The Feasibility of Cylindrical Step-Wedge Phantom for Evaluating Modulation Transfer Function of CT Image : Variation of Field of View

Authors

  • Neneng Kurnia Sari  Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Heri Sutanto  Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Choirul Anam  Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Ariij Naufal  Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Riska Amilia  Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof. Soedarto SH, Tembalang, Semarang 50275, Central Java, Indonesia

DOI:

https://doi.org//10.32628/IJSRST52310632

Keywords:

Spatial resolution, modulation transfer function (MTF), edge spread function (ESF), field of view (FOV), cylindrical step-wedge water CT phantom

Abstract

This study aims to evaluate the modulation transfer function (MTF) from a cylindrical step-wedge phantom having diameters of 8-32 cm at various field of views (FOVs). In this study, MTF curves were measured based on the edge spread function (ESF) using IndoQCT software. In addition, noises were also measured using IndoQCT software. It was found that the MTF curve decreased as the FOV increases. The difference in the MTF 10% from FOVs of 35-50 cm was 16-20% with a p-value of 0.392. Meanwhile, the difference in MTF 50% was 16-21% with the same p-value of 0.392. It was also found that MTF curve also decreased as the phantom diameter increases. The differences in MTF 10% and 50% from phantom diameter of 8-32 cm were 6-14% and 6-16%. It is resulted that the noise level decreases as the FOV increases and the noise level also decreased as the phantom diameter increases.

References

  1. Bankier AA, Kressel HY. Through the Looking Glass revisited: the need for more meaning and less drama in the reporting of dose and dose reduction in CT. Radiology. 2012;265(1):4-8. doi:10.1148/radiol.12121145
  2. Nakahara S, Tachibana M, Watanabe Y. One-year analysis of Elekta CBCT image quality using NPS and MTF. J Appl Clin Med Phys. 2016 May 8;17(3):211-222. doi: 10.1120/jacmp.v17i3.6047. PMID: 27167279; PMCID: PMC5690923.
  3. Xie X, Fan H, Wang A, Zou N, Zhang Y. Regularized slanted-edge method for measuring the modulation transfer function of imaging systems. Appl Opt. 2018;57(22):6552-6558. doi:10.1364/AO.57.006552
  4. Maruyama S. Assessment of Uncertainty Depending on Various Conditions in Modulation Transfer Function Calculation Using the Edge Method. J Med Phys. 2021;46(3):221-227. doi:10.4103/jmp.JMP_36_21
  5. Kayugawa A, Ohkubo M, Wada S. Accurate determination of CT point-spread-function with high precision. J Appl Clin Med Phys. 2013;14(4):3905. Published 2013 Jul 8. doi:10.1120/jacmp.v14i4.3905
  6. Manson EN, Bambara L, Nyaaba RA, et al. Comparison of Modulation Transfer Function Measurements for Assessing The Performance of Imaging Systems. Medical Physics. 2017;5(2):188-191.
  7. Kim, K. B., Jeong, S. H., Lee, S. H., & Kim, K. (2021). Investigation of patch-based modulation transfer function (MTF) prediction framework in radiography. Radiation Physics and Chemistry, 189. https://doi.org/10.1016/j.radphyschem.2021.109728
  8. Valzano, S., & Matheoud, R. (2014). Quality Controls in x-Ray Imaging. In Comprehensive Biomedical Physics (pp. 167–191). Elsevier. https://doi.org/10.1016/b978-0-444-53632-7.00208-2
  9. Anam C, Fujibuchi T, Budi WS, Haryanto F, Dougherty G. An algorithm for automated modulation transfer function measurement using an edge of a PMMA phantom: Impact of field of view on spatial resolution of CT images. J Appl Clin Med Phys. 2018;19(6):244-252. doi:10.1002/acm2.12476
  10. Nofrianto, Choirul Anam, Eko Hidayanto, Ariij Naufal. Comparison of MTFs Measured using IndoQCT and ImQuest Software on GE CT Phantom Images. Int J Sci Res Sci Technol [Internet]. 2023 Jun 16;852–8. Available from: https://ijsrst.com/IJSRST523103156
  11. Anam C, Naufal A, Budi WA, Sutanto H, Haryanto F, Dougherty G. (2023). Manual IndoQCT Version 22a. Undip Press
  12. Zhang J, Bao Z, Huang X, Jiang D, Xie C, Zhou Y. Methods to evaluate the performance of kilovoltage cone-beam computed tomography in the three-dimensional reconstruction space. Int J Radiat Res. 2019; 17(2) :189-202. doi: http://ijrr.com/article-1-2494-en.html
  13. Salimova N, Hinrichs JB, Gutberlet M, Meyer BC, Wacker FK, von Falck C. The impact of the field of view (FOV) on image quality in MDCT angiography of the lower extremities. Eur Radiol. 2022;32(5):2875-2882. doi:10.1007/s00330-021-08391-x
  14. Safi Y, Ghazizadeh Ahsaie M, Jafarian Amiri M. Effect of the Field of View Size on CBCT Artifacts Caused by the Presence of Metal Objects in the Exomass. Int J Dent. 2022;2022:2071108. Published 2022 Sep 9. doi:10.1155/2022/2071108
  15. Miyata T, Yanagawa M, Hata A, Honda, O, Yoshida Y, Kikuchi N, Tsubamoto M, Tsukagoshi S, Uranishi A, Tomiyama N. Influence of field of view size on image quality: ultra-high-resolution CT vs. conventional high-resolution CT. Eur Radiol. 2020;30(6):3324-3333. doi:10.1007/s00330-020-06704-0
  16. Niktash A, Mehralizadeh S, Talaeipour A. The Effect of Different Field of View Sizes on Contrast-to-Noise Ratio of Cone-Beam Computed Tomography Units: An In-Vitro Study. Front Dent. 2022;19:32. Published 2022 Sep 18. doi:10.18502/fid.v19i32.10804
  17. Takenaga T, Katsuragawa S, Goto M, Hatemura M, Uchiyama Y, Shiraishi J. Modulation transfer function measurement of CT images by use of a circular edge method with a logistic curve-fitting technique. Radiol Phys Technol. 2015;8(1):53-59. doi:10.1007/s12194-014-0286-x
  18. Cho HW, Yoon HJ, Yoon JC. Analysis of crack image recognition characteristics in concrete structures depending on the illumination and image acquisition distance through outdoor experiments. Sensors (Basel). 2016;16(10):1646. doi:10.3390/s16101646
  19. Zarb, F., Rainford, L., & McEntee, M. F. (2010). Image quality assessment tools for optimization of CT images. In Radiography (Vol. 16, Issue 2, pp. 147–153). https://doi.org/10.1016/j.radi.2009.10.002
  20. Solomon J, Wilson J, Samei E. Characteristic image quality of a third generation dual-source MDCT scanner: Noise, resolution, and detectability. Med Phys. 2015;42(8):4941-4953. doi:10.1118/1.4923172
  21. Oshina I, Spigulis J. Beer-Lambert law for optical tissue diagnostics: current state of the art and the main limitations. J Biomed Opt. 2021;26(10):100901. doi:10.1117/1.JBO.26.10.100901
  22. Mayerhöfer TG, Pahlow S, Popp J. The Bouguer-Beer-Lambert Law: Shining Light on the Obscure. Chemphyschem. 2020;21(18):2029-2046. doi:10.1002/cphc.202000464

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Published

2023-12-30

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Research Articles

How to Cite

[1]
Neneng Kurnia Sari, Heri Sutanto, Choirul Anam, Ariij Naufal, Riska Amilia, " The Feasibility of Cylindrical Step-Wedge Phantom for Evaluating Modulation Transfer Function of CT Image : Variation of Field of View, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 10, Issue 6, pp.218-225, November-December-2023. Available at doi : https://doi.org/10.32628/IJSRST52310632