Comparison of experimental measurements and fast Monte Carlo simulations for typical set-ups in fluoroscopically-guided interventional procedures

PyMCGPU-IR is an application based on the Monte Carlo code MCGPU-IR that automatically retrieves procedure information from X-ray systems and medical worker positions from a tracking camera system. PyMCGPU-IR calculates personal dose equivalent values, doses in organs and effective dose values for both patient and medical staff in interventional radiology procedures and displays them visually. The code's main advantage lies in its time efficiency, enabling simulations in under 2 min with statistical uncertainties below 5% (k = 2). This study involved testing in a hospital room using an interventional X-ray system. A RANDO phantom simulated the patient, with passive dosimeters affixed to the back for measuring skin dose values. A PMMA slab phantom represented the operator, with passive and active dosimeters affixed to its front surface to measure Hp(10). The irradiation conditions were simulated with PyMCGPU-IR using voxelized geometries to represent both phantoms. Results demonstrate good agreement between PyMCGPU-IR simulations and measured patient skin dose values, with differences of up to 5% for mean skin dose and up to 14% for the peak skin dose. Concerning Hp(10) values on the operator phantom, PyMCGPU-IR calculated values fall within the uncertainty ranges of dosimeter measurements for most points. The highest Hp(10) discrepancy is 42%, which is acceptable when compared with the typical variability observed between active and passive personal dosimeters measurements in interventional radiology. The results demonstrate PyMCGPU-IR's satisfactory performance for patient and personal dosimetry, compared to existing solutions like commercial skin dose calculation software and personal physical dosimeters. •Computational dosimetry for radiation exposure in patients and medical staff during medical interventions.•Monte Carlo methods for radiation modelling, calculating equivalent, organ and effective doses in medical scenarios.•Improve time efficiency in Monte Carlo simulations using GPUs.