Making a novel method to obtain the required irradiation time in fast neutron radiation therapy of liver tissue

Author

Abstract

During radiotherapy by any radiation, it is always essential to stop absorbing the excess dose by a tissue. To better treat cancerous tissues and to make more precise irradiation for a cancerous tumor, there needs the accurate irradiation time to be estimated. First, the constituent materials of any of the existing organs in abdominal tissue are extracted and defined in the MCNPX code. Then, every organ in the abdominal tissue is voxelized by MATLAB software. Each of the voxels is defined based on Hounsfield unit of pixels in DICOM images. Then, the voxels are assigned to the related tissue which is comprised of its constituent materials, and they are filled up with them. Then, the liver tissue is segmented among the abdomen region from other tissues. Then, the geometry of the segmented liver tissue is generated as input data for MCNPX code, and the absorbed dose is computed. After obtaining the values of absorbed doses in liver tissue per each of incident fast neutron energies, the required irradiation time is obtained in second by making an appropriate proportion of absorbed dose and activity. This precise required irradiation time is obtained by an advanced software application (designed in this research using Delphi 7 programming language) through establishing a relationship between the absorbed dose and activity based upon the energy of clinical fast neutron source. The required irradiation time is calculated to reach the desired dose for each patient during fast neutron radiation therapy for similar liver tissues accordingly.

Keywords

References

[1] S.A. Mousavi Shirazi, D. Sardari. Design and simulation of a new model for treatment by NCT. Sci. Technol. Nucl. Ins. 2012 (2012) 1-7. [2] A. Stenvall, E. Larsson, S.E. Strand, B.A. Jönsson. A small-scale anatomical dosimetry model of the liver. Phys. Med. Biol. 59 (2014) 3353-3371. [3] I. Postuma, S. Bortolussi, N. Protti, F. Ballarini, P. Bruschi, L. Ciani and et al. An improved neutron autoradiography set-up for 10B concentration measurements in biological samples. Rep. Pract. Oncol. Radiother. 21 (2016) 123-128. [4] H. Koivunoro, D. Bleuel, U. Nastasi, T. Lou, J. Reijonen, K.N. Leung. BNEUTRON THERAPY dose distribution in liver with epithermal D–D and D–T fusion-based neutron beams. Appl. Radiat. Isot. 61 (2004) 853-859. [5] J.T. Smith, R.M. Hawkins, J.A. Guthrie, D.J. Wilson, P.M. Arnold, S. Boyes and et al. Effect of slice thickness on liver lesion detection and characterisation by multidetector CT. J. Med. Imaging. Radiat. Oncol. 54 (2010) 188-193. [6] G.N. Hounsfield. Computed medical imaging. J. Radiol. 210 (1980) 22-28. [7] T.E. Reeves, P. Mah, W.D. McDavid. Deriving Hounsfield units using grey levels in cone beam CT: a clinical application. Dentomaxillofac. Radiol. 41 (2012) 500-508. [8] J.J. McBride, M. Mason Guest, E. L. Scott. The Storage of the Major Liver Components; emphasizing the relationship of glycogen to water in the liver and the hydration of glycogen. J. Biol. Chem. 139 (1941) 943-952

Files

Share

How to cite

Statistics