Prog Med Phys.  2020 Dec;31(4):163-171. 10.14316/pmp.2020.31.4.163.

Improvement of Calculation Accuracy in the Electron Monte Carlo Algorithm with Optional Air Profile Measurements

• Sung J
• Jin H
• Kim J
• Park JM
• Kim Ji
• Choi CH
• Chun M

• KMID: 2510477
• DOI: http://doi.org/10.14316/pmp.2020.31.4.163

Abstract

Purpose
In this study, the accuracies of electron Monte Carlo (eMC) calculation algorithms were evaluated to determine whether electron beams were modeled by optional air profiles (APs) designed for each applicator size.
Methods
Electron beams with the energies of 6, 9, 12, and 16 MeV for VitalBeam (Varian Medical System, Palo Alto, CA, USA) and 6, 9, 12, 16, and 20 MeV for Clinac iX (Varian Medical System) were used. Optional APs were measured at the source-to-detector distance of 95 cm with jaw openings appropriate for each machine, electron beam energy, and applicator size. The measured optional APs were postprocessed and converted into the w2CAD format. Then, the electron beams were modeled and calculated with and without optional APs. Measured profiles, percentage depth doses, penumbras with respect to each machine, and energy were compared to calculated dose distributions.
Results
For VitalBeam, the profile differences between the measurement and calculation were reduced by 0.35%, 0.15%, 0.14%, and 0.38% at 6, 9, 12, and 16 MeV, respectively, when the beams were modeled with APs. For Clinac iX, the differences were decreased by 0.16%, -0.31%, 0.94%, 0.42%, and 0.74%, at 6, 9, 12, 16, and 20 MeV, respectively, with the insertion of APs. Of note, no significant improvements in penumbra and percentage depth dose were observed, although the beam models were configured with APs.
Conclusions
The accuracy of the eMC calculation can be improved in profiles when electron beams are modeled with optional APs.

Keyword

Electron Monte Carlo; Air profile measurement; Electron applicator; Beam configuration; Eclipse treatment planning system

Figure

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  Fig. 1 Schematic diagrams of the measurement setup for (a) optional air profiles and (b) verifications.

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  Fig. 2 Measured and calculated profiles with and without air profiles (APs) for VitalBeam: (a, c) in-line and (b, d) cross-line profiles at 6 and 16 MeV, respectively.

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  Fig. 3 Measured and calculated profiles with and without air profiles (APs) for Clinac iX: (a, c) in-line and (b, d) cross-line profiles at 6 and 20 MeV, respectively.

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  Fig. 4 Comparison of the measured and calculated percentage depth dose (PDD) curves with and without air profiles (Aps) and corresponding dose differences at (a) 6 and (c) 16 MeV for VitalBeam and at (b) 6 and (d) 20 MeV for Clinac iX. Calculation with AP–measurement, difference between the calculation with AP and measurement value; Calculation without AP–measurement, difference between the calculation without AP and measurement value.

Reference

References

1. Ma CMC, Chetty IJ, Deng J, Faddegon B, Jiang SB, Li J, et al. 2020; Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157. Med Phys. 47:e1–e18. DOI: 10.1002/mp.13898. PMID: 31679157.

2. Wanklyn MD, Kidane G, Crees L. 2016; Verification measurements of an eMC algorithm using a 2D ion chamber array. J Appl Clin Med Phys. 17:320–328. DOI: 10.1120/jacmp.v17i5.6150. PMID: 27685111. PMCID: PMC5874119.

3. Chetty IJ, Curran B, Cygler JE, DeMarco JJ, Ezzell G, Faddegon BA, et al. 2007; Report of the AAPM Task Group No. 105: issues associated with clinical implementation of Monte Carlo-based photon and electron external beam treatment planning. Med Phys. 34:4818–4853. DOI: 10.1118/1.2795842. PMID: 18196810.

4. Pemler P, Besserer J, Schneider U, Neuenschwander H. 2006; Evaluation of a commercial electron treatment planning system based on Monte Carlo techniques (eMC). Z Med Phys. 16:313–329. DOI: 10.1078/0939-3889-00330. PMID: 17216757.

5. Fix MK, Frei D, Volken W, Neuenschwander H, Born EJ, Manser P. 2010; Monte Carlo dose calculation improvements for low energy electron beams using eMC. Phys Med Biol. 55:4577–4588. DOI: 10.1088/0031-9155/55/16/S11. PMID: 20668339.

6. Cygler JE, Daskalov GM, Chan GH, Ding GX. 2004; Evaluation of the first commercial Monte Carlo dose calculation engine for electron beam treatment planning. Med Phys. 31:142–153. DOI: 10.1118/1.1633105. PMID: 14761030.

7. Xu Z, Walsh SE, Telivala TP, Meek AG, Yang G. 2009; Evaluation of the eclipse electron Monte Carlo dose calculation for small fields. J Appl Clin Med Phys. 10:75–85. DOI: 10.1120/jacmp.v10i3.2834. PMID: 19692969. PMCID: PMC5720559.

8. Ding GX, Duggan DM, Coffey CW, Shokrani P, Cygler JE. 2006; First macro Monte Carlo based commercial dose calculation module for electron beam treatment planning--new issues for clinical consideration. Phys Med Biol. 51:2781–2799. DOI: 10.1088/0031-9155/51/11/007. PMID: 16723766.

9. Neuenschwander H, Born EJ. 1992; A macro Monte Carlo method for electron beam dose calculations. Phys Med Biol. 37:107–125.

10. Zhang A, Wen N, Nurushev T, Burmeister J, Chetty IJ. 2013; Comprehensive evaluation and clinical implementation of commercially available Monte Carlo dose calculation algorithm. J Appl Clin Med Phys. 14:127–145. DOI: 10.1120/jacmp.v14i2.4062. PMID: 23470937. PMCID: PMC5714370.

11. Chamberland E, Beaulieu L, Lachance B. 2015; Evaluation of an electron Monte Carlo dose calculation algorithm for treatment planning. J Appl Clin Med Phys. 16:60–79. DOI: 10.1120/jacmp.v16i3.4636. PMID: 26103470. PMCID: PMC5690146.

12. Łukomska S, Kukołowicz P, Zawadzka A, Gruda M, Giżyńska M, Jankowska A, et al. 2016; Evaluation of the usefulness of the electron Monte Carlo algorithm for planning radiotherapy with the use of electron beams. Pol J Med Phys Eng. 22:49–54.

13. Jong WL, Ung NM, Tiong AHL, Rosenfeld AB, Wong JHD. 2018; Characterisation of a MOSFET-based detector for dose measurement under megavoltage electron beam radiotherapy. Radiat Phys Chem. 144:76–84.

14. Fix MK, Cygler J, Frei D, Volken W, Neuenschwander H, Born EJ, et al. 2013; Generalized eMC implementation for Monte Carlo dose calculation of electron beams from different machine types. Phys Med Biol. 58:2841–2859. DOI: 10.1088/0031-9155/58/9/2841. PMID: 23563175.

15. Ojala J, Kapanen M, Hyödynmaa S. 2016; Full Monte Carlo and measurement-based overall performance assessment of improved clinical implementation of eMC algorithm with emphasis on lower energy range. Phys Med. 32:801–811. DOI: 10.1016/j.ejmp.2016.05.005. PMID: 27189311.

16. Varian Medical Systems. 2015. Eclipse photon and electron algorithms reference guide. Varian Medical Systems;Palo Alto:

17. Shimozato T, Kojima T, Sakamoto M, Hata Y, Sasaki K, Araki N. 2012; Evaluating the output stability of LINAC with a reference detector using 3D water phantom. Igaku Butsuri. 32:176–181. PMID: 24568022.

18. Khan FM, Gibbons JP. 2014. Khan’s the physics of radiation therapy. Lippincott Williams & Wilkins;Philadelphia:

19. Brualla L, Palanco-Zamora R, Wittig A, Sempau J, Sauerwein W. 2009; Comparison between PENELOPE and electron Monte Carlo simulations of electron fields used in the treatment of conjunctival lymphoma. Phys Med Biol. 54:5469–5481. DOI: 10.1088/0031-9155/54/18/008. PMID: 19706962.

20. Edimo P, Kwato Njock MG, Vynckier S. 2013; Validation of XiO Electron Monte Carlo-based calculations by measurements in a homogeneous phantom and by EGSnrc calculations in a heterogeneous phantom. Phys Med. 29:631–638. DOI: 10.1016/j.ejmp.2012.08.004. PMID: 23010450.