Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Fielding, Andrew

doi:10.1017/s1460396923000079

Cited by 11 publications

(10 citation statements)

References 92 publications

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“…It is done by sampling appropriate quantities from the probability distributions governing the individual physical processes, using machine-generated random numbers. 16 2 Nooshin Banaee et al Since MC tracks the particles until they lose their energy, the volume in which this particle tracking is done might affect the calculated dose. In routine radiotherapy workflow, the volume of the patient is obtained with the external contour, and it is usually created by automated tools of the TPSs, causing some fluctuations on the contour and consequently creating a volume that can be different compared to the real value.…”

Section: Discussionmentioning

confidence: 99%

Evaluating the performance of automated external contouring tool on dose calculation of treatment planning system

Banaee,

Aeini,

Barough

2024

J Radiother Pract

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Introduction The main goal of radiation therapy is to eradicate all cancer cells and minimize the damage to healthy tissues around the tumour. Treatment planning systems are used to predict the outcome of the treatment in terms of dose distribution prior to the treatment. One of the most reliable dose calculation algorithms is Monte Carlo. The aim of this study is to evaluate the performance of automated external contouring tool on dose calculation using Monte Carlo algorithm. Materials and methods The external contour of thorax phantom was created by automated tools of Monaco treatment planning system, and then, the IAEA-TECDOC-1583 quality assurance tests were created. Then, the treatment plans were delivered to the phantom, and the dose was measured by the Farmer ionization chamber at specific points. The external contour was corrected according to the source surface distances (SSD) which are mentioned in TECDOC-1583, and the dose was re-calculated. Finally, a comparison was made between the results. Results Dosimetric tests of TECDOC-1583 showed the errors ranged from −2·8% to +2·5%. In case of editing external contour and omitting fluctuations, the errors were decreased. The comparisons indicated that the most significant variation occurred in test 4 and the least changes were related to the tests 1 and 3. Conclusions The results of the study showed that the fluctuations of the external contour affect the calculated volume of the phantom and thus the dose. In order to obtain correct results, automated external contouring tools should be used with the correct instructions and re-checked before treatment planning.

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Section: Discussionmentioning

confidence: 99%

Evaluating the performance of automated external contouring tool on dose calculation of treatment planning system

Banaee,

Aeini,

Barough

2024

J Radiother Pract

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“…Monte Carlo simulation of the irradiation system and phasespace generation MC beam modelling of our irradiation system, comprised of a custom-made lead collimator with 10 mm diameter apertures mounted into a cell irradiator, was performed and a phase-space le was produced in the EGSnrc [15,16], BEAMnrc [17], and DOSXYZnrc codes [18]. Veri cation of the simulations has been performed to ensure reliability of our MC modelled irradiation system for all irradiation conditions.…”

Section: Methodsmentioning

confidence: 99%

“…To create the MC mouse phantom model, the mouse image set (in DICOM format) was converted to a "egsphant" le (BEAMnrc-based phantom le [17]) (Fig. 1) using STATDOSE code (EGSnrc-based code [18,19]). According to the CT numbers in the image set, each voxel in the MC mouse phantom represents a particular type of mouse tissue with its associated electron density.…”

Section: Monte Carlo Mouse Phantommentioning

confidence: 99%

In-silico evaluation of the effect of set-up errors on dose delivery during mouse irradiations with a cell irradiator-based collimator system

Entezam

Fielding

Ratnayake

et al. 2023

Preprint

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Set-up errors are a problem for pre-clinical irradiators that lack imaging capabilities. The aim of this study was to investigate the impact of the potential set-up errors on the dose distribution for a mouse with a xenographic tumour irradiated with a Gammacell irradiator equipped with an in-house lead collimator with 10 mm diameter apertures. The EGSnrc Monte-Carlo (MC) code was used to simulate the potential errors caused by displacements of the mouse in the irradiation setup. The impact of the simulated set-up displacements on the dose delivered to the xenographic tumour and surrounding organs was assessed. MC dose calculations were performed in a Computed Tomography (CT) derived model of the mouse for the reference position of the tumour in the irradiation setup. The errors were added into the CT data and then the mouse doses for the corresponding shifts were recalculated and dose volume histograms (DVHs) were generated. The investigation was performed for 1 cm and 0.5 cm diameter tumours. The DVH resulting from introducing the maximum setup errors for 1 cm diameter tumours showed up to 35% reduced dose to a significant fraction of the tumour volume. The setup errors demonstrated an insignificant effect on doses for 0.5 cm diameter tumour irradiations. Setup errors were observed to have negligible impact on out of field doses to organs at risk. The dosimetric results presented herein verify the robustness of our collimator system for irradiations of xenograft tumours up to 0.5 cm diameter in the presence of the maximum setup errors.

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“…To overcome the difficulties of the measurements, numerical simulations with Monte Carlo (MC) codes would allow a detailed analysis of each component of mixed fields with the aim to compensate for the lack of the precision in measurements. [9][10][11][12] The aim of this study is to calculate different neutron contamination parameters such as neutron fluence, neutron absorbed dose, and neutron equivalent dose in small 18 MV photon fields by MC MCNPX simulation and compare those created in presence of circular cones.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Comparison of neutron contamination in small photon fields of secondary collimator jaws and circular cones

Banaee,

Goodarzi,

Hosseinzadeh

2023

J Radiother Pract

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Introduction: Advanced treatment modalities involve applying small fields which might be shaped by collimators or circular cones. In these techniques, high-energy photons produce unwanted neutrons. Therefore, it is necessary to know neutron parameters in these techniques. Materials and methods: Different parts of Varian linac were simulated by MCNPX, and different neutron parameters were calculated. The results were then compared to photoneutron production in the same nominal fields created by circular cones. Results: Maximum neutron fluence for 1 × 1, 2 × 2, 3 × 3 cm2 field sizes was 165, 40.4, 19.78 (cm–2.Gy-1 × 106), respectively. The maximum values of neutron equivalent doses were 17.1, 4.65, 2.44 (mSv/Gy of photon dose) for 1 × 1, 2 × 2, 3 × 3 cm2 field size, respectively, and maximum neutron absorbed doses reached 903, 253, 131 (µGy/Gy photon dose) for 1 × 1, 2 × 2, 3 × 3 cm2 field sizes, respectively. Conclusion: Comparing the results with those in the presence of circular cones showed that circular cones reduce photoneutron production for the same nominal field sizes.

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Monte-Carlo techniques for radiotherapy applications I: introduction and overview of the different Monte-Carlo codes

Cited by 11 publications

References 92 publications

Evaluating the performance of automated external contouring tool on dose calculation of treatment planning system

Evaluating the performance of automated external contouring tool on dose calculation of treatment planning system

In-silico evaluation of the effect of set-up errors on dose delivery during mouse irradiations with a cell irradiator-based collimator system

Comparison of neutron contamination in small photon fields of secondary collimator jaws and circular cones

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