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Journal of Engineering and Applied Sciences

ISSN: Online 1818-7803
ISSN: Print 1816-949x
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Imaging Radiation Dose Reduction with Adaptive Statistical Iterative Reconstruction in Brain CT

Yoon-Jeong Kim, Dan-Bi Lee, Ino Yu, Su-Chul Han, Hong-Ryang Jung and Cheong-Hwan Lim
Page: 7431-7434 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

We compared and analyzed patient doses depending on the application of FBP (Filtered Back Projection) and ASIR (Adaptive Statistical Iterative Reconstruction Algorithm). A64-MDCT Optima ™ CT 660 system was used for imaging. For quantitative analysis, images containing both sides of orbit and basal ganglia were obtained. After setting a 40~45 mm2 area as Region of Interest (ROI), the average CT number was measured. A Statistical Program, SPSS 22.0 was used for the calculations and ANOVA, Kruskal-Wallis and paired t-tests were performed after the normality and equivalence tests. For quantitative analysis, a comparison of SNR of each scan type was carried out. From the Kruskal-Wallis test, the SNR of axial scan was 0.13±0.67 and the SNR of Helical scan was 0.12±0.64. There was a significant difference for the axial scan values (χ2= 12.54, p<0.05) but there was no corresponding significant difference for those from the Helical scan (χ2 = 0.49, p>0.05). When ASIR was applied in the axial scan, the value of CTDIvol decreased by 21.46 mGy (47.8%) at maximum. The value of DLP decreased by 343.42 mGy•cm (47.8%) at maximum. When ASIR was applied in the Helical scan, the value of CTDIvol decreased by 18.52 mGy (49.9%) at maximum and the value of vol DLP decreased by 328.92 mGy•cm (49.9%) at maximum. This study could confirm a dose reduction through applying FBP and ASIR algorithm for each scan type in brain CT imaging.


How to cite this article:

Yoon-Jeong Kim, Dan-Bi Lee, Ino Yu, Su-Chul Han, Hong-Ryang Jung and Cheong-Hwan Lim. Imaging Radiation Dose Reduction with Adaptive Statistical Iterative Reconstruction in Brain CT.
DOI: https://doi.org/10.36478/jeasci.2017.7431.7434
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.7431.7434