Radiation Dose and Image Quality with Exposure Factor Variation Using a Virtual Grid in Digital Radiography

Authors

  • Fitrus Ardoni  Postgraduate Diagnostic Imaging Program, Health Polytechnic of Semarang, Semarang, Indonesia
    Department of Diagnostic Imaging and Radiotherapy, Health Polytechnic of Ministry of Health Jakarta II, Jakarta, Indonesia
  • Lina Choridah  Department of Diagnostic Imaging and Radiotherapy, Health Polytechnic of Semarang, Semarang, Indonesia
  • Edy Susanto  Department of Diagnostic Imaging and Radiotherapy, Health Polytechnic of Semarang, Semarang, Indonesia
  • Muhammad Irsal  Department of Diagnostic Imaging and Radiotherapy, Health Polytechnic of Ministry of Health Jakarta II, Jakarta, Indonesia

DOI:

https://doi.org//10.32628/IJSRST52310649

Keywords:

Exposure Factor, Virtual Grid, Radiation Dose, Image Quality.

Abstract

Digital radiography technology provides many advantages. However, there are still frequent repetitions of inspections due to failure to determine the exposure factor due to a decrease in image quality. Virtual Grid is a digital radiographic image processing technology that converts image quality that is deteriorating due to X-ray scattering to better image quality by reducing the effects of X-ray scattering. Application of a virtual grid can contribute to improving image quality and increasing the procedural efficiency of the workflow in a radiographic examination. This study uses a research-experimental design, with a One-Shot Case Study. The sample selection of 60 samples was carried out randomly by judgmental or purposive sampling. The sampling technique was carried out with specific considerations for the research objectives to determine the optimal exposure factor by using a virtual grid for the skull, lumbar, and pelvic radiographic examinations. Then, it was analyzed quantitatively and qualitatively visually by three radiologists—a bivariate analysis of data using one-way ANOVA. Qualitative analysis was carried out as well as a test. Feel free to assess the agreement of the informants. Results In the quantitative and qualitative analysis, the exposure factor and the ideal virtual grid ratio for optimization are skull AP: 106 kV, 2 mAs, ratio 14:1, skull lateral: 106 kV, 1.25 mAs, ratio 14:1, skull lumbar AP: 106 kV, 4 mAs, ratio 14:1, skull lumbar lateral: 113 kV, 6.3 mAs, 10:1 ratio, and pelvis AP: 92 kV, 8 mAs, 14:1 ratio.

References

  1. S. Benfield, J. D. Hewis, and C. M. Hayre, “Investigating perceptions of ‘dose creep’ amongst student radiographers: A grounded theory study,” Radiography, vol. 27, no. 2, pp. 605–610, 2021, doi: 10.1016/j.radi.2020.11.023.
  2. L. Bastiani et al., “Patient Perceptions and Knowledge of Ionizing Radiation from Medical Imaging,” JAMA Netw Open, vol. 4, no. 10, pp. 1–13, 2021, doi: 10.1001/jamanetworkopen.2021.28561.
  3. G. Andria, F. Attivissimo, A. Di Nisio, A. M. L. Lanzolla, G. Guglielmi, and R. Terlizzi, “Dose optimization in chest radiography: System and model characterization via experimental investigation,” IEEE Trans Instrum Meas, vol. 63, no. 5, pp. 1163–1170, 2014, doi: 10.1109/TIM.2013.2282411.
  4. Bapeten, “Tingkat Panduan Diagnostik Atau Diagnostic Reference Level ( Drl ),” no. 8, 2019.
  5. Kepala Badan Pengawas Tenaga Nuklir Republik Indonesia, “Peraturan Badan Pengawas Tenaga Nuklir Republik Indonesia Nomor 4 Tahun 2020 Tentang Keselamatan Radiasi Pada Penggunaan Pesawat Sinar-X Dalam Radiologi Diagnostik Dan Intervensional,” pp. 1–52, 2020.
  6. J. Vassileva and M. Rehani, “Diagnostic reference levels,” AJR Am J Roentgenol, vol. 204, no. 1, pp. W1–W3, 2015, doi: 10.2214/AJR.14.12794.
  7. M. Irsal, E. Hidayanto, J. Fisika, F. Sains, and U. Diponegoro, “Analisa Pengaruh Faktor Eksposi Terhadap Entrance Surface Air Kerma (Esak),” Youngster Physics Journal, vol. 3, no. 4, pp. 271–278, 2014.
  8. K. Shamsi et al., “Evaluation of effective dose and entrance skin dose in digital radiology,” Polish Journal of Medical Physics and Engineering, vol. 26, no. 2, pp. 119–125, 2020, doi: 10.2478/pjmpe-2020-0013.
  9. S. C. Bushong, Radiologic Science for Technologists:Physics,Biology,and Protection, Eleventh E. Elsivier, 2017.
  10. A. N. Mukhtar and H. Sutanto, “Analisa Pengaruh Grid Rasio Dan Faktor Eksposi Terhadap Gambaran Radiografi Phantom Thorax,” Youngster Physics Journal, vol. 4, no. 1, pp. 133–138, 2015.
  11. M. Y. Takahiro Kawamura, Satoshi Naito, Kayo Okano, “Improvement in Image Quality and Workflow of X-Ray Examinations using a New Image Processing Method, ‘Virtual Grid Technology,’” Fujifilm research & development, no. 60, pp. 21–27, 2015.
  12. D. Sugiyono, Metode Penelitian Kuantitatif, Kualitatif, dan Tindakan. 2013.
  13. Y. Marihot, S. Sari, and A. Endang, Buku Metode Penelitian Kualitatif & Kuantitatif, vol. 1, no. 1. 2022.
  14. M. B. Freitas, R. B. Pimentel, L. F. Braga, F. S. A. Salido, R. F. C. A. Neves, and R. B. Medeiros, “Patient dose optimization for computed radiography using physical and observer-based measurements as image quality metrics,” Radiation Physics and Chemistry, vol. 172, p. 108768, Jul. 2020, doi: 10.1016/J.RADPHYSCHEM.2020.108768.
  15. W. Budiaji, “The Measurement Scale and Number of Responses in Likert Scale,” Journal of Agricultural and Fisheries Sciences, vol. 2, no. 2, pp. 127–133, 2013, doi: 10.31227/osf.io/k7bgy.
  16. P. Brian Nett, “X-ray Contrast To Noise (CNR) Illustrated Examples Of Image Noise (SNR, Quantum Mottle) For Radiologic Technologists • How Radiology Works,” https://howradiologyworks.com/x-ray-cnr/. Accessed: Sep. 15, 2022. [Online]. Available: https://howradiologyworks.com/x-ray-cnr/
  17. T. Pengpan, N. Rattanarungruangchai, J. Dechjaithat, P. Panthim, P. Siricharuwong, and A. Prapan, “Optimization of Image Quality and Organ Absorbed Dose for Pediatric Chest X-Ray Examination: In-House Developed Chest Phantom Study,” Radiol Res Pract, vol. 2022, pp. 1–10, 2022, doi: 10.1155/2022/3482458.
  18. A. J. Abdi et al., “Visual evaluation of image quality of a low dose 2d/3d slot scanner imaging system compared to two conventional digital radiography x-ray imaging systems,” Diagnostics, vol. 11, no. 10, pp. 1–15, 2021, doi: 10.3390/diagnostics11101932.
  19. “Estimasi Reliabilitas Antar Rater (Interrater Reliability) dengan SPSS - Semesta Psikometrika.” Accessed: Sep. 19, 2022. [Online]. Available: https://www.semestapsikometrika.com/2018/10/estimasi-reliabilitas-antar-rater.html
  20. F. Mau, S. Supargiyono, and E. E. Herdiana Murhandarwati, “Koefesien Kappa sebagai Indeks Kesepakatan Hasil Diognosis Mikroskopis Malaria di Kabupaten Belu Nusa Tenggara Timur,” Buletin Penelitian Kesehatan, vol. 43, no. 2, 2015, doi: 10.22435/bpk.v43i2.4145.117-124.
  21. R. T. Quinn B. Carroll, M.ED., Radiography in The Digital Age:Physics-Exposure-Radiation Biology. Charles C Thomas • Publisher, LTD, 2011.
  22. Badan Pengawas Tenaga Nuklir (BAPETEN), “Keputusan Kepala Badan Pengawas Tenaga Nuklir Nomor: 1211/K/V/2021 Tentang Penetapan Nilai Tingkat Panduan Diagnsotik Indonesia (Indonesian Diagnostic Reference Level) Untuk Modalitas Sinar-X, CT Scan Dan Radiografi Umum,” p. 4, 2021.

International Journal of Scientific Research in Science and Technology

Downloads

Published

2023-12-30

Issue

Volume 10, Issue 6, November-December-2023

Section

Research Articles

License

Copyright (c) IJSRST

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Fitrus Ardoni, Lina Choridah, Edy Susanto, Muhammad Irsal, " Radiation Dose and Image Quality with Exposure Factor Variation Using a Virtual Grid in Digital Radiography, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 10, Issue 6, pp.323-331, November-December-2023. Available at doi : https://doi.org/10.32628/IJSRST52310649