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PyMCGPU-IR is an innovative occupational dose monitoring tool for interventional radiology procedures. It reads the radiation data from the Radiation Dose Structured Report of the procedure and combines this information with the position of the monitored worker recorded using a 3D camera system. This information is used as an input file for the fast Monte Carlo radiation transport code MCGPU-IR in order to assess the organ doses, Hp(10) and Hp(0.07), as well as the effective dose. In this study, Hp(10) measurements of the first operator during an endovascular aortic aneurysm repair procedure and a coronary angiography using a ceiling suspended shield are compared to PyMCGPU-IR calculations. Differences in the two reported examples are found to be within 15%, which is considered as being very satisfactory. The study highlights the promising advantages of PyMCGPU-IR, although there are still several improvements that need to be implemented before its final clinical use., Peer Reviewed, Postprint (published version)

This study presents the performance of two fast Monte Carlo codes, PENELOPE/penEasyIR and MCGPU-IR in order to assess operator doses in interventional radiology. In particular, it aims to validate the calculations when workers are protected with shielding located between the patient and the operator. The experiments are performed in a calibration laboratory and measurements are gathered using Thermo EPD and Mirion DMC personal active dosemeters. Calculation efficiency of the fast Monte Carlo codes is approximately four orders of magnitude greater than for a standard Monte Carlo code. Satisfactory agreement between measurements and calculations is shown., This work was partially supported by EJP-CONCERT for 2014–2018 (662287); the Ministerio de Economía y Competitividad (PCIN-2017-044); and the Spanish Nuclear Safety Council through project EDOCI and the ‘Cátedra Argos’., Objectius de Desenvolupament Sostenible::3 - Salut i Benestar, Postprint (author's final draft)

Individual monitoring of radiation workers is essential to ensure compliance with legal dose limits and to ensure that doses are As Low As Reasonably Achievable. However, large uncertainties still exist in personal dosimetry and there are issues with compliance and incorrect wearing of dosimeters. The objective of the PODIUM (Personal Online Dosimetry Using Computational Methods) project was to improve personal dosimetry by an innovative approach: the development of an online dosimetry application based on computer simulations without the use of physical dosimeters. Occupational doses were calculated based on the use of camera tracking devices, flexible individualised phantoms and data from the radiation source. When combined with fast Monte Carlo simulation codes, the aim was to perform personal dosimetry in real-time. A key component of the PODIUM project was to assess and validate the methodology in interventional radiology workplaces where improvements in dosimetry are needed. This paper describes the feasibility of implementing the PODIUM approach in a clinical setting. Validation was carried out using dosimeters worn by Vascular Surgeons and Interventional Cardiologists during patient procedures at a hospital in Ireland. Our preliminary results from this feasibility study show acceptable differences of the order of 40% between calculated and measured staff doses, in terms of the personal dose equivalent quantity Hp(10), however there is a greater deviation for more complex cases and improvements are needed. The challenges of using the system in busy interventional rooms have informed the future needs and applicability of PODIUM. The availability of an online personal dosimetry application has the potential to overcome problems that arise from the use of current dosimeters. In addition, it should increase awareness of radiation protection among staff. Some limitations remain and a second phase of development would be required to bring the PODIUM method into ope, Peer Reviewed, Postprint (published version)

Interventional radiology techniques cause radiation exposure both to patient and personnel. The radiation dose to the operator is usually measured with dosimeters located at specific points above or below the lead aprons. The aim of this study is to develop and validate two fast Monte Carlo (MC) codes for radiation transport in order to improve the assessment of individual doses in interventional radiology. The proposed methodology reduces the number of required dosemeters and provides immediate dose results., Peer Reviewed, Objectius de Desenvolupament Sostenible::3 - Salut i Benestar, Postprint (published version)

Introduction: Interventional procedures are associated with potentially high radiation doses to the skin. The 2013/59/EURATOM Directive establishes that the equipment used for interventional radiology must have a device or a feature informing the practitioner of relevant parameters for assessing patient dose at the end of the procedure. Monte Carlo codes of radiation transport are considered to be one of the most reliable tools available to assess doses. However, they are usually too time consuming for use in clinical practice. This work presents the validation of the fast Monte Carlo code MC-GPU for application in interventional radiology. Methodologies: MC-GPU calculations were compared against the well-validated Monte Carlo simulation code PENELOPE/penEasy by simulating the organ dose distribution in a voxelized anthropomorphic phantom. In a second phase, the code was compared against thermoluminescent measurements performed on slab phantoms, both in a calibration laboratory and at a hospital. Results: The results obtained from the two simulation codes show very good agreement, differences in the output were within 1%, whereas the calculation time on the MC-GPU was 2500 times shorter. Comparison with measurements is of the order of 10%, within the associated uncertainty. Conclusions: It has been verified that MC-GPU provides good estimates of the dose when compared to PENELOPE program. It is also shown that it presents very good performance when assessing organ doses in very short times, less than one minute, in real clinical set-ups. Future steps would be to simulate complex procedures with several projections., Peer Reviewed, Objectius de Desenvolupament Sostenible::3 - Salut i Benestar, Postprint (published version)