COMPARATIVE STUDY
JOURNAL ARTICLE

Dose reduction in chest CT: comparison of the adaptive iterative dose reduction 3D, adaptive iterative dose reduction, and filtered back projection reconstruction techniques

Yoshitake Yamada, Masahiro Jinzaki, Takahiro Hosokawa, Yutaka Tanami, Hiroaki Sugiura, Takayuki Abe, Sachio Kuribayashi
European Journal of Radiology 2012, 81 (12): 4185-95
22883532

OBJECTIVES: To assess the effectiveness of adaptive iterative dose reduction (AIDR) and AIDR 3D in improving the image quality in low-dose chest CT (LDCT).

MATERIALS AND METHODS: Fifty patients underwent standard-dose chest CT (SDCT) and LDCT simultaneously, performed under automatic exposure control with noise index of 19 and 38 (for a 2-mm slice thickness), respectively. The SDCT images were reconstructed with filtered back projection (SDCT-FBP images), and the LDCT images with FBP, AIDR and AIDR 3D (LDCT-FBP, LDCT-AIDR and LDCT-AIDR 3D images, respectively). On all the 200 lung and 200 mediastinal image series, objective image noise and signal-to-noise ratio (SNR) were measured in several regions, and two blinded radiologists independently assessed the subjective image quality. Wilcoxon's signed rank sum test with Bonferroni's correction was used for the statistical analyses.

RESULTS: The mean dose reduction in LDCT was 64.2% as compared with the dose in SDCT. LDCT-AIDR 3D images showed significantly reduced objective noise and significantly increased SNR in all regions as compared to the SDCT-FBP, LDCT-FBP and LDCT-AIDR images (all, P ≤ 0.003). In all assessments of the image quality, LDCT-AIDR 3D images were superior to LDCT-AIDR and LDCT-FBP images. The overall diagnostic acceptability of both the lung and mediastinal LDCT-AIDR 3D images was comparable to that of the lung and mediastinal SDCT-FBP images.

CONCLUSIONS: AIDR 3D is superior to AIDR. Intra-individual comparisons between SDCT and LDCT suggest that AIDR 3D allows a 64.2% reduction of the radiation dose as compared to SDCT, by substantially reducing the objective image noise and increasing the SNR, while maintaining the overall diagnostic acceptability.

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