Thorium Bioassay of Miners Revisited.

• Tác giả: Marcus Cattani, Gregory Stanley Hewson, Martin Ian Ralph
• Ngôn ngữ: eng
• Thông tin xuất bản: England : Journal of radiological protection : official journal of the Society for Radiological Protection , 2025
• Bộ sưu tập: NCBI
• ID: 726414

Tóm tắt

This study aimed to revisit previous in-vitro thorium studies on workers and reevaluate their significance against the current International Commission on Radiological Protection (ICRP) models for thorium intake. Thorium concentrations in the urine and blood serum of Western Australian mineral sands workers had previously been interpreted using biokinetic models recommended by the ICRP. These findings revealed significant inconsistencies with those of other monitoring methods, including in-vivo lung counting and personal air sampling. Data on thorium concentrations in the urine and blood serum of workers and their exposure records were extracted from the previously published research and assessed using the Taurus internal dosimetry software application. Inhalation intake parameters such as aerosol particle size and lung solubility were selected to reflect the chronic intake of relatively insoluble mineral sands dust. The literature values for the urinary excretion of thorium by other thorium-exposed workers were also reviewed. Internal dosimetry modelling highlights the sensitivity of urinary thorium excretion as a function of the dust particle size distribution and particle dissolution rate. The timing of urine sample collection is particularly critical during the early years of chronic intake, especially in certain work rosters. The significantly lower urinary thorium concentrations predicted for chronic intake of Type S thorium compounds highlight the need for sensitive analytical techniques for bioassays and a better understanding of non-occupational (environmental) intake. Current ICRP biokinetic models applied to urinary thorium concentrations reported for mineral sands workers and other thorium-exposed workers infer that past doses are likely to be underestimated and are now significant. .