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基于扩展个人剂量监测(EPR)的俄罗斯乌拉尔地区居民外照射剂量计算不确定性验证。

EPR-based uncertainty validation of the calculated external doses for population exposed in the urals region.

机构信息

Biophys. Lab., Urals Research Center for Radiation Medicine, 68A Vorovsky Str., 454124, Chelyabinsk, Russia.

Department of Radiation Biology, Chelyabinsk State University, 129 Bratiev Kashirinykh Str., 454001, Chelyabinsk, Russia.

出版信息

Radiat Prot Dosimetry. 2023 Sep 18;199(14):1586-1590. doi: 10.1093/rpd/ncac238.

DOI:10.1093/rpd/ncac238
PMID:37721077
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10505940/
Abstract

Tooth enamel Electron Paramagnetic Resonance (EPR) spectroscopy was used as a method for external dosimetry in the territories contaminated in the 1950s by PA 'Mayak' (Urals region) to validate the mean dose estimates predicted by the Techa River Dosimetry System (TRDS). The purpose of this study is to validate the uncertainties of TRDS doses. Ninety percent confidence intervals (90% confidence interval, CI) of dose estimated with both methods were compared for 220 people. All data were grouped according to the width of 90%CI, viz.: (1) 90%CI of EPR-based dose ≤  90%CI of TRDS prediction (38 cases); (2) 90%CI of EPR-based dose >  90%CI of TRDS prediction (182 cases). About 91% of 90%CIs overlap. In group 1, 100% cases overlap. In group 2, 80% of the cases were non-contradictive (the calculated 90%CI is completely within the measured one). Interval comparison of doses predicted retrospectively and estimated based on individual measurements are non-contradictory and demonstrate a good agreement.

摘要

利用牙釉质电子顺磁共振(EPR)波谱法作为 20 世纪 50 年代被 PA“玛雅克”(乌拉尔地区)污染地区外部剂量测定的方法,验证捷克斯洛伐克河剂量测定系统(TRDS)预测的平均剂量估计值。本研究旨在验证 TRDS 剂量的不确定性。对 220 人用两种方法估算的剂量的 90%置信区间(90%置信区间,CI)进行了比较。所有数据均根据 90%CI 的宽度进行分组,即:(1)基于 EPR 的剂量 90%CI≤TRDS 预测的 90%CI(38 例);(2)基于 EPR 的剂量 90%CI>TRDS 预测的 90%CI(182 例)。约 91%的 90%CI 重叠。在第 1 组中,100%的病例重叠。在第 2 组中,80%的病例无矛盾(计算的 90%CI 完全在测量值内)。回顾性预测的剂量与基于个体测量的估计剂量的区间比较没有矛盾,表明两者具有良好的一致性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/57a6ee9fc5c0/ncac238f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/a18cda8930af/ncac238f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/cb1b521d7b11/ncac238f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/57a6ee9fc5c0/ncac238f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/a18cda8930af/ncac238f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/cb1b521d7b11/ncac238f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/13cd/10505940/57a6ee9fc5c0/ncac238f3.jpg

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Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors.使用具有共享误差的蒙特卡洛剂量测定系统校正超额相对风险模型中的置信区间。
PLoS One. 2017 Apr 3;12(4):e0174641. doi: 10.1371/journal.pone.0174641. eCollection 2017.
3
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