in the form of simple user-friendly tools, including testing for the most appropriate model for distribution of chromosome aberrations and calculations of posterior probability distributions. The individual tools are described in detail and relevant examples of the use of the methods and the corresponding CytoBayesJ software tools are given. In this way, the suitability of the Bayesian approach to biological radiation dosimetry is highlighted and its wider application encouraged by providing a user-friendly software interface and manual in English and Russian.

A comparison of six statistical distributions for analysis of chromosome aberration data for radiation biodosimetry.

The Poisson distribution is the most widely recognised and commonly used distribution for cytogenetic radiation biodosimetry. However, it is recognised that, due to the complexity of radiation exposure cases, other distributions may be more properly applied. Here, the Poisson, gamma, negative binomial, beta, Neyman type-A and Hermite distributions are compared in terms of their applicability to 'real-life' radiation exposure situations. The identification of the most appropriate statistical model in each particular exposure situation more correctly characterises data. The results show that for acute, homogeneous (whole-body) exposures, the Poisson distribution can still give a good fit to the data. For localised partial-body exposures, the Neyman type-A model was found to be the most robust. Overall, no single distribution was found to be universally appropriate. A distribution-specific method of analysis of cytogenetic data is therefore recommended. Such an approach may lead potentially to more accurate biological dose estimates.

Cytogenetic dose-response in vitro for biological dosimetry after exposure to high doses of gamma-rays.

The dose response for dicentrics plus centric rings and total unstable chromosome-type aberrations was studied in the first mitoses of cultured human peripheral blood lymphocytes irradiated in vitro to doses of ∼2, 4, 6, 8, 10, 16 and 20 Gy of acute (60)Со gamma-rays. A dose-dependent increase of aberration yield was accompanied by a tendency to the underdispersion of dicentrics and centric rings among cells distributions compared with Poisson statistics at doses ≥6 Gy. The formal fitting of the data to a linear-quadratic model resulted in an equation with the linear and quadratic coefficients ranged 0.098-0.129×cell(-1)×Gy(-1) and 0.039-0.034×cell(-1)×Gy(-2), respectively, depending on the fitting method. The actual radiation-induced aberration yield was markedly lower than expected from a calibration curve, generated earlier within a lower dose range. Interlaboratory variations in reported dicentric yields induced by medium-to-high radiation doses in vitro are discussed.

Limitations associated with analysis of cytogenetic data for biological dosimetry.

The scientific literature concerning cytogenetic biodosimetry has been reviewed to identify the range of scenarios of radiation exposure where biodosimetry has been carried out. Limitations in the existing standardized statistical methodology have been identified and categorized, and the reasons for these limitations have been explored. Statistical problems generally occur due to either low numbers of aberrations leading to large uncertainties or deviations in aberration-per-cell distributions leading to over- or under-dispersion with respect to the Poisson model. A number of difficulties also stem from limitations of the classical statistical methodology, which requires that chromosome aberration yields be considered as something "fixed" and thus provides a deterministic estimate of radiation dose and associated confidence limits (because an assignment of a probability to an event is based solely on the observed frequency of occurrence of the event). Therefore, it is suggested that solutions to the listed problems should be based in the Bayesian framework. This will allow the investigator to take a probabilistic approach to analysis of cytogenetic data, which can be considered highly appropriate for biological dose estimation.

Delayed chromosomal instability in lymphocytes of cancer patients after radiotherapy.

PURPOSE: To assess possible delayed chromosomal instability (DCI) expressed as elevated chromatid breakage in cells containing previously formed chromosome type aberrations in cultured blood lymphocytes of cancer patients after radiotherapy (RT). MATERIALS AND METHODS: Twenty patients treated for uterine cancer with external Co(60) RT, without chemotherapy, were selected. Blood was taken before, 1-2 days after RT and one year later. Lymphocytes were cultured for 50 and 100 h. Metaphases were stained with fluorescence-plus-Giemsa and analysed for chromosome and chromatid aberrations in 1st (M1) and 3rd plus later (M3+) mitoses. RESULTS: RT caused a significant increase of radiation-specific chromosome aberrations in patients' lymphocytes together with DCI, which was observed as an excessive yield of cells containing both chromosome and chromatid aberrations (defined as C(acs&act)). This DCI passed successfully through mitoses in vitro, and at the end of RT a mean yield of 'extra' C(acs&act) was 3 x 10(-3) x cell(-1) amongst either M1 or M3+ cells. At the end of RT and one year later DCI in M1 lymphocytes appeared at random amongst patients, but some inter-individual variation was found for DCI presence in M3+ cells at both post-irradiation samplings. As time passed, the mean yield of lymphocytes exhibiting DCI decreased in vivo and one year after RT reached the pre-treatment level of 1 x 10(-3) x cell(-1). CONCLUSIONS: DCI was demonstrated in descendants of human lymphocytes after therapeutic irradiation. The effect diminished one year later, suggesting that the progeny of patients' irradiated stem cells did not produce new daughter lymphocytes exhibiting DCI during the studied post-irradiation period.