Nuclear medicine is a medical specialty that uses small amounts of radioactive substances for diagnostic and therapeutic purposes, by visualizing the functioning of organs and tissues. The nuclear medicine service (NMS) performs exams that require different preparations and procedures to be followed, as well as various radionuclides, necessitating their handling and administration by the staff [1]. All requirements related to the radiological protection of Occupationally Exposed Individuals (OEIs) are defined by the NN 3.01 Standard – Basic Guidelines for Radiological Protection of the National Nuclear Energy Commission (CNEN). One way to ensure protection is through the use of dosimeters to measure the level of radiation exposure and proper shielding of sources [2]. Additionally, dose limits are defined by CNEN, and since the service works with unsealed sources, it is even more important to control the levels of radiation received by the staff [3]. Thus, through Monte Carlo simulation, the dose received by an OEI during routine activities in a nuclear medicine service, such as handling and administering radiopharmaceuticals, as well as monitoring and positioning patients for image acquisition, is determined. The radiopharmaceuticals used for the simulations were ¹⁸F-FDG, ^99mTc-MDP, and ^99mTc-Sestamibi. The scenarios are created using the 3D modeling software Blender, taking into account the anatomical position of the OEI and the patient. The individuals involved will be represented by MESH Anthropomorphic Phantoms [4] and positioned according to the regular positions of the service, which includes the necessary manipulations to enable their modeling. Using another software, the scenario is translated into the MCNP language [5]. The doses received by the OEI were determined, for each position, considering all situations during an exam, based on the activities of the employed radionuclides. The results showed the main organs irradiated, providing data for radiation protection improvements.

Acknowledgements: The authors would like to thank the Brazilian agencies CNPq (Grants 312160/2023-2 (L.P.N), 312124/2021-0 (A.P.P), 309675/2021-9 (W.S.S) and 406303/2022-3), and FAPEMIG (Grants APQ-04215-22, APQ-01254-23 and APQ-04348-23).