Volume 3, Issue 2

Original research papers



E.A. Shishkina, V.I. Zalyapin, Yu.S. Timofeev, M.O. Degteva, M. Smith, B. Napier

Pages: 133-137

DOI: 10.21175/RadJ.2018.02.022

Received: 2 JUL 2018, Received revised: 12 NOV 2018, Accepted: 20 NOV 2018, Published online: 27 DEC 2018

The estimation of dose factors for active marrow exposed to bone-seeking beta-emitters, such as 89Sr and 90Sr/90Y (0 – 1.5 MeV and 0 – 2.4 MeV, respectively), is an important task of bone dosimetry. Monte Carlo simulations of electron – photon transport to calculate the active marrow doses are based on the geometrical modeling of bone structures. The model geometry should consist of accurate descriptions of spongiosa fine structure and cortical bone thickness (because of the high probability of low energy electron emission) as well as descriptions of bone macro-dimensions (because the maximum electron path length in spongiosa is about 5-9 mm). New computer tomography (CT) -based methods are widely applied to develop computational dosimetric phantoms. The advantage of the CT-based method is in high realism of the description of complex bone shape as well as in the possibility of an adequate description of bone microstructure with µCT. However, the method has a number of disadvantages, viz.: (1) the method is laborious and expensive; (2) the use of cadavers is associated with organizational difficulties; (3) one cadaver –based model can be non-representative and does not allow estimation of the uncertainties associated with individual variability of human anatomy; (4) cortical bone thickness is fixed based on the CT, for which resolution is worse than the measurand; (5) in practice, the limitation in voxel resolution of the computational phantom often results in narrowing down the strong points given by µCT because of an inadequate representation of the microstructure. Moreover, high individual variability of bone shapes and macro-dimensions negates the advantages of the above-mentioned high realism. The aim of the presented study is to elaborate the algorithm of parametric bone modeling, which allows for the generation of phantoms of hematopoietic bone segments based on known micro- and macro dimensions. We propose an approach that permits easy subdivision of bones into small segments, which may be described by simple-shape geometric figures with appropriate voxel resolution. Spongiosa structure (presented by a stochastic rod-like model and calibrated by literature-derived bone volume-to-total volume ratio) is covered by a homogenous cortical layer. All parameters of the proposed cadaver-free model can be obtained from the literature on morphometry and hystomorphometry. Moreover, the parametric modeling allows the simulation of individual variability of bone-specific dimensions.

  1. L. Yu. Krestinina et al., “Leukaemia incidence in the Techa River Cohort: 1953-2007,” Brit. J. Cancer, vol. 109, no. 11, pp. 2886 – 2893, Nov. 2013.
    DOI: 10.1038/bjc.2013.614
    PMid: 24129230
    PMCid: PMC3844904
  2. M. O. Дегтева и др, “Современное представление о радиоактивном загрязнении реки Теча в 1949–1956 гг.,” Радиационная биология. Радиоэкология, т. 85, no. 5, стр. 532-534, 2016 (M. O. Degteva et al., “Contemporary understanding of radioactive contamination of the Techa River in 1949–1956,” Radiat. Biol. Radioecol., vol. 85, no. 5, pp. 532 – 534, 2016.)
    DOI: 10.7868/S0869803116050039
  3. A. V. Akleev et al., “Consequences of the radiation accident at the Mayak production association in 1957 (the `Kyshtym Accident`),” J. Radiol. Prot., vol. 37, no. 3, pp. R19 - R42, Aug. 2017.
    DOI: 10.1088/1361-6498/aa7f8d
    PMid: 28703713
  4. A. Aarkrog et al., “Radioactive inventories from the Kyshtym and Karachay accidents: estimates based on soil samples collected in the South Urals (1990-1995),” Sci. Total Environ., vol. 201, no. 2, pp. 137 – 154, Aug 1997.
    DOI: 10.1016/S0048-9697(97)00098-3
  5. M. O. Degteva et al., “Development of an improved dose reconstruction system for the Techa River population affected by the operation of the Mayak Production Association,” Radiat. Res., vol. 166, no. 1, e0174641, Aug. 2006.
    DOI: 10.1667/RR3438.1
    PMid: 16808612
  6. Z. Zhang et al., “Correction of confidence intervals in excess relative risk models using Monte Carlo dosimetry systems with shared errors,” PLOS ONE, vol. 12, no. 4, pp. 255 – 270, Apr. 2017.
    DOI: 10.1371/journal.pone.0174641
    PMid: 28369141
    PMCid: PMC5378348
  7. J. R. Whitwell, F. W. Spiers, “Calculated beta ray dos factors for trabecular bone,” Phys. Med. Biol., vol. 21, no. 1, pp. 16 – 38, Nov. 1976.
    DOI: 10.1088/0031-9155/21/1/002
    PMid: 1257296
  8. A. Shah et al., “A paired-image radiation transport model for skeletal dosimetry,” J. Nucl. Med., vol. 46, no. 2, pp. 344 – 353, Feb. 2005.
    Retrieved from: http://jnm.snmjournals.org/content/46/2/344.full.pdf+html;
    Retrieved on: May 20, 2018
  9. D. W Dempster et al., “Standardized nomenclature, symbols, and units for bone histomorphometry: a 2012 update of the report of the ASBMR Histomorphometry Nomenclature Committee,” J. Bone Miner. Res., vol. 28, no. 1, pp. 2 – 17, Jan. 2013.
    DOI: 10.1002/jbmr.1805
    PMid: 23197339
    PMCid: PMC3672237
  10. D. M. Connor et al., “Comparison of diffraction-enhanced computed tomography and monochromatic synchrotron radiation computed tomography of human trabecular bone,” Phys. Med. Biol., vol. 54, no. 20, pp. 6123 – 6133, Oct. 2009.
    DOI: 10.1088/0031-9155/54/20/006
    PMid: 19779219
  11. A. M. H. Da Silva et al., “Two and three-dimensional morphometric analysis of trabecular bone using X-ray microtomography (µCT),” Rev. Bras. Eng. Biomed., vol. 30, no. 2, pp. 93 – 101, Jun. 2014.
    DOI: 10.1590/rbeb.2014.011
  12. V. I. Zalyapin et al., “A parametric stochastic model of bone geometry,” Bulletin SUSU MMCS, vol. 11, no. 2, pp. 44 – 57, Jun. 2018.
    DOI: 10.14529/mmp180204
  13. B. A. Campbell et al., “Distribution Atlas of Proliferating Bone Marrow in Non-Small Cell Lung Cancer Patients Measured by FLT-PET/CT Imaging. With Potential Applicability in Radiation Therapy Planning,” Int. J. Radiat. Oncol. Biol. Phys., vol. 92, no. 5, pp. 1035 – 1043, Aug. 2015.
    DOI: 10.1016/j.ijrobp.2015.04.027
    PMid: 26194679
  14. F. W. Spiers et al., “Mean skeletal dose factors for beta-particle emitters in human bone: Part I: Volume-seeking radionuclides,” Brit. J. Radiol., vol. 51, no. 608, pp. 622 – 627, Aug. 1978.
    DOI: 10.1259/0007-1285-51-608-622
    PMid: 678757
  15. J. Le Grand et al., “Calculated dose factors for the radiosensitive tissues in bone,” in Proc. Second Int. Conf. on Strontium Metabolism National Technical Information Service, Washington, USA, 1972, p. 49.
  16. W. Hough et al., “An image-based skeletal dosimetry model for the ICRP reference adult male – internal electron source”, Phys. Med. Biol., vol. 56, no. 8, pp. 2309 – 2346, Apr. 2013.
    DOI: 10.1088/0031-9155/56/8/001
    PMid: 21427487
    PMCid: PMC3942888