Literature DB >> 24713541

Ultra-low-dose CT of the lung: effect of iterative reconstruction techniques on image quality.

Masahiro Yanagawa1, Tomoko Gyobu2, Ann N Leung3, Misa Kawai2, Yutaka Kawata4, Hiromitsu Sumikawa2, Osamu Honda2, Noriyuki Tomiyama2.   

Abstract

RATIONALE AND
OBJECTIVES: To compare quality of ultra-low-dose thin-section computed tomography (CT) images of the lung reconstructed using model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASIR) to filtered back projection (FBP) and to determine the minimum tube current-time product on MBIR images by comparing to standard-dose FBP images.
MATERIALS AND METHODS: Ten cadaveric lungs were scanned using 120 kVp and four different tube current-time products (8, 16, 32, and 80 mAs). Thin-section images were reconstructed using MBIR, three ASIR blends (30%, 60%, and 90%), and FBP. Using the 8-mAs data, side-to-side comparison of the four iterative reconstruction image sets to FBP was performed by two independent observers who evaluated normal and abnormal findings, subjective image noise, streak artifact, and overall image quality. Image noise was also measured quantitatively. Subsequently, 8-, 16-, and 32-mAs MBIR images were compared to standard-dose FBP images. Comparisons of image sets were analyzed using the Wilcoxon signed rank test with Bonferroni correction.
RESULTS: At 8 mAs, MBIR images were significantly better (P < .005) than other reconstruction techniques except in evaluation of interlobular septal thickening. Each set of low-dose MBIR images had significantly lower (P < .001) subjective and objective noise and streak artifacts than standard-dose FBP images. Conspicuity and visibility of normal and abnormal findings were not significantly different between 16-mAs MBIR and 80-mAs FBP images except in identification of intralobular reticular opacities.
CONCLUSIONS: MBIR imaging shows higher overall quality with lower noise and streak artifacts than ASIR or FBP imaging, resulting in nearly 80% dose reduction without any degradations of overall image quality.
Copyright © 2014 AUR. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Radiation dose reduction; adaptive statistical iterative reconstruction; filtered back projection; image quality; model-based iterative reconstruction

Mesh:

Year:  2014        PMID: 24713541     DOI: 10.1016/j.acra.2014.01.023

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


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