Journal of Modern Research Physics
Volume 10, Issue 1 (Spring and Summer 2025 2025)
JMRPh 2025, 10(1): 14-26 |
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Usefi M, Banaee N, HassanPpour S, Khazaee Moghadam M. Investigation and Comparison of Dose Distribution Between the Convolution Algorithm and Monte Carlo Simulation in the Gamma Knife Device for Brain Tumor Treatment. JMRPh 2025; 10 (1) :14-26
URL: http://jmrph.khu.ac.ir/article-1-259-en.html
URL: http://jmrph.khu.ac.ir/article-1-259-en.html
Department of Medical Radiation, Engineering Faculty, Central Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract: (30 Views)
Cancer remains one of humanity's most significant challenges, necessitating precise and effective therapeutic approaches. Advanced techniques such as stereotactic radiosurgery (SRS) and cutting-edge devices like Gamma Knife have been employed for the treatment of brain tumors. Convolution algorithms, recognized for their ability to detect tissue heterogeneity, and Monte Carlo simulations, known as the most accurate dose calculation method, have garnered considerable attention. In this study, the Gamma Knife system was simulated using Monte Carlo codes to calculate dose distribution on a heterogeneous phantom. Subsequently, the phantom underwent CT imaging and analysis within the Gamma Knife treatment planning system. Results indicated minimal dose distribution differences in central profiles but increased discrepancies at field margins. This research contributes to enhanced therapeutic precision and reduced side effects.
Keywords: Gamma Knife, Monte Carlo Simulation, Dose Distribution, Convolution Algorithm, Gafchromic Film
Type of Study: Research |
Subject:
Special
Received: 2025/03/15 | Accepted: 2025/09/3 | Published: 2025/09/22 | ePublished: 2025/09/22
Received: 2025/03/15 | Accepted: 2025/09/3 | Published: 2025/09/22 | ePublished: 2025/09/22
References
1. 1[ Delaidelli, A. and A. Moiraghi, Recent advances in the diagnosis and treatment of brain tumors. Brain sciences, 14(3): p. 224, 2024. [DOI:10.3390/brainsci14030224] [PMID] []
2. [2] Mellinghoff, I.K. and R.J. Gilbertson, Brain Tumors: Challenges and Opportunities to Cure. J Clin Oncol, 35(21): p. 2343-2345, 2017. [DOI:10.1200/JCO.2017.74.2965] [PMID]
3. [3] Lara-Velazquez, M., et al., Advances in brain tumor surgery for glioblastoma in adults. Brain sciences, 7(12): p. 166, 2017. [DOI:10.3390/brainsci7120166] [PMID] []
4. [4] Tsugawa, T., et al., Gamma knife stereotactic radiosurgery for intracranial hemangiopericytoma. Journal of Radiosurgery and SBRT, 3(1): p. 29, 2014.
5. [5] Anvari, A., P. Sasanpour, and M.R. Kheradmardi, Radiotherapy and immunotherapy in melanoma brain metastases. Hematology/oncology and stem cell therapy, 2021.
6. [6] Higuchi, Y., et al., Modern management for brain metastasis patients using stereotactic radiosurgery: literature review and the authors' gamma knife treatment experiences. Cancer management and research,: p. 1889-1899 , 2018. [DOI:10.2147/CMAR.S116718] [PMID] []
7. [7] Kamal, S., Gamma Knife Radiosurgery-A Revolutionary Modality in the Treatment of Brain Tumors. National Journal of Health Sciences, 7(4): p. 142-143, 2022. [DOI:10.21089/njhs.74.0142]
8. [8] Ashley Cothran, R., Hypofractionated radiation: Understanding the modality and impact on patient outcomes. Clinical Journal of Oncology Nursing, 26(1): p. 23-26, 2022.
9. [9] Zhan, D.-J., et al. Multi-group Particle Swarm Optimization with K-means Gap Filling for Finding Gamma Knife Treatment Plans. in 2023 13th International Conference on Information Science and Technology (ICIST). IEEE, 2023. [DOI:10.1109/ICIST59754.2023.10367177]
10. [10] Xing, L., et al., Overview of image-guided radiation therapy. Medical Dosimetry, 31(2): p. 91-112, 2006. [DOI:10.1016/j.meddos.2005.12.004] [PMID]
11. [11] Podgorsak, E.B., et al., Radiosurgery with high energy photon beams: a comparison among techniques. International Journal of Radiation Oncology* Biology* Physics, 16(3): p. 857-865, 1989. [DOI:10.1016/0360-3016(89)90506-3] [PMID]
12. [12] Rice, R., et al., Measurements of dose distributions in small beams of 6 MV x-rays. Physics in Medicine & Biology, 32(9): p. 1087, 1987. [DOI:10.1088/0031-9155/32/9/002] [PMID]
13. [13] Stoica, F., R. Perin, and D. Neamtu, RISK FACTORS ASSOCIATED WITH STEREOTACTIC RADIOSURGERY FOR LARGE SKULL BASE BENIGN MENINGIOMAS. Romanian Neurosurgery, 38, 2024. [DOI:10.33962/roneuro-2024-134]
14. [14] Zhu, D., et al., Study of a spherical phantom for Gamma knife dosimetry. Journal of Applied Clinical Medical Physics, 11(2): p. 222-229, 2010. [DOI:10.1120/jacmp.v11i2.3130] [PMID] []
15. [15] Nakazawa, H., et al., Effect of skull contours on dose calculations in Gamma Knife Perfexion stereotactic radiosurgery. Journal of Applied Clinical Medical Physics, 15(2): p. 28-38, 2014. [DOI:10.1120/jacmp.v15i2.4603] [PMID] []
16. [16] Khan, F.M. and J.P. Gibbons, Khan's the physics of radiation therapy. Lippincott Williams & Wilkins, 2014.
17. [17] Zhang, P., et al., Fast verification of Gamma Knife™ treatment plans. Journal of Applied Clinical Medical Physics, 1(4): p. 158-164, 2000. [DOI:10.1120/jacmp.v1i4.2638] [PMID] []
18. [18] Xu, A., et al., Dose differences between the three dose calculation algorithms in Leksell GammaPlan. Journal of Applied Clinical Medical Physics, 15(5): p. 89-99, 2014. [DOI:10.1120/jacmp.v15i5.4844] [PMID] []
19. [19] Zhang, A., et al., Comprehensive evaluation and clinical implementation of commercially available Monte Carlo dose calculation algorithm. Journal of Applied Clinical Medical Physics, 14(2): p. 127-145, 2013. [DOI:10.1120/jacmp.v14i2.4062] [PMID] []
20. [20] Chaikh, A., J.-Y. Giraud, and J. Balosso, A method to quantify and assess the dosimetric and clinical impact resulting from the heterogeneity correction in radiotherapy for lung cancer. International Journal of Cancer Therapy and Oncology, 2(1), 2014. [DOI:10.14319/ijcto.0201.10]
21. [21] Fultz, S., et al., Photoneutron cross sections for V 51 and Co 59. Physical Review, 128(5): p. 2345, 1962. [DOI:10.1103/PhysRev.128.2345]
22. [22] Sloboda, R.S., et al., A brief look at model-based dose calculation principles, practicalities, and promise. Journal of contemporary brachytherapy, 9(1): p. 79-88, 2017. [DOI:10.5114/jcb.2017.65849] [PMID] []
23. [23] Schreuder, A.N., et al., Validation of the RayStation Monte Carlo dose calculation algorithm using realistic animal tissue phantoms. Journal of Applied Clinical Medical Physics, 20(10): p. 160-171, 2019. [DOI:10.1002/acm2.12733] [PMID] []
24. [24] Ahnesjö, A., M. Saxner, and A. Trepp, A pencil beam model for photon dose calculation. Medical physics, 19(2): p. 263-273, 1992. [DOI:10.1118/1.596856] [PMID]
25. [25] Ahnesjö, A. and M.M. Aspradakis, Dose calculations for external photon beams in radiotherapy. Physics in Medicine & Biology, 44(11): p. R99, 1999. [DOI:10.1088/0031-9155/44/11/201] [PMID]
26. [26] Lu, W., et al., Accurate convolution/superposition for multi-resolution dose calculation using cumulative tabulated kernels. Physics in Medicine & Biology, 50(4): p. 655, 2005. [DOI:10.1088/0031-9155/50/4/007] [PMID]
27. [27] Elmtalab, S., et al., Determination of the neutron contamination during brain radiotherapy using a moderated-boron trifluoride detector and the Mcnp Monte Carlo code. Radiation protection dosimetry, 198(3): p. 129-138, 2022. [DOI:10.1093/rpd/ncac001] [PMID]
28. [28] Aziz, M.A., et al., -Beam Neutron Optimization for Boron Neutron Capture Therapy (BNCT) facility. Arab Journal of Nuclear Sciences and Applications, 57(4): p. 17-26, 2024. [DOI:10.21608/ajnsa.2024.304087.1830]
29. [29] Shende, R., S. Dhoble, and G. Gupta, Dosimetric Evaluation of Radiation Treatment Planning for Simultaneous Integrated Boost Technique Using Monte Carlo Simulation. Journal of Medical Physics, 48(3): p. 298-306, 2023. [DOI:10.4103/jmp.jmp_4_23] [PMID] []
30. [30] Raghavi, S., et al., Evaluation of Dose Calculation Algorithms Accuracy for ISOgray Treatment Planning System in Motorized Wedged Treatment Fields. Journal of Medical Signals & Sensors, 14(10): p. 31, 2024. [DOI:10.4103/jmss.jmss_28_24] [PMID] []
31. [31] Chetty, I.J., et al., Report of the AAPM Task Group No. 105: Issues associated with clinical implementation of Monte Carlo‐based photon and electron external beam treatment planning. Medical physics, 34(12): p. 4818-4853, 2007. [DOI:10.1118/1.2795842] [PMID]
32. [32] Jia, X., et al., GPU-based fast Monte Carlo simulation for radiotherapy dose calculation. Physics in Medicine & Biology, 56(22): p. 7017, 2011. [DOI:10.1088/0031-9155/56/22/002] [PMID]
33. [33] Han, T., et al., Dosimetric comparison of Acuros XB deterministic radiation transport method with Monte Carlo and model‐based convolution methods in heterogeneous media. Medical Physics, 38(5): p. 2651-2664, 2011. [DOI:10.1118/1.3582690] [PMID] []
34. [34] Junios, K.D., Treatment planning system pada kanker prostat dengan teknik brachyterapy. Jurnal Ipteks Terapan, 10(3): p. 155-160, 2016. [DOI:10.22216/jit.2016.v10i3.587]
35. [35] Trnka, J., J. Novotny Jr, and J. Kluson, MCNP‐based computational model for the Leksell Gamma Knife. Medical physics, 34(1): p. 63-75, 2007. [DOI:10.1118/1.2401054] [PMID]
36. [36] Al-Dweri, F.M., A.M. Lallena, and M. Vilches, A simplified model of the source channel of the Leksell GammaKnife® tested with PENELOPE. Physics in Medicine & Biology, 49(12): p. 2687, 2004. [DOI:10.1088/0031-9155/49/12/015] [PMID]
37. [37] Xiong, W., et al. Implementation of Monte Carlo simulations for the Gamma Knife system. in Journal of Physics: Conference Series. IOP Publishing, 2007. [DOI:10.1088/1742-6596/74/1/021023]
38. [38] Reinhardt, S., et al., Comparison of Gafchromic EBT2 and EBT3 films for clinical photon and proton beams. Medical physics, 39(8): p. 5257-5262, 2012. [DOI:10.1118/1.4737890] [PMID]
39. [39] Costa, F., S. Sarmento, and O. Sousa, Assessment of clinically relevant dose distributions in pelvic IOERT using Gafchromic EBT3 films. Physica Medica, 31(7): p. 692-701, 2015. [DOI:10.1016/j.ejmp.2015.05.013] [PMID]
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