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Low Dose Brain CT, Comparative Study with Brain Post Processing Algorithm

Published:20 March 2020Publication History

ABSTRACT

Computed tomography (CT) scanners and CT exams increase continuously. The researchers aim to minimize the ionizing radiation dose by introducing new CT protocols, providing diagnostic CT images with a lower radiation dose to patients. However, such studies encounter difficulties, when the radiation dose is lowered, the quality of images becomes less and sometimes not diagnostic. In this study, the researcher aims to provide a low dose brain CT protocol, in order to then determine if the images match the quality criteria of Brain CT; and determine the diagnostic appearance of the images. Then, the researcher will compare the results obtained from the Brain CT, as well as the brain post-processing algorithm to determine which one provides a better diagnostic image, and a better match for the quality criteria of Brain CT, by the Numerical criterion (1: weak, 2: moderate, 3:perfect) which is used by expert medical imaging technologists, On a sample of 35 patients; the first brain CT was conducted by 22 milli-gray (mGy) volume computed tomography dose index (CTDIvol); the resulting image was noisy, with a poor match for quality criteria, then CTDIvol was raised to 25 mGy, then to 30 mGy, and finally to 33.8 mGy. At this point, the image was acceptable to complete the study. Four radiologists have been engaged to determine if the image provides diagnostic appearance, then six expert medical imaging technologists were involved to determine the quality criteria. These steps were followed for the Brain CT before and after applying the post-processing algorithm. Then the results were compared with the reference study of brain CT. The results for low dose brain CT were diagnostic and matching the quality criteria for brain CT. After applying the brain post-processing algorithm the image's diagnostic appearance was disturbed, the suggested protocol by the study provided a 47% dose reduction, from the standard protocol which uses 63 mGy. The problem of signal reduction is solved by using iDose4, which improves the signal to noise ratio (SNR).

References

  1. PhD2 A Löve, MD, corresponding author1 M-L Olsson, MSc, 2 R Siemund, MD, PhD, 1 F Stålhammar, MD, 1 I M Björkman-Burtscher, MD, PhD, 1, 3 and M Söderberg. 2013. Six iterative reconstruction algorithms in brain CT: a phantom study on image quality at different radiation dose levels. Br J Radiol 73, 9 (2013), 384--395.Google ScholarGoogle Scholar
  2. Italo Aprile, I. Ottaviano, E. Buono, A. Di Renzo, P. Fiaschini, and P. Ottaviano. 2012. Low-dose brain computer tomography sensitivity: A comparative study with a conventional technique. Neuroradiol. J. 25, 2 (2012), 151--162.Google ScholarGoogle ScholarCross RefCross Ref
  3. Heinrich J Audebert and Jochen B Fiebach. 2015. Brain Imaging in Acute Ischemic Stroke - MRI or CT? (2015). DOI:https://doi.org/10.1007/s11910-015-0526-4Google ScholarGoogle Scholar
  4. R. Baxter, N. Hastings, A. Law, and E. J.. Glass. 2008. When to order CT vs. MRI. Prem. Radiol. 39, 5 (2008), 3.Google ScholarGoogle Scholar
  5. Nour-Eldin NE3. Beeres M1, Wichmann JL2, Paul J2, Mbalisike E2, Elsabaie M2, Vogl TJ2. 2015. CT chest and gantry rotation time: does the rotation time influence image quality? pubmed 56, 8 (2015), 950--4.Google ScholarGoogle Scholar
  6. Et Al Bruening, R. 2006. Protocols For Multislice CT, 2nd Edition (2nd ed.). springer.Google ScholarGoogle Scholar
  7. A Calzado, R Rodri, and A Mun. 2000. Quality criteria implementation for brain and lumbar spine CT examinations. 73, 4 (2000), 384--395.Google ScholarGoogle Scholar
  8. Hamacher J Cohnen M, Fischer H. 2000. CT by use of reduced current and kilovoltage: relationship between image quality and dose reduction. Am J Neuroradio 9, 11 (2000), 1654--60.Google ScholarGoogle Scholar
  9. Tim Dalgleish, J. Mark G.. Williams, Ann-Marie J. Golden, Nicola Perkins, Lisa Feldman Barrett, Phillip J. Barnard, Cecilia Au Yeung, Victoria Murphy, Rachael Elward, Kate Tchanturia, and Edward Watkins. 2007. Protocols for Multislice CT 4- and 16-row Applications.Google ScholarGoogle Scholar
  10. Lee W Goldman. 2008. Principles of CT: Multislice CT*. J Nucl Med Technol 2008; 36, 12 (2008), 57--69.Google ScholarGoogle Scholar
  11. Walter Huda. 2011. Radiation dosimetry in CT: the role of the manufacturer. 3, 2 (2011), 247--259. Retrieved from https://www.openaccessjournals.com/articles/radiation-dosimetry-in-ct-the-role-of-the-manufacturer-9141.htmlGoogle ScholarGoogle Scholar
  12. Lois E.Romans. 2010. Computed Tomography for Technologists A Comprehensive Text by Lois E. Romans 2010 (1st ed.). springer.Google ScholarGoogle Scholar
  13. philips. Philips Ingenutiy Family Manual Guide (1st ed.).Google ScholarGoogle Scholar
  14. philips. 2011. iDose 4 iterative reconstruction technique.Google ScholarGoogle Scholar
  15. Medical Radiology. 2007. Radiation Dose from Adult and Pediatric Multidetector Computed Tomography. springer.Google ScholarGoogle Scholar
  16. Siva P. Raman, Mahadevappa Mahesh, Robert V. Blasko, and Elliot K. Fishman. 2013. CT scan parameters and radiation dose: Practical advice for radiologists. J. Am. Coll. Radiol. 10, 11 (2013), 840--846.Google ScholarGoogle ScholarCross RefCross Ref
  17. Adult Routine, Head Ct, and Protocols Version. 2016. Routine Ct Head (Brain).Google ScholarGoogle Scholar
  18. Horrocks JA Sohaib SA, Peppercorn PD. 2001. Effect of decreasing mAs on image quality and patients dose in sinus CT. Br J Radiol (2001).Google ScholarGoogle Scholar

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      cover image ACM Other conferences
      DMIP '19: Proceedings of the 2019 2nd International Conference on Digital Medicine and Image Processing
      November 2019
      59 pages
      ISBN:9781450376983
      DOI:10.1145/3379299

      Copyright © 2019 ACM

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      Publication History

      • Published: 20 March 2020

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