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半自动着丝粒评分系统在职业照射辐射暴露的甄别和监测中的应用。

Application of a semi-automated dicentric scoring system in triage and monitoring occupational radiation exposure.

机构信息

Laboratory of Biological Dosimetry, National Radiation Emergency Medical Center, Korea Institute of Radiological and Medical Sciences, Seoul, South Korea.

Department of Biomedical Laboratory Science, College of Medical Sciences, Soonchunhyang University, Asan, South Korea.

出版信息

Front Public Health. 2022 Oct 20;10:1002501. doi: 10.3389/fpubh.2022.1002501. eCollection 2022.

Abstract

The dicentric chromosome assay (DCA) is considered the gold standard for radiation biodosimetry, but it is limited by its long dicentric scoring time and need for skilled scorers. The automation of scoring dicentrics has been considered a strategy to overcome the constraints of DCA. However, the studies on automated scoring methods are limited compared to those on conventional manual DCA. Our study aims to assess the performance of a semi-automated scoring method for DCA using and irradiated samples. Dose estimations of 39 blind samples irradiated and 35 industrial radiographers occupationally exposed were estimated using the manual and semi-automated scoring methods and subsequently compared. The semi-automated scoring method, which removed the false positives of automated scoring using the dicentric chromosome (DC) scoring algorithm, had an accuracy of 94.9% in the irradiated samples. It also had more than 90% accuracy, sensitivity, and specificity to distinguish binary dose categories reflecting clinical, diagnostic, and epidemiological significance. These data were comparable to those of manual DCA. Moreover, Cohen's kappa statistic and McNemar's test showed a substantial agreement between the two methods for categorizing samples into never and ever radiation exposure. There was also a significant correlation between the two methods. Despite of comparable results with two methods, lower sensitivity of semi-automated scoring method could be limited to assess various radiation exposures. Taken together, our findings show the semi-automated scoring method can provide accurate dose estimation rapidly, and can be useful as an alternative to manual DCA for biodosimetry in large-scale accidents or cases to monitor radiation exposure of radiation workers.

摘要

着丝粒染色体分析(DCA)被认为是辐射生物剂量学的金标准,但由于其着丝粒评分时间长且需要熟练的评分员,因此受到限制。自动评分着丝粒已被认为是克服 DCA 限制的一种策略。然而,与传统的手动 DCA 相比,自动评分方法的研究还很有限。我们的研究旨在使用 和 照射的样本评估 DCA 的半自动评分方法的性能。使用手动和半自动评分方法对 39 个盲样( 和 )和 35 个职业暴露于 的工业放射技师进行剂量估计,随后进行比较。半自动评分方法使用着丝粒(DC)评分算法去除自动评分的假阳性,在 照射的样本中的准确率为 94.9%。它还具有超过 90%的准确率、灵敏度和特异性,可区分反映临床、诊断和流行病学意义的二进制剂量类别。这些数据与手动 DCA 相当。此外,Cohen's kappa 统计量和 McNemar 检验表明,两种方法在将 样本分类为从未接触过和曾接触过辐射方面具有实质性的一致性。两种方法之间也存在显著相关性。尽管两种方法的结果相当,但半自动评分方法的灵敏度较低,可能限制了其对各种辐射暴露的评估。总之,我们的研究结果表明,半自动评分方法可以快速提供准确的剂量估计,并且可以作为手动 DCA 的替代方法,用于大规模事故或监测放射工作人员辐射暴露的情况下的生物剂量学。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2dcb/9631783/ca3d51a99194/fpubh-10-1002501-g0001.jpg

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