1. Sarrut D, Bardiès M, Boussion N, et al. (2014) A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications. Med Phys, 41(6): 064301. [DOI:10.1118/1.4871617] [PMID]

2. Papadimitroulas P (2017) Dosimetry applications in GATE Monte Carlo toolkit. Phys Med, 41: 136-140. [DOI:10.1016/j.ejmp.2017.02.005] [PMID]

3. Slimani FAA, Hamdi M, Bentourkia MH (2018) G4DARI: Geant4/GATE based Monte Carlo simulation interface for dosimetry calculation in radiotherapy. Comput Med Imaging Graph, 67: 30-39. [DOI:10.1016/j.compmedimag.2018.04.008] [PMID]

4. Krieger T and Sauer OA (2005) Monte Carlo-versus pencil-beam-/collapsed-cone-dose calculation in a heterogeneous multi-layer phantom. Phys Med Biol, 50(5): 859-68. [DOI:10.1088/0031-9155/50/5/010] [PMID]

5. Zaman A, Kakakhel MB, Hussain A (2019) A comparison of Monte Carlo, anisotropic analytical algorithm (AAA) and Acuros XB algorithms in assessing dosimetric perturbations during enhanced dynamic wedged radiotherapy deliveries in heterogeneous media. J Radiother Pract, 18(1): 75-81. [DOI:10.1017/S1460396918000262]

6. Lee B, Jeong S, Chung K, et al. (2019) Feasibility of a GATE Monte Carlo platform in a clinical pretreatment QA system for VMAT treatment plans using TrueBeam with an HD120 multileaf collimator. J Appl Clin Med Phys, 20(10): 101-10. [DOI:10.1002/acm2.12718] [PMID] []

7. Nahum AE (1999) Condensed-history Monte-Carlo simulation for charged particles: what can it do for us? Radiat Environ Biophys, 38(3): 163-173. [DOI:10.1007/s004110050152] [PMID]

8. Andreo P (1991) Monte Carlo techniques in medical radiation physics. Phys Med Biol, 36(7): 861. [DOI:10.1088/0031-9155/36/7/001] [PMID]

9. Nahum A (2007) Monte-Carlo based patient dose computation. Handbook of Radiotherapy Physics: Theory and Practice. Taylor & Francis, Inglaterra. [DOI:10.1201/9781420012026.ch28]

10. Mostaar A, Alahverdi M, Shahriari M (2003) Application of MCNP4C Monte Carlo code in radiation dosimetry in heterogeneous phantom. Int J Radiat Res, 1: 143-149.

11. Elcim Y, Dirican B, Yavas O (2018) Dosimetric comparison of pencil beam and Monte Carlo algorithms in conformal lung radiotherapy. J Appl Clin Med Phys, 199(5): 616-624. [DOI:10.1002/acm2.12426] [PMID] []

12. Thiam C O, Breton V, Donnarieix D, et al. (2008) Validation of a dose deposited by low-energy photons using GATE/GEANT4. Phys Med Biol, 53(11): 3039-55. [DOI:10.1088/0031-9155/53/11/019] [PMID]

13. Visvikisa D, Bardiesb M, Chiavassab S, et al. (2006) Use of the GATE Monte Carlo package for dosimetry applications. Nucl, 569(2): 335-340. [DOI:10.1016/j.nima.2006.08.049]

14. Brualla L, Rodriguez M, Lallena AM (2017) Monte Carlo systems used for treatment planning and dose verification. Strahlenther Onkol, 193(4): 243-259. [DOI:10.1007/s00066-016-1075-8] [PMID]

15. Byrnes K, Ford A, Bennie N (2019) Verification of the Elekta Monaco TPS Monte Carlo in modelling radiation transmission through metals in a water equivalent phantom. Phys Eng Sci Med, 42(2): 639-45. [DOI:10.1007/s13246-019-00749-2] [PMID]

16. Santin G, Strul D, Lazaro D, et al. (2003) GATE: A Geant4-based simulation platform for PET and SPECT integrating movement and time management. IEEE Trans Nucl Sci, 50(5): 1516-1521. [DOI:10.1109/TNS.2003.817974]

17. Jan S, Santin G, Strul D, et al. (2004) GATE: a simulation toolkit for PET and SPECT. Phys Med Biol, 49(19): 4543-61. [DOI:10.1088/0031-9155/49/19/007] [PMID] []

18. Abolaban FA and Taha EM (2020) Representation and illustration of the initial parameters in GATE 8.1 Monte Carlo simulation of an Elekta Versa-HD linear accelerator. J Radiat Res Appl Sc, 13(1): 642-7. [DOI:10.1080/16878507.2020.1820271]

19. Grevillot L, Frisson T, Maneval D, et al. (2011) Simulation of a 6 MV Elekta Precise Linac photon beam using GATE/GEANT4. Phys Med Biol, 56(4): 903-18. [DOI:10.1088/0031-9155/56/4/002] [PMID]

20. Jan S, Benoit D, Becheva E, et al. (2011) GATE V6: a major enhancement of the GATE simulation platform enabling modelling of CT and radiotherapy. Phys Med Biol, 56(4): 881-901. [DOI:10.1088/0031-9155/56/4/001] [PMID]

21. GATE (2017) GATE User's Guide Version: GATE 8.0. OpenGATE Collaboration http://www.opengatecollaboration.org/UsersGuide; March 2017

22. Shalek RJ (1977) Determination of absorbed dose in a patient irradiated by beams of X or gamma rays in radiotherapy procedures. Med Phys, 4(5): 461. [DOI:10.1118/1.594356]

23. Hasenbalg F, Neuenschwander H, Mini R, Born EJ (2007) Collapsed cone convolution and analytical anisotropic algorithm dose calculations compared to VMC++ Monte Carlo simulations in clinical cases. Phys Med Biol, 52(13): 3679- 369. [DOI:10.1088/0031-9155/52/13/002] [PMID]

24. Reis QM, Nicolucci P, Fortes SS, Silva LP (2019) Effects of heterogeneities in dose distributions under nonreference conditions: Monte Carlo simulation vs dose calculation algorithms. Med Dosim, 44(1): 74-82. [DOI:10.1016/j.meddos.2018.02.009] [PMID]

25. Najafzadeh M, Nickfarjam A, Jabbari K, et al. (2019) Dosimetric verification of lung phantom calculated by collapsed cone convolution: A Monte Carlo and experimental evaluation. J Xray Sci Technol, 27(1): 161-175. [DOI:10.3233/XST-180425] [PMID]

26. Yavuzkanat N and Kürem HBS (2020) Monte Carlo Simulation of the Gamma-Ray Transmissions for the newly Designed Shielding Blocks used in Radiotherapy. J Adv Res, 6(2): 364-77. https://doi.org/10.28979/jarnas.844955 [DOI:10.28979/comufbed.753299]

27. Aspradakis MM (1997) A study to assess and improve dose computations in photon beam therapy. Med Phys, 24(8): 1334-1334. [DOI:10.1118/1.598090]

28. Sauer OA (1995) Calculation of dose distributions in the vicinity of High‐Z interfaces for photon beams. Med Phys 22(10): 1685-1690. [DOI:10.1118/1.597433] [PMID]

29. Han T, Mikell J K, Salehpour M, Mourtada F (2011) Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model‐based convolution methods in heterogeneous media. Med Phy, 38(5): 2651-2664. [DOI:10.1118/1.3582690] [PMID] []

30. Chow J C, Leung M K, Van Dyk J (2009) Variations of lung density and geometry on inhomogeneity correction algorithms: A Monte Carlo dosimetric evaluation. Med Phys, 36(8): 3619-3630. [DOI:10.1118/1.3168966] [PMID]

31. Fogliata A, Vanetti E, Albers D, et al. (2007) On the dosimetric behaviour of photon dose calculation algorithms in the presence of simple geometric heterogeneities: comparison with Monte Carlo calculations. Phys Med Biol, 52(5): 1363- 1385. [DOI:10.1088/0031-9155/52/5/011] [PMID]

32. Schneider W, Bortfeld T, Schlegel W (2000) Correlation between CT numbers and tissue parameters needed for Monte Carlo simulations of clinical dose distributions. Phys Med Biol, 45(2): 459-78. [DOI:10.1088/0031-9155/45/2/314] [PMID]

33. Vanderstraeten B, Chin PW, Fix M, et al. (2007) Conversion of CT numbers into tissue parameters for Monte Carlo dose calculations: a multi-centre study. Phys Med Biol, 52(3): 539-62. [DOI:10.1088/0031-9155/52/3/001] [PMID]

34. Kawrakow I and Walters B (2006) Efficient photon beam dose calculations using DOSXYZnrc with BEAMnrc. Med Phys, 33(8): 3046-3056. [DOI:10.1118/1.2219778] [PMID]

35. Benhalouche S, Visvikis D, Le Maitre A, et al. (2013) Evaluation of clinical IMRT treatment planning using the GATE Monte Carlo simulation platform for absolute and relative dose calculations. Med phys, 40(2): 021711. [DOI:10.1118/1.4774358] [PMID]

36. Seroul P, Sarrut D (2008) VV: a viewer for the evaluation of 4D image registration, presented at Medical Image Computing and Computer-Assisted Intervention MICCAI Workshop [DOI:10.54294/hfoogp]

37. Palmans H, Andreo P, Huq MS, et al. (2017) Dosimetry of small static fields used in external beam radiotherapy: an IAEA-AAPM international code of practice for reference and relative dose determination. Med Phys 45(11): e1123-e45. [DOI:10.1002/mp.13208]

38. Low DA, Harms WB, Mutic S, Purdy JA (1998) A technique for the quantitative evaluation of dose distributions. Med Phys, 25(5): 656-661. [DOI:10.1118/1.598248] [PMID]

39. Hussein M, Clark C, Nisbet A (2017) Challenges in calculation of the gamma index in radiotherapy-towards good practice. Phys Med, 36: 1-11. [DOI:10.1016/j.ejmp.2017.03.001] [PMID]

40. Williams T, Kelley C Gnuplot software (ver 4.4.3). Web access (preferred): https://sourceforge.net/projects/gnuplot

41. Venselaar J, Welleweerd H, Mijnheer B (2001) Tolerances for the accuracy of photon beam dose calculations of treatment planning systems. Radiother Oncol, 60(2): 191-201. [DOI:10.1016/S0167-8140(01)00377-2]

42. Mesbahi A, Reilly A J, Thwaites D I (2006) Development and commissioning of a Monte Carlo photon beam model for Varian Clinac 2100EX linear accelerator. Appl Radiat Isot, 64(6): 656-662. [DOI:10.1016/j.apradiso.2005.12.012] [PMID]

43. Gershkevitsh E, Schmidt R, Velez G, et al. (2008) Dosimetric verification of radiotherapy treatment planning systems: Results of IAEA pilot study. Radiother Oncol, 89(3): 338-346. [DOI:10.1016/j.radonc.2008.07.007] [PMID]

44. Knöös T, Wieslander E, Cozzi L, et al. (2006) Comparison of dose calculation algorithms for treatment planning in external photon beam therapy for clinical situations. Phys Med Biol, 51(22): 5785- 807. [DOI:10.1088/0031-9155/51/22/005] [PMID]

45. Tai DT, Oanh LT, Son ND, et al. (2019) Dosimetric and Monte Carlo verification of jaws-only IMRT plans calculated by the Collapsed Cone Convolution algorithm for head and neck cancers. Rep Pract Oncol, 24(1): 105-114. [DOI:10.1016/j.rpor.2018.11.004] [PMID] []

46. Chopra KL, Leo P, Kabat Ch, et al. (2018) Evaluation of dose calculation accuracy of treatment planning systems in the presence of tissue heterogeneities. Ther Radiol Oncol, 2: 28. [DOI:10.21037/tro.2018.07.01]

47. Stathakis S, Esquivel C, Vazquez Quino L, et al. (2012) Accuracy of the small field dosimetry using the Acuros XB dose calculation algorithm within and beyond heterogeneous media for 6 MV photon beams. Int J Med Phys Clin Eng Radiat Oncol, 1: 78-87. [DOI:10.4236/ijmpcero.2012.13011]