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头部CT:采用针对儿童的低辐射剂量方案,利用自适应统计迭代重建技术(ASIR-V)提高图像质量。

Head CT: Image quality improvement with ASIR-V using a reduced radiation dose protocol for children.

作者信息

Kim Hyun Gi, Lee Ho-Joon, Lee Seung-Koo, Kim Hyun Ji, Kim Myung-Joon

机构信息

Department of Radiology, Ajou University School of Medicine, Ajou University Medical Center, 164 World Cup-ro, Yeongtong-gu, Suwon, Korea, 443-380.

Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, Korea, 120-752.

出版信息

Eur Radiol. 2017 Sep;27(9):3609-3617. doi: 10.1007/s00330-017-4733-z. Epub 2017 Jan 23.

DOI:10.1007/s00330-017-4733-z
PMID:28116512
Abstract

OBJECTIVE

To investigate the quality of images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V), using pediatric head CT protocols.

METHODS

A phantom was scanned at decreasing 20% mA intervals using our standard pediatric head CT protocols. Each study was then reconstructed at 10% ASIR-V intervals. After the phantom study, we reduced mA by 10% in the protocol for <3-year-old patients and applied 30% ASIR-V and by 30% in the protocol for 3- to 15-year-old patients and applied 40% ASIR-V.

RESULTS

Increasing the percentage of ASIR-V resulted in lower noise and higher contrast-to-noise ratio (CNR) and preserved spatial resolution in the phantom study. Compared to a conventional-protocol, reduced-dose protocol with ASIR-V achieved 12.8% to 34.0% of dose reduction and showed images of lower noise (9.22 vs. 10.73, P = 0.043) and higher CNR in different levels (centrum semiovale, 2.14 vs. 1.52, P = 0.003; basal ganglia, 1.46 vs. 1.07, P = 0.001; and cerebellum, 2.18 vs. 1.33, P < 0.001). Qualitative analysis showed higher gray-white matter differentiation and sharpness and preserved overall diagnostic quality in the images with ASIR-V.

CONCLUSIONS

Use of ASIR-V allowed a 12.8% to 34.0% dose reduction in each age group with potential to improve image quality.

KEY POINTS

• It is possible to reduce radiation dose and improve image quality with ASIR-V. • We improved noise and CNR and decreased radiation dose. • Sharpness improved with ASIR-V. • Total radiation dose was decreased by 12.8% to 34.0%.

摘要

目的

采用儿科头部CT扫描方案,研究自适应统计迭代重建V(ASIR-V)技术重建图像的质量。

方法

使用我们的标准儿科头部CT扫描方案,以20%毫安(mA)的间隔递减对模型进行扫描。然后,每次扫描的图像以10%的ASIR-V间隔进行重建。在模型扫描研究之后,我们将<3岁患者扫描方案中的毫安数降低10%并应用30%的ASIR-V,将3至15岁患者扫描方案中的毫安数降低30%并应用40%的ASIR-V。

结果

在模型扫描研究中,增加ASIR-V的百分比会降低噪声、提高对比噪声比(CNR)并保持空间分辨率。与传统扫描方案相比,采用ASIR-V的低剂量扫描方案实现了12.8%至34.0%的剂量降低,并且在不同层面(半卵圆中心,2.14对1.52,P = 0.003;基底节,1.46对1.07,P = 0.001;小脑,2.18对1.33,P < 0.001)显示出噪声更低(9.22对10.73,P = 0.043)和CNR更高的图像。定性分析表明,使用ASIR-V重建的图像具有更高的灰白质对比度和清晰度,并且整体诊断质量得以保持。

结论

使用ASIR-V可使每个年龄组的辐射剂量降低12.8%至34.0%,并有可能提高图像质量。

要点

• 使用ASIR-V可以降低辐射剂量并提高图像质量。• 我们改善了噪声和CNR并降低了辐射剂量。• 使用ASIR-V清晰度得到改善。• 总辐射剂量降低了12.8%至34.0%。

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2
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3
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Quant Imaging Med Surg. 2023 Mar 1;13(3):1814-1824. doi: 10.21037/qims-22-353. Epub 2022 Nov 30.
4
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5
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6
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4
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5
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