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双能减影放射摄影在 COVID-19 肺炎成像中的潜在应用。

The potential application of dual-energy subtraction radiography for COVID-19 pneumonia imaging.

机构信息

KULeuven, Department of Oncology, Laboratory of Experimental Radiotherapy, Leuven, Belgium.

出版信息

Br J Radiol. 2021 Apr 1;94(1120):20201384. doi: 10.1259/bjr.20201384. Epub 2021 Mar 18.

DOI:10.1259/bjr.20201384
PMID:33733827
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8010552/
Abstract

X-ray imaging plays a crucial role in the confirmation of COVID-19 pneumonia. Chest X-ray radiography and CT are two major imaging techniques that are currently adopted in the diagnosis of COVID-19 pneumonia. However, dual-energy subtraction radiography is hardly discussed as potential COVID-19 imaging application. More advanced X-ray radiography equipment often supports dual-energy subtraction X-ray radiography. Dual-energy subtraction radiography enables the calculation of pseudo-radiographs, in which bones are removed and only soft-tissues are highlighted. In this commentary, the author would like to draw the attention to the potential use of dual-energy subtraction X-ray radiography ( soft-tissue pseudo-radiography) for the assessment and the longitudinal follow-up of COVID-19 pneumonia.

摘要

X 射线成像在 COVID-19 肺炎的确诊中起着至关重要的作用。胸部 X 射线摄影和 CT 是目前用于 COVID-19 肺炎诊断的两种主要成像技术。然而,双能减影射线摄影作为潜在的 COVID-19 成像应用几乎没有被讨论过。更先进的 X 射线摄影设备通常支持双能减影 X 射线摄影。双能减影射线摄影可以计算出伪射线照片,其中骨骼被去除,只突出软组织。在这篇评论中,作者希望引起人们对双能减影 X 射线摄影(软组织伪射线摄影)在 COVID-19 肺炎评估和纵向随访中的潜在用途的关注。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27c3/8010552/7152c1643ee9/bjr.20201384.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27c3/8010552/7152c1643ee9/bjr.20201384.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/27c3/8010552/7152c1643ee9/bjr.20201384.g001.jpg

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本文引用的文献

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Variations in CT Utilization, Protocols, and Radiation Doses in COVID-19 Pneumonia: Results from 28 Countries in the IAEA Study.COVID-19 肺炎 CT 应用、方案和辐射剂量的变化:来自国际原子能机构研究的 28 个国家的结果。
Radiology. 2021 Mar;298(3):E141-E151. doi: 10.1148/radiol.2020203453. Epub 2020 Nov 10.
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用于COVID-19分类的人工智能辅助胸部X光多策略图像增强
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