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A severe irradiation accident involving a victim occurred in April 2009 in South America. The victim has found a 192Ir source fallen from a gammagraphy device and has put it in the left pocket of his pants. Very quickly, an erythema and a blister appeared on the left leg of the victim involving hospitalisation. Following the request of the IAEA assistance, the Ionizing Radiation Dosimetry Laboratory of IRSN was asked to perform a numerical dosimetric reconstruction. A personalised voxel phantom of the victim has been constructed thanks to the Simulation of External Source Accident with Medical images tool developed by the laboratory, and a calculation of the dose with the MCNPX computer code allowed to determine the boundary of the necrotic dose at 25 Gy. On the basis of these calculations, the physicians have performed exeresis of the necrotic region on the left leg on 4 May 2009. Associated with mesenchymal stem cell injection, the leg of the victim was healthy on December 2009. [ABSTRACT FROM PUBLISHER]

Radiation overexposure accidents are rare but can have severe health consequences. Evaluating the dose received by the patient is a crucial step in the medical management. For that purpose, for more than 15 years, IRSN has been developing an in-house tool named SESAME for the numerical reconstruction of radiological accidents due to external sources. Recently, two new functionalities were implemented in SESAME to allow accurate reconstructions of interventional radiology (IR) overexposures. The experimental validation of SESAME for the reconstruction of overexposures in IR is presented. First, an anthropomorphic dummy equipped with dosemeters was irradiated following conditions similar to a fluoroscopically guided interventional procedure. Then the procedure was simulated using SESAME. Finally measured doses were compared to calculated doses. Even with a limited amount of data available, SESAME can provide valuable dose information for the medical team in charge of the patient, such as skin dose mapping and dose distribution in depth., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

A parameter uncertainty analysis has been performed to derive the probability distribution of the weighted equivalent dose to lung for an adult (w(lung) H(lung)) per unit exposure to radon progeny in the home. The analysis was performed using the ICRP Publication 66 human respiratory tract model (HRTM) with tissue weighting factor for the lung, w(lung) = 0.12 and the radiation weighting factor for alpha particles, wR = 20. It is assumed that the HRTM is a realistic representation of the physical and biological processes, and that the parameter values are uncertain. The parameter probability distributions used in the analysis were based on a combination of experimental results and expert judgement from several prominent European scientists. The assignment of the probability distributions describing the uncertainty in the values of the assigned fractions (ABB, Abb, AAI) of the tissue weighting factor proved difficult in practice due to lack of quantitative data. Because of this several distributions were considered. The results of the analysis give a mean value of w(lung) H(lung) per unit exposure to radon progeny in the home of 15 mSv per working level month (WLM) for a population. For a given radon gas concentration, the mean value of w(lung) H(lung) per unit exposure is 13 mSv per 200 Bq.m(-3).y of 222Rn. Parameters characterising the distributions of w(lung) H(lung) per unit exposure are given. If the ICRP weighting factors are fixed at their default values (ABB, Abb, AAI = 0.333, 0.333, 0.333; w(lung) = 0.12; and wr = 20) then on the basis of this uncertainty analysis it is extremely unlikely (P approximately 0.0007) that a value of Hw/Pp for exposure in the home is as low as 4 mSv per WLM, the value determined with the epidemiological approach. Even when the uncertainties in the ABB, Abb, AAI, values are included then this probability is predicted to be between 0.01 to 0.08 depending upon the distribution assumed for describing the uncertainties in the ABB, Abb, AAI, values. Thus, it is concluded that the uncertainties in the HRTM parameters considered in this study cannot totally account for the discrepancy between the dosimetric and epidemiological approaches.