Occupational exposure to ionizing radiation in medical staff: trends during the 2009-2019 period in a multicentric study.

OBJECTIVES: Health workers exposed to ionizing radiation account for + 50% of workers exposed to man-made radiation in France. Over the last decade, the use of radiation in medicine has increased due to the introduction of new practices. The EXposition des Professionnels de santE aux RayonnemenTs ioniSants study aims to evaluate and characterize the trends in radiation exposure of health workers in France between 2009 and 2019. METHODS: This retrospective study includes all health workers with at least one dosimetric record in the system for occupational dosimetry registration (Système d'information de la surveillance de l'exposition aux rayonnements ionisants) database for each of the years 2009, 2014, and 2019, in the hospitals included in the study. Individual external doses and socio-professional data were collected. Statistical analyses include descriptions, graphs, and logistic regressions. RESULTS: A total of 1457 workers were included (mean age: 39.8 years, 59% women). The average exposure significantly decreased between 2009 and 2019 (-0.008 mSv/year, p < 0.05). There were large discrepancies in trends according to professions, departments, hospitals, and gender. Over the 10-year study period, radiologic technologists and physicians were the most exposed (0.15 mSv (95%CI 0.14-0.16) and 0.13 mSv (0.06-0.21), respectively), but their exposure tended to decrease. Workers in nuclear medicine departments had the highest radiation exposure (0.36 mSv (0.33-0.39)), which remained stable over time. Thirty-eight percent of recorded doses were nonzero in 2009, decreasing to 20% in 2019. CONCLUSIONS: This study allowed to identify physicians and radiologic technologists in nuclear medicine departments as the most exposed medical workers in France, and to show an overall decrease trend in radiation exposure. This should be instructive for radiation monitoring and safety of exposed medical workers. KEY POINTS: • Radiation exposure of healthcare workers in most medical departments has steadily decreased between 2009 and 2019 in several French hospitals. • The number of zero doses consistently increased during the study period. • Workers in nuclear medicine departments are the most exposed, especially radiologic technologists and physicians.

Cohort profile: ORICAMs, a French cohort of medical workers exposed to low-dose ionizing radiation.

Medical personnel represent the largest group of workers occupationally exposed to ionizing radiation. Although the health risks associated with occupational exposure to low doses of ionizing radiation in the medical field have been investigated in several national cohorts, no study has been conducted in France to date. The ORICAMs (Occupational Radiation Induced Cancer in Medical staff) cohort is a nationwide French longitudinal cohort of medical workers exposed to ionizing radiation aiming to investigate the risk of radiation-associated cancer and non-cancer mortality. The ORICAMs cohort was set up in 2011 and includes all medical personnel monitored for ionizing radiation exposure with at least one dosimetric record in the SISERI database (the national registry for monitoring ionizing radiation exposure in workers) over the period 2002-2012. Causes of death were abstracted from death certificates and coded according to ICD-10. The follow-up ended on 31/12/2013. Standardized mortality ratios (SMRs) were calculated by cause of death to compare the mortality in the cohort to that in the French population, by gender, age group and calendar period. Among the 164,015 workers included in the cohort (60% women) a total of 1,358 deaths (892 in male and 466 in female) were reported. The observed number of all-cause deaths was significantly lower than expected based on national rates in both male (SMR = 0.35; 95% CI: 0.33, 0.38; ndeaths = 892) and female (SMR = 0.41; 95% CI: 0.38, 0.45; ndeaths = 466). This analysis leads to the conclusion that mortality in French workers exposed to medical radiation is significantly lower than the national reference rates. However, these results based on a comparative analysis with national rates may be impacted by the healthy worker effect towards low SMRs, and do not enable to establish a potential relationship between occupational exposure and mortality risk, even if we may suspect an impact of high SES of these professionals on the observed decreased mortality. Thus, further dose-response analyses based on individual ionizing radiation exposure and job's type will be conducted to characterize correlation between risk of cancer mortality and occupational exposure.

Unified description and validation of Monte Carlo simulators in PET.

Several Monte Carlo simulators are currently available for positron emission tomography (PET). Because each code has been described in a different way, it is difficult to know which one is best suited to a specific application. To help clarify the capabilities and accuracy of different codes dedicated to PET simulations, we propose a uniform description of the code features. This description specifies features pertaining to the models used for simulating the physics of PET and for describing a PET acquisition, to the acceleration strategies and to the technical characteristics of the code implementation. To assess the code accuracy, we suggest validation procedures based on NEMA phantoms involving standard physical parameters and simulation of a complex activity distribution. A test characterizing the statistical properties of detected coincidences is also described. The proposed code description and validation procedures are illustrated by considering the SimSET and PET-EGS codes. These codes differ in many features, including models for randoms and dead time, and source description. Despite these differences, both codes yielded data with properties close to those of real data. Depending on the intended application, one code might be preferred however. Indeed, only PET-EGS allows for accurate modelling of count rates while SimSET is more computationally efficient. The proposed code description and validation procedures might help determine which code is most appropriate for a specific application.