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Automated patient centering of computed tomography images and its implementation to evaluate clinical practices in three hospitals in Indonesia

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: This study aims to develop a software tool for investigating patient centering profiles of axial CT images and to implement it to evaluate practices in three hospitals in Indonesia. Methods: The evaluation of patient centering accuracy was conducted by comparing the center coordinate of the patient’s image to the center coordinates of the axial CT image. This process was iterated for all slices to yield an average patient mis-centering in both the x- and y-axis. We implemented the software to evaluate the profile of centering on 268 patient images from the head, thorax, and abdomen examinations taken from three hospitals. Results: We found that 82% of patients were mis-centered in the y-axis (i.e., placed more than 5 mm from the iso-center), with 49% of patients placed 10–35 mm from the iso-center. Most of the patients had a tendency to be placed below the iso-centers. In head examinations, patients were more precisely positioned than in the other examinations. We did not find any significant difference in mis-centering between males and females. We found that there was a slight difference between mis-centering in adult and pediatric patients. Conclusion: Software for automated patient centering was successfully developed. Patients in three hospitals in Indonesia had a tendency to be placed under the iso-center of the gantry.
Słowa kluczowe
Rocznik
Strony
207--214
Opis fizyczny
Bibliogr. 29 poz., rys., tab.
Twórcy
autor
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
autor
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
autor
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
autor
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
autor
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Department of Physics, Faculty of Sciences and Mathematics, Diponegoro University, Jl. Prof Soedarto, SH, Tembalang, Semarang 50275, Central Java, Indonesia
  • Department of Applied Physics and Medical Imaging, California State University Channel Islands, Camarillo, CA 93012, USA
Bibliografia
  • 1. Shahi V, Brinjikji W, Cloft HJ, Thomas KB. Trends in CT utilization for pediatric fall patients in US emergency departments. Acad Radiol. 2015;22(7):898-903. https://doi.org/10.1016/j.acra.2015.02.016
  • 2. Brinjikji W, Kallmes DF, Cloft HJ. Rising utilization of CT in adult fall patients. Am J Roentgenol. 2015;204(3):558-562. https://doi.org/10.2214/AJR.14.13107
  • 3. Goldman LW. Principles of CT: Radiation dose and image quality. J Nucl Med Technol. 2007;35:213-225. https://doi.org/10.2967/jnmt.106.037846
  • 4. Hooper T, Eccles G, Milliken T, Mathieu‐Burry JR, Reed W. Dose reduction in CT imaging for facial bone trauma in adults: A narrative literature review. J Med Rad Sci. 2019;66(2):122-132. https://doi.org/10.1002/jmrs.319
  • 5. Anam C, Haryanto F, Widita R, Arif I, Dougherty G. The evaluation of the effective diameter (Deff) calculation and its impact on the size-specific dose estimate (SSDE). Atom Indonesia. 2017;43(1):55-60. https://doi.org/10.17146/aij.2017.617
  • 6. Yabuuchi H, Kamitani T, Sagiyama K, et al. Clinical application of radiation dose reduction for head and neck CT. Eur J Radiol. 2018;107:209-215. https://doi.org/10.1016/j.ejrad.2018.08.021
  • 7. Kataria B, Nilsson Althén J, Smedby Ö, Persson A, Sökjer H, Sandborg M. Image quality and potential dose reduction using advanced modeled iterative reconstruction (ADMIRE) in abdominal CT-A review. Radiat Prot Dosimetry. 2021;195(3-4):177-187. https://doi.org/10.1093/rpd/ncab020
  • 8. Kataria B, Sandborg M, Althén JN. Implications of patient centering on organ dose in computed tomography. Radiat Prot Dosimetry. 2016;169(1-4):130-135. https://doi.org/10.1093/rpd/ncv527
  • 9. Habibzadeh MA, Ay MR, Kamali Asl AR, Ghadiri H, Zaidi H. Impact of mis-centering on patient dose and image noise in x-ray CT imaging: Phantom and clinical studies. Phys Med. 2012;28(3):191-199. https://doi.org/10.1016/j.ejmp.2011.06.002
  • 10. Furukawa Y, Matsubara K, Tsutsumi Y. A comparison of automatic and manual compensation methods for the calculation of tube currents during off centered patient positioning with a noise based automatic exposure control system in computed tomography. Phys Eng Sci Med. 2021;44(3):823-832. https://doi.org/10.1007/s13246-021-01033-y
  • 11. Euler A, Saltybaeva N, Alkadhi H. How patient off-centering impacts organ dose and image noise in pediatric head and thoracoabdominal CT. Euro Radiol. 2019;29(12):6790-6793. https://doi.org/10.1007/s00330-019-06330-5
  • 12. Sabarudin A, Mustafa Z, Nassir KM, Hamid HA, Sun Z. Radiation dose reduction in thoracic and abdominal-pelvic CT using tube current modulation: a phantom study. J Appl Clin Med Phys. 2014;16(1):319-328. https://doi.org/10.1120/jacmp.v16i1.5135
  • 13. Greffier, J, Frandon, J, de Forges H, et al. Impact of additional mattresses in emergency CT on the automated patient centering proposed by a 3D camera: a phantom study. Sci Rep. 2021;11:13191. https://doi.org/10.1038/s41598-021-92637-7
  • 14. Cheng PM. Patient vertical centering and correlation with radiation output in adult abdominopelvic CT. J Digit Imaging. 2016;29(4):428-437. https://doi.org/10.1007/s10278-016-9861-5
  • 15. Sookpeng S, Martin CJ, Kadman B. Eye lens radiation dose to mis-centering patients and health-care staff from head computed tomography. J Rad Nu. 2019;38:193-199. https://doi.org/10.1016/j.jradnu.2019.05.002
  • 16. Anam C, Fujibuchi T, Toyoda T, et al. The impact of head miscentering on the eye lens dose in CT scanning: Phantoms study. J Phys: Conf Ser. 2019;1204:012022. https://doi.org/10.1088/1742-6596/1204/1/012022
  • 17. Booij R, van Straten M, Wimmer A, Budde RPJ. Automated patient positioning in CT using a 3D camera for body contour detection: accuracy in pediatric patients. Eur Radiol. 2021;31(1):131-138. https://doi.org/10.1007/s00330-020-07097-w
  • 18. Toth T, Ge Z, Daly MP. The influence of patient centering on CT dose and image noise. Med Phys. 2007;24(7):3093-3101. https://doi.org/10.1118/1.2748113
  • 19. Li J, Udayasankar UK, Toth TL, Seamans J, Small WC, Kalra MK. Automatic patient centering for MDCT: Effect on radiation dose. Am J Roentgenol. 2007;188:547-552. https://doi.org/10.2214/AJR.06.0370
  • 20. ICRP. Assessing dose of the representative person for the purpose of the radiation protection of the public. ICRP Publication 101a. Ann. ICRP. 2006;36
  • 21. Anam C, Naufal A, Fujibuchi T, Matsubara K, Dougherty G. Automated development of the contrast-detail curve based on statistical low-contrast detectability in CT images. J Appl Clin Med Phys. 2022;23:e13719. https://doi.org/10.1002/acm2.13719
  • 22. Anam C, Haryanto F, Widita R, Arif I. Automated estimation of patient's size from 3D image of patient for size specific dose estimates (SSDE). Adv Sci Eng Med. 2015;7(10): 892-896. https://doi.org/10.1166/asem.2015.1780
  • 23. Anam C, Haryanto F, Widita R, Arif I, Dougherty G. Automated calculation of water-equivalent diameter (DW) based on AAPM task group 220. J Appl Clin Med Phys. 2016;17(4):320-333. https://doi.org/10.1120/jacmp.v17i4.6171
  • 24. International Atomic Energy Agency. Quality assurance programme for computed tomography: Diagnostic and therapy applications. IAEA Human Health Series No. 19. IAEA. Vienna. 2012
  • 25. Afrieda N, Anam C, Budi WS, Dougherty G. Automated patient position in CT examination using a Kinect camera. J Phys: Conf Ser. 2020;1505:012034. https://doi.org/10.1088/1742-6596/1505/1/012034
  • 26. Kaasalainen T, Palmu K, Reijonen V, Kortesniemi M. Effect of patient centering on patient dose and image noise in chest CT. Am J Roentgenol. 2014;203(1):123-130. https://doi.org/10.2214/AJR.13.12028
  • 27. Akin-Akintayo OO, Alexander LF, Neill R, et al. Prevalence and severity of off-centering during diagnostic CT: Observations from 57,621 CT scans of the chest, abdomen, and/or pelvis, current problems in diagnostic radiology. Curr Probl Diagn Radiol. 2019;48(3):229-234. https://doi.org/10.1067/j.cpradiol.2018.02.007
  • 28. Gudjonsdottir J, Svensson JR, Campling S, Brennan PC, Jonsdottir B. Efficient use of automatic exposure control systems in computed tomography requires patient positioning. Acta Radiol. 2009;50(9):1035-1041. https://doi.org/10.3109/02841850903147053
  • 29. DeWeese L, Griglock T, Moody A, Mehlberg A, Winters C. The improvement of patient centering in computed tomography through a technologist focused education initiative. J Digit Imaging. 2022;35(2):327-334. https://doi.org/10.1007/s10278-021-00580-w
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9dc93b82-d9da-4c5b-96ce-2489b5866b0c
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