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Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone
PURPOSE: To prospectively determine the diagnostic performance of low-dose CT (LDCT) with adaptive statistical iterative reconstruction (ASIR) technique for the detection of urinary stone disease. RESULTS: The average DLP and ED was 408.16 ± 119.04 mGy and 6.12 ± 1.79 mSv in CDCT, and 138.19 ± 76.87...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5929449/ https://www.ncbi.nlm.nih.gov/pubmed/29732006 http://dx.doi.org/10.18632/oncotarget.25047 |
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author | Li, Xiaohu Shu, Hongmin Zhang, Yifei Li, Xiaoshu Song, Jian Du, Junhua Qian, Yinfeng Liu, Bin Yu, Yongqiang |
author_facet | Li, Xiaohu Shu, Hongmin Zhang, Yifei Li, Xiaoshu Song, Jian Du, Junhua Qian, Yinfeng Liu, Bin Yu, Yongqiang |
author_sort | Li, Xiaohu |
collection | PubMed |
description | PURPOSE: To prospectively determine the diagnostic performance of low-dose CT (LDCT) with adaptive statistical iterative reconstruction (ASIR) technique for the detection of urinary stone disease. RESULTS: The average DLP and ED was 408.16 ± 119.04 mGy and 6.12 ± 1.79 mSv in CDCT, and 138.19 ± 76.87 mGy and 2.07 ± 1.15 mSv in LDCT, respectively. The dose reduction rate of LDCT was nearly 66.1% for both DLP and ED (P < 0.05). LDCT–80% ASIR images showed great image quality (mean score = 4.09), which was similar to CDCT-FBP images (mean score = 4.17) (P > 0.05), but higher than LDCT-FBP images (mean score = 2.77) (P < 0.05). MATERIALS AND METHODS: 70 consetutive patients with clinically suspected urolithiasis underwent non-enhanced CT. Followed by both conventional-dose CT (CDCT) and low-dose CT (LDCT) scans. Automatic tube current modulation (ATCM) scanning was used, with a noise index setting of 13 in CDCT and 25 in LDCT. Reconstructions were performed with filtered back projection (FBP) and different settings of adaptive statistical iterative reconstruction [ASIR(40%, 60%, 80%)]. Urinary calculi (size, location, number), image quality (scale 1–5), image noise (scale 1–3) and diagnostic confidence levels (scale 1–3) were evaluated and measured by two radiologists independently. Radiation dose was recorded by calculating dose length product (DLP) and effective dose (ED). Statistical analyses included Mann-Whitney U test and Paired t tests. CONCLUSIONS: LDCT with ASIR can reduce the radiation dose while maintain relatively high image quality in the diagnosis of urinary stone diseases. |
format | Online Article Text |
id | pubmed-5929449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-59294492018-05-04 Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone Li, Xiaohu Shu, Hongmin Zhang, Yifei Li, Xiaoshu Song, Jian Du, Junhua Qian, Yinfeng Liu, Bin Yu, Yongqiang Oncotarget Clinical Research Paper PURPOSE: To prospectively determine the diagnostic performance of low-dose CT (LDCT) with adaptive statistical iterative reconstruction (ASIR) technique for the detection of urinary stone disease. RESULTS: The average DLP and ED was 408.16 ± 119.04 mGy and 6.12 ± 1.79 mSv in CDCT, and 138.19 ± 76.87 mGy and 2.07 ± 1.15 mSv in LDCT, respectively. The dose reduction rate of LDCT was nearly 66.1% for both DLP and ED (P < 0.05). LDCT–80% ASIR images showed great image quality (mean score = 4.09), which was similar to CDCT-FBP images (mean score = 4.17) (P > 0.05), but higher than LDCT-FBP images (mean score = 2.77) (P < 0.05). MATERIALS AND METHODS: 70 consetutive patients with clinically suspected urolithiasis underwent non-enhanced CT. Followed by both conventional-dose CT (CDCT) and low-dose CT (LDCT) scans. Automatic tube current modulation (ATCM) scanning was used, with a noise index setting of 13 in CDCT and 25 in LDCT. Reconstructions were performed with filtered back projection (FBP) and different settings of adaptive statistical iterative reconstruction [ASIR(40%, 60%, 80%)]. Urinary calculi (size, location, number), image quality (scale 1–5), image noise (scale 1–3) and diagnostic confidence levels (scale 1–3) were evaluated and measured by two radiologists independently. Radiation dose was recorded by calculating dose length product (DLP) and effective dose (ED). Statistical analyses included Mann-Whitney U test and Paired t tests. CONCLUSIONS: LDCT with ASIR can reduce the radiation dose while maintain relatively high image quality in the diagnosis of urinary stone diseases. Impact Journals LLC 2018-04-13 /pmc/articles/PMC5929449/ /pubmed/29732006 http://dx.doi.org/10.18632/oncotarget.25047 Text en Copyright: © 2018 Li et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Clinical Research Paper Li, Xiaohu Shu, Hongmin Zhang, Yifei Li, Xiaoshu Song, Jian Du, Junhua Qian, Yinfeng Liu, Bin Yu, Yongqiang Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title | Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title_full | Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title_fullStr | Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title_full_unstemmed | Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title_short | Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone |
title_sort | low-dose ct with adaptive statistical iterative reconstruction for evaluation of urinary stone |
topic | Clinical Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5929449/ https://www.ncbi.nlm.nih.gov/pubmed/29732006 http://dx.doi.org/10.18632/oncotarget.25047 |
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