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Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital
The clinical anteroposterior (AP) chest images taken with a mobile radiography system were analyzed in this study to utilize the clinical exposure index (EI) as a patient dose-monitoring tool. The digital imaging and communications in medicine header of 6048 data points exposed under the 90 kVp and...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582475/ https://www.ncbi.nlm.nih.gov/pubmed/37860502 http://dx.doi.org/10.1016/j.heliyon.2023.e20760 |
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author | Park, Hyemin Kim, Jungsu Kang, Eun-Ju Kim, Yeji Jo, Hyejin Heo, Jin-Haeng Yang, Wonseok Yoon, Yongsu |
author_facet | Park, Hyemin Kim, Jungsu Kang, Eun-Ju Kim, Yeji Jo, Hyejin Heo, Jin-Haeng Yang, Wonseok Yoon, Yongsu |
author_sort | Park, Hyemin |
collection | PubMed |
description | The clinical anteroposterior (AP) chest images taken with a mobile radiography system were analyzed in this study to utilize the clinical exposure index (EI) as a patient dose-monitoring tool. The digital imaging and communications in medicine header of 6048 data points exposed under the 90 kVp and 2.5 mAs were extracted using Python for identifying the distribution of clinical EI. Even under the same exposure conditions, the clinical EI distribution was 137.82–4924.38. To determine the cause, the effect of a patient's body shape on EI was confirmed using actual clinical chest AP image data binarized into 0 and 255-pixel values using Python. As a result, the relationship between the direct X-ray area of the chest AP image, the higher the clinical EI, the larger the rate of the direct X-ray area. A conversion equation was also derived to infer entrance surface dose through clinical EI based on the patient thickness. This confirmed the possibility of directly monitoring patient dose through EI without a dosimeter in real-time. Therefore, to use the clinical EI of the mobile radiography system as a patient dose-monitoring tool, the derivation method of clinical EI considers several factors, such as the relationship between patient factors. |
format | Online Article Text |
id | pubmed-10582475 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-105824752023-10-19 Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital Park, Hyemin Kim, Jungsu Kang, Eun-Ju Kim, Yeji Jo, Hyejin Heo, Jin-Haeng Yang, Wonseok Yoon, Yongsu Heliyon Research Article The clinical anteroposterior (AP) chest images taken with a mobile radiography system were analyzed in this study to utilize the clinical exposure index (EI) as a patient dose-monitoring tool. The digital imaging and communications in medicine header of 6048 data points exposed under the 90 kVp and 2.5 mAs were extracted using Python for identifying the distribution of clinical EI. Even under the same exposure conditions, the clinical EI distribution was 137.82–4924.38. To determine the cause, the effect of a patient's body shape on EI was confirmed using actual clinical chest AP image data binarized into 0 and 255-pixel values using Python. As a result, the relationship between the direct X-ray area of the chest AP image, the higher the clinical EI, the larger the rate of the direct X-ray area. A conversion equation was also derived to infer entrance surface dose through clinical EI based on the patient thickness. This confirmed the possibility of directly monitoring patient dose through EI without a dosimeter in real-time. Therefore, to use the clinical EI of the mobile radiography system as a patient dose-monitoring tool, the derivation method of clinical EI considers several factors, such as the relationship between patient factors. Elsevier 2023-10-07 /pmc/articles/PMC10582475/ /pubmed/37860502 http://dx.doi.org/10.1016/j.heliyon.2023.e20760 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research Article Park, Hyemin Kim, Jungsu Kang, Eun-Ju Kim, Yeji Jo, Hyejin Heo, Jin-Haeng Yang, Wonseok Yoon, Yongsu Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title | Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title_full | Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title_fullStr | Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title_full_unstemmed | Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title_short | Feasibility of new patient dose management tool in digital radiography: Using clinical exposure index data of mobile chest radiography in a large university hospital |
title_sort | feasibility of new patient dose management tool in digital radiography: using clinical exposure index data of mobile chest radiography in a large university hospital |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582475/ https://www.ncbi.nlm.nih.gov/pubmed/37860502 http://dx.doi.org/10.1016/j.heliyon.2023.e20760 |
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