Reconstructing Hanford worker external doses from photons for epidemiology

The accurate reconstruction of external photon doses is essential for credible radiation epidemiology. This article presents the methodology used to derive dose estimates for 37 012 Hanford Site workers included in the Million Person Study. The approach employs historical dose records from the Hanford Radiation Exposure database and a previous epidemiology study. Bias correction factors specific to dosimeter type and period of use were applied and missing annual doses were estimated using a hierarchical nearby method to estimate deep dose equivalent for each worker. For early years with limited detection sensitivity, missed doses were quantified based on expected time-period-specific, low-dose statistical distributions. The revised dose estimates resulted in lower median and mean career doses than unadjusted data, while increasing the number of person-years with nonzero dose. Sensitivity analyses assessed the influence of bias in dosimetry measurements, missed doses and gap years on dose estimates. Differences in cumulative dose estimates between unadjusted and revised annual estimates are most prominent in the early operational years due to the highest bias during that time period.

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Publication Details

Journal
Journal of Radiological Protection
Published
2025-09-23
DOI
https://doi.org/10.1088/1361-6498/ae0a59
Citations
3
Primary Topic
Radiation Dose and Imaging
Type
article
Field-Weighted Citation Impact
4.08
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article

Reconstructing Hanford worker external doses from photons for epidemiology

Caleigh Samuels, David J. Girardi, Ashley P. Golden, Helen A. Grogan et al.
3 citations
Journal of Radiological Protection
Radiation Dose and Imaging
4.08
article

Reconstructing Hanford worker external doses from photons for epidemiology

Caleigh Samuels, David J. Girardi, Ashley P. Golden, Helen A. Grogan, Lawrence T. Dauer, Michael Bellamy, Sara C. Howard
article en
3 citations

Abstract

The accurate reconstruction of external photon doses is essential for credible radiation epidemiology. This article presents the methodology used to derive dose estimates for 37 012 Hanford Site workers included in the Million Person Study. The approach employs historical dose records from the Hanford Radiation Exposure database and a previous epidemiology study. Bias correction factors specific to dosimeter type and period of use were applied and missing annual doses were estimated using a hierarchical nearby method to estimate deep dose equivalent for each worker. For early years with limited detection sensitivity, missed doses were quantified based on expected time-period-specific, low-dose statistical distributions. The revised dose estimates resulted in lower median and mean career doses than unadjusted data, while increasing the number of person-years with nonzero dose. Sensitivity analyses assessed the influence of bias in dosimetry measurements, missed doses and gap years on dose estimates. Differences in cumulative dose estimates between unadjusted and revised annual estimates are most prominent in the early operational years due to the highest bias during that time period.

Journal of Radiological ProtectionVol. 45(4)
Oak Ridge Associated Universities (US), Oak Ridge National Laboratory (US), Memorial Sloan Kettering Cancer Center (US), Oregon State University Cascades (US)
Openalex Percentile: Top 6%
Radiation Dose and Imaging
4.08
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Reconstructing Hanford worker external doses from photons for epidemiology — Caleigh Samuels, David J. Girardi, et al. · Journal of Radiological Protection (2025) | TGRS Research Map | TGRS