Research article Special Issues

High-resolution phantom of a nephron for radiation nephrotoxicity evaluation in biophysical simulations

  • Received: 10 December 2021 Revised: 11 May 2022 Accepted: 26 May 2022 Published: 17 June 2022
  • Computer simulation plays an important role in medical physics. The aim of this study was to generate an accurate model to calculate the absorbed dose at the cell level in a voxelized phantom of nephrons. In order to implement a model of kidney microdosimetry, a 3D mesh phantom of a human kidney nephron, representing a cortical nephron, was digitized to create a 3D voxelized phantom of a nephron for use in Monte Carlo simulations. The phantom was fed to GATE Monte Carlo toolkits, and simulations were performed to calculate the absorbed dose/energy from alpha and electron sources over a range of energy levels. The results were compared to the results published in literature that were derived by using a stylized phantom. The dose estimated in subunits of the voxelized and stylized phantoms showed a considerable bias (average of relative differences). The maximum difference for self-absorption was 12.5%, and up to 20% for cross-absorption. The digital phantom showed very significant differences in dose distribution among the cells in different subunits of the nephron. The results demonstrated that a small dissimilarity in the size and shape of subunits can lead to a considerable difference in the microdosimetry results. The model presented in this study offers a phantom that not only presents the realistic geometry of a nephron, which has been neglected in previous stylized models, but also one that has the capability of plotting the spatial distribution of the absorbed dose for any distribution of radiopharmaceuticals in nephron cells.

    Citation: Masoud Jabbary, Hossein Rajabi. High-resolution phantom of a nephron for radiation nephrotoxicity evaluation in biophysical simulations[J]. AIMS Biophysics, 2022, 9(2): 147-160. doi: 10.3934/biophy.2022013

    Related Papers:

  • Computer simulation plays an important role in medical physics. The aim of this study was to generate an accurate model to calculate the absorbed dose at the cell level in a voxelized phantom of nephrons. In order to implement a model of kidney microdosimetry, a 3D mesh phantom of a human kidney nephron, representing a cortical nephron, was digitized to create a 3D voxelized phantom of a nephron for use in Monte Carlo simulations. The phantom was fed to GATE Monte Carlo toolkits, and simulations were performed to calculate the absorbed dose/energy from alpha and electron sources over a range of energy levels. The results were compared to the results published in literature that were derived by using a stylized phantom. The dose estimated in subunits of the voxelized and stylized phantoms showed a considerable bias (average of relative differences). The maximum difference for self-absorption was 12.5%, and up to 20% for cross-absorption. The digital phantom showed very significant differences in dose distribution among the cells in different subunits of the nephron. The results demonstrated that a small dissimilarity in the size and shape of subunits can lead to a considerable difference in the microdosimetry results. The model presented in this study offers a phantom that not only presents the realistic geometry of a nephron, which has been neglected in previous stylized models, but also one that has the capability of plotting the spatial distribution of the absorbed dose for any distribution of radiopharmaceuticals in nephron cells.



    加载中

    Acknowledgments



    The authors received no financial support for the research and/or authorship of this article.

    Conflicts of interest



    The authors declare that they have no conflict of interest affecting the publication of this article. The approval of the local ethics committee was obtained.

    [1] Bolch W, Lee C, Wayson M, et al. (2010) Hybrid computational phantoms for medical dose reconstruction. Radiat Environ Biophy 49: 155-168. https://doi.org/10.1007/s00411-009-0260-x
    [2] Lee C, Lodwick D, Williams J L, et al. (2008) Hybrid computational phantoms of the 15-year male and female adolescent: applications to CT organ dosimetry for patients of variable morphometry. Med Phys 35: 2366-2382. https://doi.org/10.1118/1.2912178
    [3] Zaidi H, Tsui BMW (2009) Review of computational anthropomorphic anatomical and physiological models. P IEEE 97: 1938-1953. https://doi.org/10.1109/JPROC.2009.2032852
    [4] Hurtado JL, Lee C, Lodwick D, et al. (2012) Hybrid computational phantoms representing the reference adult male and adult female: construction and applications for retrospective dosimetry. Health Phys 102. https://doi.org/10.1097/HP.0b013e318235163f
    [5] Caon M (2004) Voxel-based computational models of real human anatomy: a review. Radiat Environ Bioph 42: 229-235. https://doi.org/10.1007/s00411-003-0221-8
    [6] Zaidi H, Xu XG (2007) Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences. Annu Rev Biomed Eng 9: 471-500. https://doi.org/10.1146/annurev.bioeng.9.060906.151934
    [7] Segars WP, Lalush DS, Tsui BMW (2000) Development of an interactive software application to model patient populations in the 4D NURBS-based cardiac torso phantom, 2000 IEEE Nuclear Science Symposium. IEEE : 7081760. https://doi.org/10.1109/NSSMIC.2000.949317
    [8] Lee C, Lodwick D, Hasenauer D, et al. (2007) Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models. Phys Med Biol 52: 3309. https://doi.org/10.1088/0031-9155/52/12/001
    [9] Jabari M, Rajabi H, Dadashzadeh S (2020) A microdosimetry model of kidney by GATE Monte Carlo simulation using a nonuniform activity distribution in digital phantom of nephron. Nucl Med Commun 41: 110-119. https://doi.org/10.1097/MNM.0000000000001112
    [10] Kim CH, Jeong JH, Bolch WE, et al. (2011) A polygon-surface reference Korean male phantom (PSRK-Man) and its direct implementation in Geant4 Monte Carlo simulation. Phys Med Biol 56: 3137. https://doi.org/10.1088/0031-9155/56/10/016
    [11] Bolch WE, Bouchet LG, Robertson JS, et al. (1999) MIRD pamphlet no. 17: the dosimetry of nonuniform activity distributions—radionuclide S values at the voxel level. J Nucl Med 40: 11S-36S.
    [12] Behr T M, Sharkey R M, Sgouros G, et al. (1997) Overcoming the nephrotoxicity of radiometal-labeled immunoconjugates: improved cancer therapy administered to a nude mouse model in relation to the internal radiation dosimetry. Cancer: Interdiscip Int J Am Cancer Soc 80: 2591-2610. https://doi.org/10.1002/(SICI)1097-0142(19971215)80:12+<2591::AID-CNCR35>3.0.CO;2-5
    [13] Cassady JR (1995) Clinical radiation nephropathy. Int J Radiat Oncol Biol Phys 31: 1249-1256. https://doi.org/10.1016/0360-3016(94)00428-N
    [14] Robbins MEC, Bonsib SM (1995) Radiation nephropathy: a review. Scanning Microsc 9: 22. https://digitalcommons.usu.edu/microscopy/vol9/iss2/22
    [15] Bodei L, Cremonesi M, Ferrari M, et al. (2008) Long-term evaluation of renal toxicity after peptide receptor radionuclide therapy with 90Y-DOTATOC and 177Lu-DOTATATE: the role of associated risk factors. Eur J Nucl Med Mol I 35: 1847-1856. https://doi.org/10.1007/s00259-008-0778-1
    [16] Valkema R, Pauwels SA, Kvols LK, et al. (2005) Long-term follow-up of renal function after peptide receptor radiation therapy with 90Y-DOTA0, Tyr3-octreotide and 177Lu-DOTA0, Tyr3-octreotate. J Nucl Med 46: 83S-91S.
    [17] Hobbs RF, Song H, Huso DL, et al. (2012) A nephron-based model of the kidneys for macro-to-micro α-particle dosimetry. Phys Med Biol 57: 4403. https://doi.org/10.1088/0031-9155/57/13/4403
    [18] Blender Project, 2007. Available from: www.blender.org
    [19] Larobina M, Murino L (2014) Medical image file formats. J Digit Imaging 27: 200-206. https://doi.org/10.1007/s10278-013-9657-9
    [20] Kaddouch S, El Khayati N (2020) Geant4/GATE comparison of geometry optimization algorithms for internal dosimetry using voxelized phantoms. Phys Part Nuclei Lett 17: 97-107. https://doi.org/10.1134/S1547477120010094
    [21] Sarrut D, Bardiès M, Boussion N, et al. (2004) A review of the use and potential of the GATE Monte Carlo simulation code for radiation therapy and dosimetry applications. Med Phys 41: 064301. https://doi.org/10.1118/1.4871617
    [22] Visvikis D, Bardies M, Chiavassa S, et al. (2006) Use of the GATE Monte Carlo package for dosimetry applications. Nucl Instrum Meth A 569: 335-340. https://doi.org/10.1016/j.nima.2006.08.049
    [23] Dalir MP, Hedayati E, Hedayati A (2021) Detection and identification of subcutaneous defects using ultrasonic waves in reflective test. J Mech Eng Sci 15: 8003-8015. https://doi.org/10.15282/jmes.15.2.2021.06.0631
    [24] Lin H, Jing J, Xu Y (2011) Effect of different cell cluster models on the radiobiological output for 211At-adioimmunotherapy. Cancer Biother Radio 26: 85-95. https://doi.org/10.1089/cbr.2010.0843
    [25] Jamison RL, Buerkert J, Lacy F (1973) A micropuncture study of Henle's thin loop in Brattleboro rats. Am J Physiol-Legacy Content 224: 180-185.
    [26] Goddu SM (1997) MIRD cellular S values: Self-absorbed dose per unit cumulated activity for selected radionuclides and monoenergetic electron and alpha particle emitters incorporated into different cell compartments, Society of Nuclear Medicine.
    [27] Firestone RB, Ekstrom LP, Chu SYF (1999) WWW Table of radioactive isotopes, APS Division of Nuclear Physics Meeting Abstracts.
  • Reader Comments
  • © 2022 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(1033) PDF downloads(65) Cited by(0)

Article outline

Figures and Tables

Figures(5)  /  Tables(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog