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Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia

BACKGROUND: Model-based iterative reconstruction (MBIR) is a promising reconstruction method which could improve CT image quality with low radiation dose. The purpose of this study was to demonstrate the advantage of using MBIR for noise reduction and image quality improvement in low dose chest CT f...

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Autores principales: Sun, Jihang, Yu, Tong, Liu, Jinrong, Duan, Xiaomin, Hu, Di, liu, Yong, Peng, Yun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356402/
https://www.ncbi.nlm.nih.gov/pubmed/28302073
http://dx.doi.org/10.1186/s12880-017-0177-9
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author Sun, Jihang
Yu, Tong
Liu, Jinrong
Duan, Xiaomin
Hu, Di
liu, Yong
Peng, Yun
author_facet Sun, Jihang
Yu, Tong
Liu, Jinrong
Duan, Xiaomin
Hu, Di
liu, Yong
Peng, Yun
author_sort Sun, Jihang
collection PubMed
description BACKGROUND: Model-based iterative reconstruction (MBIR) is a promising reconstruction method which could improve CT image quality with low radiation dose. The purpose of this study was to demonstrate the advantage of using MBIR for noise reduction and image quality improvement in low dose chest CT for children with necrotizing pneumonia, over the adaptive statistical iterative reconstruction (ASIR) and conventional filtered back-projection (FBP) technique. METHODS: Twenty-six children with necrotizing pneumonia (aged 2 months to 11 years) who underwent standard of care low dose CT scans were included. Thinner-slice (0.625 mm) images were retrospectively reconstructed using MBIR, ASIR and conventional FBP techniques. Image noise and signal-to-noise ratio (SNR) for these thin-slice images were measured and statistically analyzed using ANOVA. Two radiologists independently analyzed the image quality for detecting necrotic lesions, and results were compared using a Friedman’s test. RESULTS: Radiation dose for the overall patient population was 0.59 mSv. There was a significant improvement in the high-density and low-contrast resolution of the MBIR reconstruction resulting in more detection and better identification of necrotic lesions (38 lesions in 0.625 mm MBIR images vs. 29 lesions in 0.625 mm FBP images). The subjective display scores (mean ± standard deviation) for the detection of necrotic lesions were 5.0 ± 0.0, 2.8 ± 0.4 and 2.5 ± 0.5 with MBIR, ASIR and FBP reconstruction, respectively, and the respective objective image noise was 13.9 ± 4.0HU, 24.9 ± 6.6HU and 33.8 ± 8.7HU. The image noise decreased by 58.9 and 26.3% in MBIR images as compared to FBP and ASIR images. Additionally, the SNR of MBIR images was significantly higher than FBP images and ASIR images. CONCLUSIONS: The quality of chest CT images obtained by MBIR in children with necrotizing pneumonia was significantly improved by the MBIR technique as compared to the ASIR and FBP reconstruction, to provide a more confident and accurate diagnosis for necrotizing pneumonia.
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spelling pubmed-53564022017-03-22 Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia Sun, Jihang Yu, Tong Liu, Jinrong Duan, Xiaomin Hu, Di liu, Yong Peng, Yun BMC Med Imaging Research Article BACKGROUND: Model-based iterative reconstruction (MBIR) is a promising reconstruction method which could improve CT image quality with low radiation dose. The purpose of this study was to demonstrate the advantage of using MBIR for noise reduction and image quality improvement in low dose chest CT for children with necrotizing pneumonia, over the adaptive statistical iterative reconstruction (ASIR) and conventional filtered back-projection (FBP) technique. METHODS: Twenty-six children with necrotizing pneumonia (aged 2 months to 11 years) who underwent standard of care low dose CT scans were included. Thinner-slice (0.625 mm) images were retrospectively reconstructed using MBIR, ASIR and conventional FBP techniques. Image noise and signal-to-noise ratio (SNR) for these thin-slice images were measured and statistically analyzed using ANOVA. Two radiologists independently analyzed the image quality for detecting necrotic lesions, and results were compared using a Friedman’s test. RESULTS: Radiation dose for the overall patient population was 0.59 mSv. There was a significant improvement in the high-density and low-contrast resolution of the MBIR reconstruction resulting in more detection and better identification of necrotic lesions (38 lesions in 0.625 mm MBIR images vs. 29 lesions in 0.625 mm FBP images). The subjective display scores (mean ± standard deviation) for the detection of necrotic lesions were 5.0 ± 0.0, 2.8 ± 0.4 and 2.5 ± 0.5 with MBIR, ASIR and FBP reconstruction, respectively, and the respective objective image noise was 13.9 ± 4.0HU, 24.9 ± 6.6HU and 33.8 ± 8.7HU. The image noise decreased by 58.9 and 26.3% in MBIR images as compared to FBP and ASIR images. Additionally, the SNR of MBIR images was significantly higher than FBP images and ASIR images. CONCLUSIONS: The quality of chest CT images obtained by MBIR in children with necrotizing pneumonia was significantly improved by the MBIR technique as compared to the ASIR and FBP reconstruction, to provide a more confident and accurate diagnosis for necrotizing pneumonia. BioMed Central 2017-03-16 /pmc/articles/PMC5356402/ /pubmed/28302073 http://dx.doi.org/10.1186/s12880-017-0177-9 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Sun, Jihang
Yu, Tong
Liu, Jinrong
Duan, Xiaomin
Hu, Di
liu, Yong
Peng, Yun
Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title_full Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title_fullStr Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title_full_unstemmed Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title_short Image quality improvement using model-based iterative reconstruction in low dose chest CT for children with necrotizing pneumonia
title_sort image quality improvement using model-based iterative reconstruction in low dose chest ct for children with necrotizing pneumonia
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5356402/
https://www.ncbi.nlm.nih.gov/pubmed/28302073
http://dx.doi.org/10.1186/s12880-017-0177-9
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