RENEB Inter-Laboratory Comparison 2021: The Gene Expression Assay.

Early and high-throughput individual dose estimates are essential following large-scale radiation exposure events. In the context of the Running the European Network for Biodosimetry and Physical Dosimetry (RENEB) 2021 exercise, gene expression assays were conducted and their corresponding performance for dose-assessment is presented in this publication. Three blinded, coded whole blood samples from healthy donors were exposed to 0, 1.2 and 3.5 Gy X-ray doses (240 kVp, 1 Gy/min) using the X-ray source Yxlon. These exposures correspond to clinically relevant groups of unexposed, low dose (no severe acute health effects expected) and high dose exposed individuals (requiring early intensive medical health care). Samples were sent to eight teams for dose estimation and identification of clinically relevant groups. For quantitative reverse transcription polymerase chain reaction (qRT-PCR) and microarray analyses, samples were lysed, stored at 20°C and shipped on wet ice. RNA isolations and assays were run in each laboratory according to locally established protocols. The time-to-result for both rough early and more precise later reports has been documented where possible. Accuracy of dose estimates was calculated as the difference between estimated and reference doses for all doses (summed absolute difference, SAD) and by determining the number of correctly reported dose estimates that were defined as ±0.5 Gy for reference doses <2.5 Gy and ±1.0 Gy for reference doses >3 Gy, as recommended for triage dosimetry. We also examined the allocation of dose estimates to clinically/diagnostically relevant exposure groups. Altogether, 105 dose estimates were reported by the eight teams, and the earliest report times on dose categories and estimates were 5 h and 9 h, respectively. The coefficient of variation for 85% of all 436 qRT-PCR measurements did not exceed 10%. One team reported dose estimates that systematically deviated several-fold from reported dose estimates, and these outliers were excluded from further analysis. Teams employing a combination of several genes generated about two-times lower median SADs (0.8 Gy) compared to dose estimates based on single genes only (1.7 Gy). When considering the uncertainty intervals for triage dosimetry, dose estimates of all teams together were correctly reported in 100% of the 0 Gy, 50% of the 1.2 Gy and 50% of the 3.5 Gy exposed samples. The order of dose estimates (from lowest to highest) corresponding to three dose categories (unexposed, low dose and highest exposure) were correctly reported by all teams and all chosen genes or gene combinations. Furthermore, if teams reported no exposure or an exposure >3.5 Gy, it was always correctly allocated to the unexposed and the highly exposed group, while low exposed (1.2 Gy) samples sometimes could not be discriminated from highly (3.5 Gy) exposed samples. All teams used FDXR and 78.1% of correct dose estimates used FDXR as one of the predictors. Still, the accuracy of reported dose estimates based on FDXR differed considerably among teams with one team's SAD (0.5 Gy) being comparable to the dose accuracy employing a combination of genes. Using the workflow of this reference team, we performed additional experiments after the exercise on residual RNA and cDNA sent by six teams to the reference team. All samples were processed similarly with the intention to improve the accuracy of dose estimates when employing the same workflow. Re-evaluated dose estimates improved for half of the samples and worsened for the others. In conclusion, this inter-laboratory comparison exercise enabled (1) identification of technical problems and corrections in preparations for future events, (2) confirmed the early and high-throughput capabilities of gene expression, (3) emphasized different biodosimetry approaches using either only FDXR or a gene combination, (4) indicated some improvements in dose estimation with FDXR when employing a similar methodology, which requires further research for the final conclusion and (5) underlined the applicability of gene expression for identification of unexposed and highly exposed samples, supporting medical management in radiological or nuclear scenarios.

Inter-laboratory comparison of gene expression biodosimetry for protracted radiation exposures as part of the RENEB and EURADOS WG10 2019 exercise.

Large-scale radiation emergency scenarios involving protracted low dose rate radiation exposure (e.g. a hidden radioactive source in a train) necessitate the development of high throughput methods for providing rapid individual dose estimates. During the RENEB (Running the European Network of Biodosimetry) 2019 exercise, four EDTA-blood samples were exposed to an Iridium-192 source (1.36 TBq, Tech-Ops 880 Sentinal) at varying distances and geometries. This resulted in protracted doses ranging between 0.2 and 2.4 Gy using dose rates of 1.5-40 mGy/min and exposure times of 1 or 2.5 h. Blood samples were exposed in thermo bottles that maintained temperatures between 39 and 27.7 °C. After exposure, EDTA-blood samples were transferred into PAXGene tubes to preserve RNA. RNA was isolated in one laboratory and aliquots of four blinded RNA were sent to another five teams for dose estimation based on gene expression changes. Using an X-ray machine, samples for two calibration curves (first: constant dose rate of 8.3 mGy/min and 0.5-8 h varying exposure times; second: varying dose rates of 0.5-8.3 mGy/min and 4 h exposure time) were generated for distribution. Assays were run in each laboratory according to locally established protocols using either a microarray platform (one team) or quantitative real-time PCR (qRT-PCR, five teams). The qRT-PCR measurements were highly reproducible with coefficient of variation below 15% in ≥ 75% of measurements resulting in reported dose estimates ranging between 0 and 0.5 Gy in all samples and in all laboratories. Up to twofold reductions in RNA copy numbers per degree Celsius relative to 37 °C were observed. However, when irradiating independent samples equivalent to the blinded samples but increasing the combined exposure and incubation time to 4 h at 37 °C, expected gene expression changes corresponding to the absorbed doses were observed. Clearly, time and an optimal temperature of 37 °C must be allowed for the biological response to manifest as gene expression changes prior to running the gene expression assay. In conclusion, dose reconstructions based on gene expression measurements are highly reproducible across different techniques, protocols and laboratories. Even a radiation dose of 0.25 Gy protracted over 4 h (1 mGy/min) can be identified. These results demonstrate the importance of the incubation conditions and time span between radiation exposure and measurements of gene expression changes when using this method in a field exercise or real emergency situation.

Effects of Radiation Exposure on the Cost-Effectiveness of CT Angiography and Perfusion Imaging in Aneurysmal Subarachnoid Hemorrhage.

BACKGROUND AND PURPOSE: CT angiography and perfusion imaging is an important prognostic tool in the management of patients with aneurysmal subarachnoid hemorrhage. The purpose of this study was to perform a cost-effectiveness analysis of advanced imaging in patients with SAH, incorporating the risks of radiation exposure from CT angiography and CT perfusion imaging. MATERIALS AND METHODS: The risks of radiation-induced brain cancer and cataracts were incorporated into our established decision model comparing the cost-effectiveness of CT angiography and CT perfusion imaging and transcranial Doppler sonography in SAH. Cancer risk was calculated by using National Cancer Institute methodology. The remaining input probabilities were based on literature data and a cohort at our institution. Outcomes were expected quality-adjusted life years gained, costs, and incremental cost-effectiveness ratios. One-way, 2-way, and probabilistic sensitivity analyses were performed. RESULTS: CT angiography and CT perfusion imaging were the dominant strategies, resulting in both better health outcomes and lower costs, even when incorporating brain cancer and cataract risks. Our results remained robust in 2-way sensitivity analyses varying the prolonged latency period up to 30 years, with either brain cancer risk up to 50 times higher than the upper 95% CI limit or the probability of cataracts from 0 to 1. Results were consistent for scenarios that considered either symptomatic or asymptomatic patients with SAH. Probabilistic sensitivity analysis confirmed our findings over a broad range of selected input parameters. CONCLUSIONS: While risks of radiation exposure represent an important consideration, CT angiography and CT perfusion imaging remained the preferred imaging compared with transcranial Doppler sonography in both asymptomatic and symptomatic patients with SAH, with improved health outcomes and lower health care costs, even when modeling a significantly higher risk and shorter latency period for both cataract and brain cancer than that currently known.

Effect of dose rate on residual γ-H2AX levels and frequency of micronuclei in X-irradiated mouse lymphocytes.

The biological risks associated with low-dose-rate (LDR) radiation exposures are not yet well defined. To assess the risk related to DNA damage, we compared the yields of two established biodosimetry end points, γ-H2AX and micronuclei (MNi), in peripheral mouse blood lymphocytes after prolonged in vivo exposure to LDR X rays (0.31 cGy/min) vs. acute high-dose-rate (HDR) exposure (1.03 Gy/min). C57BL/6 mice were total-body irradiated with 320 kVP X rays with doses of 0, 1.1, 2.2 and 4.45 Gy. Residual levels of total γ-H2AX fluorescence in lymphocytes isolated 24 h after the start of irradiation were assessed using indirect immunofluorescence methods. The terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay was used to determine apoptotic cell frequency in lymphocytes sampled at 24 h. Curve fitting analysis suggested that the dose response for γ-H2AX yields after acute exposures could be described by a linear dependence. In contrast, a linear-quadratic dose-response shape was more appropriate for LDR exposure (perhaps reflecting differences in repair time after different LDR doses). Dose-rate sparing effects (P < 0.05) were observed at doses ≤2.2 Gy, such that the acute dose γ-H2AX and TUNEL-positive cell yields were significantly larger than the equivalent LDR yields. At the 4.45 Gy dose there was no difference in γ-H2AX expression between the two dose rates, whereas there was a two- to threefold increase in apoptosis in the LDR samples compared to the equivalent 4.45 Gy acute dose. Micronuclei yields were measured at 24 h and 7 days using the in vitro cytokinesis-blocked micronucleus (CBMN) assay. The results showed that MNi yields increased up to 2.2 Gy with no further increase at 4.45 Gy and with no detectable dose-rate effect across the dose range 24 h or 7 days post exposure. In conclusion, the γ-H2AX biomarker showed higher sensitivity to measure dose-rate effects after low-dose LDR X rays compared to MNi formation; however, confounding factors such as variable repair times post exposure, increased cell killing and cell cycle block likely contributed to the yields of MNi with accumulating doses of ionizing radiation.

A new view of radiation-induced cancer.

Biologically motivated mathematical models are important for understanding the mechanisms of radiation-induced carcinogenesis. Existing models fall into two categories: (1) short-term formalisms, which focus on the processes taking place during and shortly after irradiation (effects of dose, radiation quality, dose rate and fractionation), and (2) long-term formalisms, which track background cancer risks throughout the entire lifetime (effects of age at exposure and time since exposure) but make relatively simplistic assumptions about radiation effects. Grafting long-term mechanisms on to short-term models is badly needed for modelling radiogenic cancer. A combined formalism was developed and applied to cancer risk data in atomic bomb survivors and radiotherapy patients and to background cancer incidence. The data for nine cancer types were described adequately with a set of biologically meaningful parameters for each cancer. These results suggest that the combined short-long-term approach is a potentially promising method for predicting radiogenic cancer risks and interpreting the underlying biological mechanisms.