A tool for precise calculation of organ doses in voxelised geometries using GAMOS/Geant4 with a graphical user interface

• Autorzy: Dubois Pedro Arce , Thao Nguyen Thi Phuong , Trung Nguyen Thien , Azcona Juan Diego , Aguilar-Redondo Pedro-Borja

Identyfikatory

DOI

10.2478/pjmpe-2021-0005

• Języki publikacji: EN

Abstrakty

EN

Introduction: The limit of the method of calculating organ doses using voxelised phantoms with a Monte Carlo simulation code is that dose calculation errors in the boundaries of the organs are especially relevant for thin, small or complex geometries. In this report, we describe a tool that helps overcome this problem, accurately calculating organ doses by applying the “parallel geometry” utility feature of Geant4 through the GAMOS framework. Methods and methods: We have tried to simplify the use of this tool by automatically processing the different DICOM image modalities (CT, PT, ST, NM), and by including the automatic conversion of the structures found in a DICOM RTSTRUCT file into Geant4 volumes that build the parallel geometry. For Nuclear Medicine applications, the DICOM PT, ST or NM images are converted into probabilities of generation of primary particles in each voxel, and the DICOM CT images into materials and material densities. For radiotherapy treatments, the DICOM RTPlan or RTIonPlan may also be used, hence the user only needs to describe the accelerator geometry. We also provide a Graphical User Interface for ease of use by for inexperienced users in Monte Carlo. Results: We have tested the functionality of the tool with an I-131 thyroid cancer treatment, and obtained the expected energy deposition and dose differences, given that the particle source, geometry and structures are defined. Conclusions: In summary, we provide an easy-to-use tool to calculate, with high accuracy, organ doses, taking into account their exact geometry as painted by the medical personnel on a voxelised phantom.

Słowa kluczowe

EN

organ dose; voxel phantoms; Geant4; GAMOS; parallel geometry

• Wydawca: Polskie Towarzystwo Fizyki Medycznej ; De Gruyter
• Czasopismo: Polish Journal of Medical Physics and Engineering
• Rocznik: 2021
• Tom: Vol. 27, Iss. 1
• Strony: 31--40
• Opis fizyczny: Bibliogr. 18 poz., rys.

Twórcy

autor

Dubois Pedro Arce

• Technology Department, Scientific Instrumentation Division, Medical Applications Unit, Centro de Investigaciones Energéticas, MedioAmbientales y Tecnológicas (CIEMAT). Av. Complutense, 40, 28040 Madrid, Spain

autor

Thao Nguyen Thi Phuong

• VINATOM, 59 Ly Thuong Kiet st., Hoan Kiem district., Ha Noi, VietNam
• Nguyen Huu Huan high school, 1 Doan Ket, Thu Duc, Ho Chi Minh city, VietNam

autor

Trung Nguyen Thien

• Techbase Yahoo. 10th level Saigon Centre Tower 2, 67 Le Loi st., district 1, Ho Chi Minh City, VietNam

autor

Azcona Juan Diego

• Servicio de Radiofísica y Protección Radiológica de la Clínica Universidad de Navarra. Av. De Pío XII, 36, 31008 Pamplona, Spain

autor

Aguilar-Redondo Pedro-Borja

• Servicio de Radiofísica y Protección Radiológica de la Clínica Universidad de Navarra. Av. De Pío XII, 36, 31008 Pamplona, Spain

Bibliografia

• 1. Bolch WE, Bouchet LG, Robertson JS, et al. The dosimetry of nonuniform activity distributions-radionuclide S values at the voxel level, MIRD pamphlet No. 17. J Nucl Med. 1999;40:11-36.
• 2. Mehdi M, Shahrokh N, Seyed RZ, Ali AP, Mahdi G, Ruhollah GA. A 3D Monte Carlo method for estimation of patient-specific internal organs absorbed dose for 99mTc-hynic-Tyr3-octreotide imaging. World J Nucl Med. 2016;15(2):114-123. https://doi.org/10.1007/s00411-003-0221-8
• 3. Martin C. Voxel-based computational models of real human anatomy: A review. Radiat Environ Biophys. 2004;42:229-235. https://doi.org/10.1007/s00411-003-0221-8
• 4. Yuan J, Chen Q, Brindle J et al. Investigation of nonuniform dose voxel geometry in Monte Carlo calculations. Technol Cancer Res Treat .2015;14(4):419-27. https://doi.org/10.1177/1533034614547459
• 5. Sharma N, Aggarwal LM. Automated medical image segmentation techniques. J Med Phys. 2010;35(1):3-14. https://doi.org/10.4103/0971-6203.58777
• 6. Awais M, Ulas B, Brent F, et al. Segmentation and image analysis of abnormal lungs at CT: current approaches, challenges, and future trends. RadioGraphics. 2015;35:1056-1076. https://doi.org/10.1148/rg.2015140232
• 7. Brent F, Ulas B, Awais M, Ziyue X, Daniel JM. A Review on segmentation of Positron Emission Tomography images. Comput Biol Med. 2014;50:76-96. https://doi.org/10.1016/j.compbiomed.2014.04.014
• 8. Paula CG, Paulo TDS, Hélio Y, Gabriel P F GR, Laura F. Reconstruction of segmented human voxel phantoms for skin dosimetry. in International Nuclear Atlantic Conference - INAC (Rio de Janeiro, Brazil) 2009. ISBN: 978-85-99141-03-8
• 9. Kramer R,Vieira JW, Khoury HJ, Lima FRA, Fuelle D. All about MAX: a male adult voxel phantom for Monte Carlo calculations in radiation protection dosimetry. Phys Med Biol. 2003;48:1239-1262. https://doi.org/10.1088/0031-9155/48/10/301
• 10. Chung-Yi H, Lai-Jun L, Pei-Yuan L, Jiing-Yih Li, Wen-Teng Wg, Shang-Chih L. Efficient segmentation algorithm for 3D bone models construction on medical images. Journal of Medical and Biological Engineering. 2010;31(6):375-386.
• 11. Xu XG. An exponential growth of computational phantom research in radiation protection, imaging, and radiotherapy: A review of the fifty-year history. Phys Med Biol. 2014;59(18):233-302. https://doi.org/10.1088/0031-9155/59/18/R233
• 12. Yeon SY, Min CH, Chan HK, Jong HJ. Conversion of ICRP male reference phantom to polygon-surface phantom. Phys. Med. Biol. 2013; 58(19): 6985-7007. https://doi.org/10.1088/0031-9155/58/19/6985
• 13.Yeon SY, Min CH, Chan HK, Jong HJ. Dose coefficients of mesh-type ICRP reference computational phantoms for idealized external exposures of photons and electrons. Nuclear Engineering and Technology. 2019;51(3):843-552. https://doi.org/10.1016/j.net.2018.12.006
• 14. Apostolakis J, Asai M, Cosmo G, Howard V, Ivanchenko V, Verderi M. Parallel geometries in Geant4: Foundation and recent enhancements. in 2008 IEEE Nuclear Science Symposium Conference Record (Dresden, Germany). 2008;883-886. https://doi.org/10.1109/NSSMIC.2008.4774535
• 15. Arce P, Rato Mendes P, Lagares JI. GAMOS: a GEANT4-based easy and flexible framework for nuclear medicine applications. in IEEE Proc. Nuc. Sci. Symp. Conf. Rec. 2008; 3162-3168. https://doi.org/10.1109/NSSMIC.2008.4775023
• 16. Arce P, Lagares JI, Harkness L, et al. Gamos: A framework to do Geant4 simulations in different physics fields with a user-friendly interface. Nuc Instr Meth Section A. 2014;735:304. https://doi.org/10.1016/j.nima.2013.09.036
• 17. Schneider U, Pedroni E, Lomax A. The calibration of CT Hounsfield units for radiotherapy treatment planning. Phys Med Biol. 1996;41(1):111-124. https://doi.org/10.1088/0031-9155/41/1/009
• 18. Geant4 Collaboration. Geant4 Book For Application Developer," Available at: http://geant4-userdoc.web.cern.ch/geant4-userdoc/UsersGuides/ForApplicationDeveloper/html/index.html (Accessed: 1 January, 2020).

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).