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. 2023 Jul 25;28(3):416-428.
doi: 10.5603/RPOR.a2023.0044. eCollection 2023.

Optimal values of the Electron Monte Carlo dose engine parameters

Jacek Wendykier  1 , Ewa Wojtyna  2 , Barbara Bekman  1 , Adam Bekman  3 , Bożena Woźniak  3 , Beata Niewiadomska  3 , Joanna Prażmowska  3 , Piotr Wendykier  4 , Marcin Bieniasiewicz  5 , Aleksandra Grządziel  1
Affiliations

Optimal values of the Electron Monte Carlo dose engine parameters

Jacek Wendykier et al. Rep Pract Oncol Radiother. .

Abstract

Background: The aim of this study was to indicate the most favorable - in terms of to the time of calculation and the uncertainty of determining the dose distribution - values of the parameters for the Electron Monte Carlo (eMC) algorithm in the Eclipse treatment planning system.

Materials and methods: Using the eMC algorithm and the variability of the values of its individual parameters, calculations of the electron dose distribution in the full-scattering virtual water phantom were performed, obtaining percentage depth doses, beam profiles, absolute dose values in points and calculation times. The reference data included water tank measurements such as relative dose distributions and absolute point doses.

Results: For 63 sets of calculation data created from selected values of the parameters for the eMC algorithm, calculation times were analyzed and the absolute calculated and measured doses were compared. Performing a statistical analysis made it possible to determine whether the differences in the values of deviations between the actual dose and the calculated dose in individual regions of the percentage depth dose curve and the beam profile are statistically significant between the analyzed sets of parameters.

Conclusions: Taking into account obtained results from the analysis of the discrepancy between the distribution of the calculated and measured dose, the correspondence of the absolute value of the calculated and measured dose and the duration of the calculation of the dose distribution, the optimal set of parameters was indicated for the eMC algorithm which allows obtaining the dose distribution and the number of monitor units in an acceptable time.

Keywords: Electron Monte Carlo algorithm; calculation time; uncertainty of dose determination.

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Conflict of interest statement

Conflicts of interest The authors have no conflict of interest to declare.

Figures

Figure 1
Figure 1
Graphical representation of the calculation time as a function of statistical uncertainty values, error bars denote 2 standard deviations (SD)
Figure 2
Figure 2
Beam profile as the statistical uncertainty (SU) function for 6 MeV at dmax for 10 × 10 cm2 applicator (normalization in the beam axis intentionally done so that the profiles do not obscure each other and noise becomes visible)
Figure 3
Figure 3
The percent depth dose (PDD) curves of the electron beam dose with marked areas where deviations between calculations and measurements are compared. A tenfold increased gradient for the PDDs are also shown. Graphs for energies of 6 MeV (top panel) and 22 MeV (bottom panel) are presented
Figure 4
Figure 4
Beam profile with marked regions where deviations between calculations and measurements are compared using different tolerance values
See this image and copyright information in PMC

References

    1. Mijnheer BJ, Battermann JJ, Wambersie A. What degree of accuracy is required and can be achieved in photon and neutron therapy? Radiother Oncol. 1987;8(3):237–252. doi: 10.1016/s0167-8140(87)80247-5. - DOI - PubMed
    1. Dutreix A. When and how can we improve precision in radiotherapy? Radiother Oncol. 1984;2(4):275–292. doi: 10.1016/s0167-8140(84)80070-5. - DOI - PubMed
    1. Malicki J, Ślosarek K. Planowanie leczenia i dozymetria w radioterapii. 2nd ed. Via Medica; Gdańsk: 2016.
    1. Seco J, Verhaegen F. Monte Carlo Techniques in Radiation Therapy. 1st ed. CRC Press; 2016.
    1. Matuszak N. [Monte Carlo jako jedna z metod symulacyjnych w radioterapii]. Lett Oncol Sci. 2019;16(2):15–22. doi: 10.21641/los.2019.17.2.91.. - DOI

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