Assessing the Relative Biological Effectiveness of Neutrons across Organs of Varying Depth among the Atomic Bomb Survivors

Assessing the Relative Biological Effectiveness of Neutrons across Organs of Varying Depth among the Atomic Bomb Survivors
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DOI:
10.1667/rr15391.1
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发表时间:
2019-10-01
期刊:
影响因子:
3.4
通讯作者:
Cullings, Harry M.
Cullings, Harry M.
中科院分区:
医学3区
文献类型:
--
作者:
Cordova, Kismet A.;Cullings, Harry M.

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在评估原子弹爆炸幸存者的辐射相关风险时,建模方法的选择可能会对结果产生重要影响,然后将其用于为全世界的辐射防护标准提供信息。广岛和长崎的原子弹爆炸产生了来自两个来源的混合场辐射照射:中子和伽马射线。中子的电离密度更高,每单位吸收剂量造成的生物损伤更大,导致比伽马射线更大的相对生物有效性(RBE)。为了解释这一点,在辐射效应研究基金会的死亡率、固体癌症发病率和其他结果报告中,综合加权剂量通常计算为伽马射线剂量和10倍中子剂量的总和。此外,在这些分析中,结肠通常被选为全身代表性器官,它在体内相对较深,因此其剂量计算涉及中子的重体屏蔽和较低的中子/伽马射线比。通过增加随访和最近更新的剂量,我们使用数据驱动的方法来确定不同深度器官的最佳拟合中子RBE。生命周期研究中实体癌发病率(1958-2009)的人-年汇总表是用不同的中子和伽马射线DS 02 R1剂量为几个器官创建的,包括乳腺、脑、甲状腺、骨髓、肺、肝和结肠。使用一系列中子权重(1-250)拟合估计辐射剂量线性效应的典型超额相对风险模型,以计算每个器官的组合剂量,并比较模型偏差以评估拟合。此外,还检查了使用伽马射线和中子剂量的单独项的模型,其中中子/伽马射线线性项的比率指示RBE的最佳估计。传统加权结肠剂量的最佳拟合RBE值为80 [95%置信区间(CI):20-190],而使用加权剂量的其他器官的RBE范围为25 - 60,最佳拟合权重和置信区间宽度均随着器官深度的增加而递增。使用单独的中子和伽马射线剂量项的模型给出了与加权线性组合相似的结果,结肠的中子/伽马射线项比为79.9(95% CI:18.8-92.3)。这些结果表明,传统建模的RBE为10可能低估了中子在整个剂量范围内的影响,尽管这些更新的估计仍然有相当宽的置信区间。此外,结肠是最深的器官之一,可能不是作为单一替代器官剂量的最佳选择,因为它可能使中子的作用最小化。未来更精细的器官剂量的工作可以揭示更多关于寿命研究数据中RBE相关信息的信息。(C)2019辐射研究学会
When assessing radiation-related risk among the atomic bomb survivors, choices in modeling approach can have an important impact on the results, which are then used to inform radiation protection standards throughout the world. The atomic bombings of Hiroshima and Nagasaki produced a mixed-field radiation exposure from two sources: neutrons and gamma rays. Neutrons are more densely ionizing and cause greater biological damage per unit absorbed dose, resulting in greater relative biological effectiveness (RBE) than gamma rays. To account for this, a combined weighted dose is typically calculated as the sum of the gamma-ray dose and 10 times the neutron dose in the Radiation Effects Research Foundation's reports of mortality, solid cancer incidence and other outcomes. In addition, the colon, which is often chosen as the whole-body representative organ in these analyses, is relatively deep in the body and therefore its dose calculation involves heavy body shielding of neutrons and a low neutron/gamma-ray ratio. With added follow-up and recently updated doses, we used a data-driven approach to determine the best-fitting neutron RBE for a range of organs of varying depth. Aggregated person-year tables of solid cancer incidence (1958-2009) from the Life Span Study were created with separate neutron and gamma-ray DS02R1 doses for several organs including breast, brain, thyroid, bone marrow, lung, liver and colon. Typical excess relative risk models estimating the linear effect of radiation dose were fitted using a range of neutron weights (1-250) to calculate combined dose for each organ, and model deviances were compared to assess fit. Furthermore, models using separate terms for gamma-ray and neutron dose were also examined, wherein the ratio of the neutron/gamma-ray linear terms indicated the best estimate of the RBE. The best-fitting RBE value for the traditional weighted colon dose was 80 [95% confidence interval (CI): 20-190], while the RBEs for other organs using weighted doses ranged from 25 to 60, with the best-fitting weights and confidence interval widths both incrementally increasing with greater depth of organ. Models using separate neutron- and gamma-ray-dose terms gave similar results to weighted linear combinations, with a neutron/gamma-ray term ratio of 79.9 (95% CI: 18.8-92.3) for colon. These results indicated that the traditionally modeled RBE of 10 may underestimate the effect of neutrons across the full dose range, although these updated estimates still have fairly wide confidence bounds. Furthermore, the colon is among the deepest of organs and may not be the best choice as a single surrogate organ dose, as it may minimize the role of the neutrons. Future work with more refined organ doses could shed more light on RBE-related information available in the Life Span Study data. (C) 2019 by Radiation Research Society