Investigation the effect of various filters on X-ray beam at dual source CT scan by introducing Erbium as new filter

Document Type : Original Article

Authors

1 Nuclear Engineering, Faculty of Sciences and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran

2 Nuclear Engineering Group, Faculty Sciences, and Modern Technologies, Graduate University of Advanced Technology, Kerman, Iran

10.22052/rsm.2024.254297.1049

Abstract

In this research, a study is performed in order to determine the optimal spectral filtration in dual-source imaging system and its effect on increasing the mean energy and energy separation between high and low energy spectra .X-ray spectrum is simulated using Monte carlo Fluka 2011 simulation code. X-ray tube with tungsten anode and 1.6 mm aluminum inherent filter was designed. Then, an additional filter was applied to the 140 keV tube and the low-energy spectrum was left unchanged to prevent further reductions in the output .In the next step,in order to minimizing the overlaps among the spectra, former filter was implemented and mean energy difrrences was investigated. Filter’s materials have selected from several elements in which, Tin and bronze are practical options. Based on our results, tin filter with a thickness of 0.5 mm has increased the average energy difference from 17.8 to 40.6 keV. In the second evaluation, using bronze filter on high and Eribium on the low energy tube, the average energy difference was increased from 17.8 to 45.87 keV.In our evaluation The overlap of low and high energy spectra have been decreased significantly.In addition to examine the sensitivity of different materials, the difrences in dual energy ratio has been compared. The larger the difference is, the contrast between two materials has increased .This increase in dual energy ratio is expected to improve the performance of dual-source CT scans in increasing contrast and improving image quality and dose reduction.

Keywords


  1. A. Bharath. Introductory Medical Imaging. Springer Nature, 2022.
  2. F. Draghi, G. Cocco, F. M. Richelmi, C. Schiavone. Abdominal wall sonography: a pictorial review. J. Ultrasound 23 (3) (2020) 265-278.
  3. S. Noble, A. F. Mejia, A. Zalesky, D. Scheinost. Improving power in functional magnetic resonance imaging by moving beyond cluster-level inference. Proc. Nat. Academy Sci. 119 (32) (2022) e2203020119.
  4. Q. B. Carroll. Radiography in the Digital Age: Physics-exposure-radiation Biology. Charles C Thomas Publisher, 2023.
  5. C. J. Harvey. Principles of Radiology. Surgery (Oxford) 26 (6) (2008) 235-238.
  6. N. E. Shalom, G. X. Gong, M. Auster. Fluoroscopy: An essential diagnostic modality in the age of high-resolution cross-sectional imaging. World J. Radiol. 12 (10) (2020) 213.
  7. M. S. Jochelson, M. B. I. Lobbes. Contrast-enhanced Mammography: State of the Art. Radiol. 299 (1) (2021) 36-48.
  8. P. J. Withers, C. Bouman, S. Carmignato, V. Cnudde, D. Grimaldi, C. K. Hagen, E. Maire, M. Manley, A. Du Plessis, S. R. Stock. X-ray computed tomography. Nat. Rev. Methods Primers 1 (2021) 18.
  9. H. Villarraga-Gómez, E. L. Herazo, S. T. Smith. X-ray computed tomography: from medical imaging to dimensional metrology. Precision Eng. 60) 2019) 544-569.
  10. A. Axiaq, A. Almohtadi, S. A. Massias, D. Ngemoh, A. Harky. The role of computed tomography scan in the diagnosis of COVID-19 pneumonia. Curr. Opin. Pulm. Med. 27 (3) (2021) 163-168.
  11. X. Ou, X. Chen, X. Xu, L. Xie, X. Chen, Z. Hong, H. Bai, X. Liu, Q. Chen, L. Li, H. Yang. Recent development in X-ray imaging technology: future and challenges. Research (Wash D C) (2021) 9892152.
  12. J. T. Bushberg, J. M. Boone. The Essential Physics of Medical Imaging. 3rd Ed. Lippincott Williams & Wilkins, Philadelphia, 2011.
  13. G. N. Hounsfield. Computerized transverse axial scanning (tomography): Part 1. Description of system. British J. Radiol. 46 (552) (1973) 1016-1022.
  14. C. H. McCollough, S. Leng, L. Yu, J. G. Fletcher. Dual-and multi-energy CT: principles, technical approaches, and clinical applications. Radiol. 276 (3) (2015) 637-653.
  15. J. A. Seibert. X-ray imaging physics for nuclear medicine technologists. Part 1: Basic principles of x-ray production. J. Nuclear Med. Tech. 32 (3) (2004) 139-147.
  16. R. Liu, S. Zhang, T. Zhao, J. A. O'Sullivan, J. F. Williamson, T. Webb, M. Porras-Chaverri, B. Whiting. Impact of bowtie filter and detector collimation on multislice CT scatter profiles: A simulation study. Med. Phys. 48 (2) (2021) 852-870.
  17. D. Tack, P. A. Gevenois (Eds). Radiation Dose from Adult and Pediatric Multidetector Computed Tomography. Medical Radiology. Springer, Berlin, Heidelberg. 2007.
  18. C. Ahdida, D. Bozzato, D. Calzolari, F. Cerutti, N. Charitonidis, A. Cimmino, A. Coronetti, G. D’Alessandro, A. Donadon Servelle, L. Esposito, R. Froeschl, R. García Alía, A. Gerbershagen, S. Gilardoni, D. Horváth, G. Hugo, A. Infantino, V. Kouskoura, A. Lechner, B. Lefebvre, G. Lerner, M. Magistris, A. Manousos, G. Moryc, F. Ogallar Ruiz, F. Pozzi, D. Prelipcean, S. Roesler, R. Rossi, M. Sabaté Gilarte, F. Salvat Pujol, P. Schoofs, V. Stránský, C. Theis, A. Tsinganis, R. Versaci, V. Vlachoudis, A. Waets, M. Widorski. New capabilities of the FLUKA multi-purpose code. Frontiers Phys. 9 (2022) 788253.
  19. J. Punnoose, J. Xu, A. Sisniega, W. Zbijewski, J. H. Siewerdsen. spektr 3.0-A computational tool for x‐ray spectrum modeling and analysis. Med. Phys. 43 (8) (2016) 4711-4717.
  20. A. J. Einstein, M. J. Henzlova, S. Rajagopalan. Estimating risk of cancer associated with radiation exposure from 64-slice computed tomography coronary angiography. JAMA 298 (3) (2007) 317-323.
  21. D. Manning. The risk of cancer from radiography. Radiography 10 (3) (2004) 171-172.
  22. Y. -H. Shao, K. Tsai, S. Kim, Y. -J. Wu, K. Demissie. Exposure to tomographic scans and cancer risks. JNCI Cancer Spectr. 4 (1) (2020) pkz072.