Fast Monte Carlo codes for occupational dosimetry in interventional radiology

Balcaza, Víctor García; Camp, Anna; Badal, Andreu; Andersson, Martin; Almén, Anja; Ginjaume, M.; Duch, M.A.

doi:10.1016/j.ejmp.2021.05.012

Cited by 11 publications

(4 citation statements)

References 39 publications

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“…MCGPU-IR was also developed for the calculation of operator's dose in fluoroscopically guided procedures [13]. It is an extension of the original MC-GPU, which also added the possibility to automatically simulate several irradiation events, thus providing the total organ doses together with the individual results for each event.…”

Section: Pymcgpu-irmentioning

confidence: 99%

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

et al. 2022

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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.

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Section: Pymcgpu-irmentioning

confidence: 99%

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

et al. 2022

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“…In order to compare calculated values with experimental ones, a normalisation to absolute values is required for each irradiation event. The normalisation factor is obtained from the ratio between experimental and simulated air kerma at a reference point [31]. The experimental air kerma was calculated using the KAP value which is a direct measurement using a physical KAP-meter located at the x-ray tube.…”

Section: Simulated Dose Per Procedures Using Monte-carlo Toolsmentioning

confidence: 99%

“…In the framework of PODIUM project, penEasy was modified to automate the calculation of personal dose equivalent, and the new program was named penEasyIR. PENELOPE/penEasyIR [31] provides the calculation of personal dose equivalent (H p (10), H p (0.07) and H p (3)) from the simulated photon fluence spectrum at a point in air. The geometry used is shown in figure 3.…”

Section: Penelope/peneasyirmentioning

confidence: 99%

Feasibility study of computational occupational dosimetry: evaluating a proof-of-concept in an endovascular and interventional cardiology setting

et al. 2022

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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 (ALARA). 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: development of an online dosimetry application based on computer simulations without physical dosimeters. Occupational doses were calculated based on camera tracking devices, flexible individualized 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 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 show acceptable differences of the order of 40% between calculated and measured staff doses, 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 of PODIUM. The availability of an online personal dosimetry application has the potential to overcome problems associated with 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 operation in a hospital setting. However, an early prototype system has been tested in a clinical setting and the results from this two-year proof-of-concept PODIUM project are promising for future development.

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“…MC‐GPU has already been employed for simulating some applications involving low‐energy (X‐ray) beams, for example, breast imaging studies and virtual clinical trials 10,11 and coherent X‐ray scattering 12 by adapting the code to include molecular interference 13 . Original and modified MC‐GPU codes were also validated for applications in interventional radiology and cardiology 14,15 . MC‐GPU was also adapted for patient‐specific CT dose calculations 16 .…”

Section: Introductionmentioning

confidence: 99%

Technical note: MC‐GPU breast dosimetry validations with other Monte Carlo codes and phase space file implementation

Massera

Thomson

2021

Medical Physics

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To validate the MC-GPU Monte Carlo (MC) code for dosimetric studies in X-ray breast imaging modalities: mammography, digital breast tomosynthesis, contrast enhanced digital mammography, and breast-CT. Moreover, to implement and validate a phase space file generation routine. Methods: The MC-GPU code (v. 1.5 DBT) was modified in order to generate phase space files and to be compatible with PENELOPE v. 2018 derived cross-section database. Simulations were performed with homogeneous and anthropomorphic breast phantoms for different breast imaging techniques. The glandular dose was computed for each case and compared with results from the PENELOPE (v. 2014) + penEasy (v. 2015) and egs_brachy (EGSnrc) MC codes. Afterward, several phase space files were generated with MC-GPU and the scored photon spectra were compared between the codes.The phase space files generated in MC-GPU were used in PENELOPE and EGSnrc to calculate the glandular dose, and compared with the original dose scored in MC-GPU. Results: MC-GPU showed good agreement with the other codes when calculating the glandular dose distribution for mammography, mean glandular dose for digital breast tomosynthesis, and normalized glandular dose for breast-CT. The latter case showed average/maximum relative differences of 2.3%/27%, respectively, compared to other literature works, with the larger differences observed at low energies (around 10 keV). The recorded photon spectra entering a voxel were similar (within statistical uncertainties) between the three MC codes. Finally, the reconstructed glandular dose in a voxel from a phase space file differs by less than 0.65%, with an average of 0.18%-0.22% between the different MC codes, agreement within approximately 2𝜎 statistical uncertainties. In some scenarios, the simulations performed in MC-GPU were from 20 up to 40 times faster than those performed by PENELOPE. Conclusions:The results indicate that MC-GPU code is suitable for breast dosimetric studies for different X-ray breast imaging modalities, with the advantage of a high performance derived from GPUs. The phase space file implementation was validated and is compatible with the IAEA standard, allowing multiscale MC simulations with a combination of CPU and GPU codes.

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Fast Monte Carlo codes for occupational dosimetry in interventional radiology

Cited by 11 publications

References 39 publications

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

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

Feasibility study of computational occupational dosimetry: evaluating a proof-of-concept in an endovascular and interventional cardiology setting

Technical note: MC‐GPU breast dosimetry validations with other Monte Carlo codes and phase space file implementation

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