Radiation Dose Estimation by Completely Automated Interpretation of the Dicentric Chromosome Assay

Abstract

Accuracy of the automated dicentric chromosome (DC) assay relies on metaphase image selection. This study validates a software framework to find the best image selection models that mitigate inter-sample variability. Evaluation methods to determine model quality include the Poisson goodness-of-fit of DC distributions for each sample, residuals after calibration curve fitting and leave-one-out dose estimation errors. The process iteratively searches a pool of selection model candidates by modifying statistical and filter cutoffs to rank the best candidates according to their respective evaluation scores. Evaluation scores minimize the sum of squared errors relative to the actual radiation dose of the calibration samples. For one laboratory, the minimum score for the curve fit residual method was 0.0475 Gy 2 , compared to 1.1975 Gy 2 without image selection. Application of optimal selection models using samples of unknown exposure produced estimated doses within 0.5 Gy of physical dose. Model optimization standardizes image selection among samples and provides relief from manual DC scoring, improving accuracy and consistency of dose estimation.

Estimating partial-body ionizing radiation exposure by automated cytogenetic biodosimetry

“…The impact of the residual FPs is minimal when both calibration and test samples are processed using the same algorithm, resulting in the equivalent levels of FP misclassification in all images, regardless of source. This effectively mitigates their effect on dose estimation (Li et al 2019). Dose estimation accuracy is therefore unaffected, and results fulfill IAEA criteria for triage biodosimetry.…”

“…All test samples were derived from whole-body (WB) exposures, except for PHE, which provided four WB and three partial-body (PB) irradiated samples. Except for HC and CNL (Li et al 2019), transfer of metaphase image data was performed via secured internet connection using Synology Cloud Station software to a centralized Network Attached Storage device at the University of Western Ontario. Results for each laboratory were separated, and images were grouped by sample dose.…”

“…ADCI generates calibration curves and estimates exposure levels of samples of uncertain dose. ADCI can process a sample of 500 metaphase images and estimate dose in ~3-5 minutes using a multicore desktop computer system (Intel i7-6700HQ, 16Gb RAM) equipped with a graphics processing unit (GPU; Nvidia® GTX 960M or RTX 2070) (Li et al 2019).…”

Meeting radiation dosimetry capacity requirements of population-scale exposures by geostatistical sampling

“…The proposed approach may partially overcome capacity resource limitations of first responders and biodosimetry laboratories to provide data for triage assessment of entire populations. Laboratory contexts, where sample preparation, imaging and DCA can be highly automated and multiplexed may have sufficient throughput [10,35,38]. Field sampling, laboratory and computational resources could be amplified through simultaneous deployment of multiple dedicated teams.…”

“…Meanwhile, biological exposure to ionizing radiation can be assessed using dicentric chromosomes (DCs), as their frequency correlates with the radiation dose in a linear quadratic manner [4,5]. Recent advancements in automated DC analysis have reduced the time required to accurately determine biological radiation exposures [6][7][8][9][10]). Nevertheless, sample preparation steps continue to introduce latency in the overall procedure, precluding comprehensive assessment of large populations.…”