PyMCGPU-IR Monte Carlo code test for occupational dosimetry.

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.

Validation of organ dose calculations with PyMCGPU-IR in realistic interventional set-ups.

INTRODUCTION: Interventional radiology procedures are associated with high skin dose exposure. 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. This work presents and validates PyMCGPU-IR, a patient dose monitoring tool for interventional cardiology and radiology procedures based on MC-GPU. MC-GPU is a freely available Monte Carlo (MC) code of photon transport in a voxelized geometry which uses the computational power of commodity Graphics Processing Unit cards (GPU) to accelerate calculations. METHODOLOGIES: PyMCGPU-IR was validated against two different experimental set-ups. The first one consisted of skin dose measurements for different beam angulations on an adult Rando Alderson anthropomorphic phantom. The second consisted of organ dose measurements in three clinical procedures using the Rando Alderson phantom. RESULTS: The results obtained for the skin dose measurements show differences below 6%. For the clinical procedures the differences are within 20% for most cases. CONCLUSIONS: PyMCGPU-IR offers both, high performance and accuracy for dose assessment when compared with skin and organ dose measurements. It also allows the calculation of dose values at specific positions and organs, the dose distribution and the location of the maximum doses per organ. In addition, PyMCGPU-IR overcomes the time limitations of CPU-based MC codes.

Can 3D Gamified Simulations Be Valid Vocational Training Tools for Persons with Intellectual Disability? An Experiment Based on a Real-life Situation.

OBJECTIVE: To investigate if 3D gamified simulations can be valid vocational training tools for persons with intellectual disability. METHODS: A 3D gamified simulation composed by a set of training tasks for cleaning in hostelry was developed in collaboration with professionals of a real hostel and pedagogues of a special needs school. The learning objectives focus on the acquisition of vocabulary skills, work procedures, social abilities and risk prevention. Several accessibility features were developed to make the tasks easy to do from a technological point-of-view. A pilot experiment was conducted to test the pedagogical efficacy of this tool on intellectually disabled workers and students. RESULTS: User scores in the gamified simulation follow a curve of increasing progression. When confronted with reality, they recognized the scenario and tried to reproduce what they had learned in the simulation. Finally, they were interested in the tool, they showed a strong feeling of immersion and engagement, and they reported having fun. CONCLUSIONS: On the basis of this experiment we believe that 3D gamified simulations can be efficient tools to train social and professional skills of persons with intellectual disabilities contributing thus to foster their social inclusion through work.