Moh. Miftakhul Dwi Fianto, Yohannes Sardjono, Andang Widi Harto, Isman Mulyadi Triatmoko, Gede Sutresna Wijaya, Yaser Kasesaz



One of the developments in particle therapy is proton radiation therapy. Meanwhile, a limited number of available proton therapy facilities makes research related to proton therapy difficult. Therefore, there is a need for alternative proton therapy simulations using programs other than those in proton therapy facilities. This research was aimed to simulate medulloblastoma brain cancer which children often experience.The program used in this research was PHITS version 3.24. The human body was modeled with the revised ORNL-MIRD phantom for a 10-year-old child. The therapy scheme was a whole posterior fossa boost of 19.8 Gy. The proton passive scattering was simulated by passing a uniform proton beam through the aperture and compensator with energy variations. The proton pencil beam scanning was simulated with small cylindrical beams with a radius of 0.5 cm, which were adjusted to the planning target volume with layers variations.The total duration to give the prescription dose was 550 seconds with passive scattering and 605 seconds with pencil beam scanning. In passive scattering, the OAR(s) with the most significant percentage of absorbed dose were the skin, cranium, and muscle, i.e., 8.22 ± 0.15 %, 5.51 ± 0.05 % and 1.39 ± 0,04 % respectively to their maximum tolerated dose, while in the pencil beam scanning, the OAR(s) with the most significant percentage of absorbed dose were the skin, cranium, and muscle, i.e., 5.42 ± 0.08 %, 4.43 ± 0.05 % and 0.51 ± 0.05 % respectively to their maximum tolerated dose. Dose distribution in passive scattering was relatively better than in pencil beam scanning in terms of dose homogeneity using dose sampling analysis at some points within the planning target volume.

Full Text:



  1. Paganetti H., Proton Therapy Physics(Series in Medical Physics and Biomedical Engineering). 2012. [Online]. Available:
  2. Yeon Soo Yeom et al., Computation Speeds and Memory Requirements of Mesh-Type ICRP Reference Computational Phantoms in Geant4, MCNP6, and PHITS., Health Phys. 2019. 116(5):664-676.
  3. Aksungur B., “Medulloblastoma : Diagnosis , Treatment And Prognosis,” Master's Thesis. 2016.
  4. Aman R. A., et al., “Panduan Penatalaksanaan Tumor Otak,” 2016. Available:
  5. BPJS Kesehatan, “Laporan Pengelolaan Program Tahun 2019 & Laporan Keuangan Tahun 2019 (Auditan).” Badan Penyelenggara Jaminan Sosial Kesehatan, Jakarta Pusat.
  6. Yeom Y. S., Han M. C., Kim C. H., Jeong J. H., Conversion of ICRP Male Reference Phantom to Polygon-surface Phantom. Phys Med Biol. 2013. 58(19):6985-7007.
  7. Sanchez-Parcerisa D., and Udías J., “Teaching Treatment Planning for Protons with Educational Open-source Software: Experience with FoCa and MatRad,” J. Appl. Clin. Med. Phys. 2018. 19 (4): 302–306.
  8. Sato T. et al., “Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02,” J. Nucl. Sci. Technol. 2018. 55 (6):684–690.
  9. Carter L. M., Ocampo Ramos J. C., Kesner A. L., Personalized Dosimetry of 177 Lu-DOTATATE: a Comparison of Organ- and Voxel-level Approaches using Open-access ImagesBiomed Phys Eng Express. 2021. 7(5): 34271565.
  10. Ute Linz and Jose Alonso., Laser-driven Ion Accelerators for Tumor Therapy Revisited Phys. Rev. Accel. Beams., 2016. 19: 124802.
  11. Yong Ho Chin, Alexander Wu Chao, and Michael M. Blaskiewicz, Two Particle Model for Studying the Effects of Space-Charge Force on Strong Head-tail Instabilities., Phys. Rev. Accel. Beams. 2016. 19: 014201.
  12. Ostrom Q., T., et al., “CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2007-2011,” Neuro. Oncol., 2014. 16(4): iv1–iv63.
  13. Ramaswamy V., et al., Medulloblastoma Subgroup-specific Outcomes in Irradiated Children: Who are the True High-risk Patients?,” Neuro. Oncol., 2016. 18(2) 291–297.
  14. Lukas M. C., et al., PARaDIM: A PHITS-Based Monte Carlo Tool for Internal Dosimetry with Tetrahedral Mesh Computational Phantoms., J Nucl Med. 2019. 60(12): 1802–1811.
  15. Cubillos-Mesías M., et al., “Impact of Robust Treatment Planning on Single- and Multi-Field Optimized Plans for Proton Beam Therapy of UnilateralHhead and Neck Target Volumes,” Radiat. Oncol. 2017. 12(1)190-199.
  16. Dörr W., Herrmann T., and Trott K., Normal Tissue Tolerance. 2017. 6 (5) 840–851.
  17. Dionisi F., et al., “Organs at Risk’s Tolerance and Dose Limits for Head and Neck Cancer Re-irradiation: A literature Review,” Oral Oncol. 2019. 98 (4)35–47.
  18. Brodin P., and Wolfgang T. A., “Revisiting the Dose Constraints for Head and Neck OARs in the Current Era of IMRT,” Oral Oncol. 2018. 18:8–18.
  19. Tatsuhiko Sato et al.,Features of Particle and Heavy Ion Transport code System (PHITS) version 3.02, Journal of Nuclear Science and Technology. 2018. 55(6): 684-690.
  20. Yock T. I., et al., “Long-term Toxic Effects of Proton Radiotherapy for Paediatric Medulloblastoma: A phase 2 Single-arm Study,” Lancet Oncol. 2016. 17 (3):287–298.


  • There are currently no refbacks.

PTKRN Digital Library Mendeley