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Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation
PURPOSE: To study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on opacity visibility on chest radiographs. MATERIALS AND METHODS: This retrospective study included 20 pairs of CT scans and same-day chest radiographs...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Radiological Society of North America
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233433/ https://www.ncbi.nlm.nih.gov/pubmed/33778565 http://dx.doi.org/10.1148/ryct.2020200107 |
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author | Choi, Hyewon Qi, Xiaolong Yoon, Soon Ho Park, Sang Joon Lee, Kyung Hee Kim, Jin Yong Lee, Young Kyung Ko, Hongseok Kim, Ki Hwan Park, Chang Min Kim, Yun-Hyeon Lei, Junqiang Hong, Jung Hee Kim, Hyungjin Hwang, Eui Jin Yoo, Seung Jin Nam, Ju Gang Lee, Chang Hyun Goo, Jin Mo |
author_facet | Choi, Hyewon Qi, Xiaolong Yoon, Soon Ho Park, Sang Joon Lee, Kyung Hee Kim, Jin Yong Lee, Young Kyung Ko, Hongseok Kim, Ki Hwan Park, Chang Min Kim, Yun-Hyeon Lei, Junqiang Hong, Jung Hee Kim, Hyungjin Hwang, Eui Jin Yoo, Seung Jin Nam, Ju Gang Lee, Chang Hyun Goo, Jin Mo |
author_sort | Choi, Hyewon |
collection | PubMed |
description | PURPOSE: To study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on opacity visibility on chest radiographs. MATERIALS AND METHODS: This retrospective study included 20 pairs of CT scans and same-day chest radiographs from 17 patients with COVID-19, along with 20 chest radiographs of controls. All pulmonary opacities were semiautomatically segmented on CT images, producing an anteroposterior projection image to match the corresponding frontal chest radiograph. The quantitative CT lung opacification mass (QCT(mass)) was defined as (opacity attenuation value + 1000 HU)/1000 × 1.065 (g/mL) × combined volume (cm(3)) of the individual opacities. Eight thoracic radiologists reviewed the 40 radiographs, and a receiver operating characteristic curve analysis was performed for the detection of lung opacities. Logistic regression analysis was performed to identify factors affecting opacity visibility on chest radiographs. RESULTS: The mean QCT(mass) per patient was 72.4 g ± 120.8 (range, 0.7–420.7 g), and opacities occupied 3.2% ± 5.8 (range, 0.1%–19.8%) and 13.9% ± 18.0 (range, 0.5%–57.8%) of the lung area on the CT images and projected images, respectively. The radiographs had a median sensitivity of 25% and specificity of 90% among radiologists. Nineteen of 186 opacities were visible on chest radiographs, and a median area of 55.8% of the projected images was identifiable on radiographs. Logistic regression analysis showed that QCT(mass) (P < .001) and combined opacity volume (P < .001) significantly affected opacity visibility on radiographs. CONCLUSION: QCT(mass) varied among patients with COVID-19. Chest radiographs had high specificity for detecting lung opacities in COVID-19 but a low sensitivity. QCT(mass) and combined opacity volume were significant determinants of opacity visibility on radiographs. Earlier incorrect version appeared online. This article was corrected on April 6, 2020 and December 14, 2020. Supplemental material is available for this article. © RSNA, 2020 |
format | Online Article Text |
id | pubmed-7233433 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Radiological Society of North America |
record_format | MEDLINE/PubMed |
spelling | pubmed-72334332020-06-02 Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation Choi, Hyewon Qi, Xiaolong Yoon, Soon Ho Park, Sang Joon Lee, Kyung Hee Kim, Jin Yong Lee, Young Kyung Ko, Hongseok Kim, Ki Hwan Park, Chang Min Kim, Yun-Hyeon Lei, Junqiang Hong, Jung Hee Kim, Hyungjin Hwang, Eui Jin Yoo, Seung Jin Nam, Ju Gang Lee, Chang Hyun Goo, Jin Mo Radiol Cardiothorac Imaging Original Research PURPOSE: To study the extent of pulmonary involvement in coronavirus 19 (COVID-19) with quantitative CT and to assess the impact of disease burden on opacity visibility on chest radiographs. MATERIALS AND METHODS: This retrospective study included 20 pairs of CT scans and same-day chest radiographs from 17 patients with COVID-19, along with 20 chest radiographs of controls. All pulmonary opacities were semiautomatically segmented on CT images, producing an anteroposterior projection image to match the corresponding frontal chest radiograph. The quantitative CT lung opacification mass (QCT(mass)) was defined as (opacity attenuation value + 1000 HU)/1000 × 1.065 (g/mL) × combined volume (cm(3)) of the individual opacities. Eight thoracic radiologists reviewed the 40 radiographs, and a receiver operating characteristic curve analysis was performed for the detection of lung opacities. Logistic regression analysis was performed to identify factors affecting opacity visibility on chest radiographs. RESULTS: The mean QCT(mass) per patient was 72.4 g ± 120.8 (range, 0.7–420.7 g), and opacities occupied 3.2% ± 5.8 (range, 0.1%–19.8%) and 13.9% ± 18.0 (range, 0.5%–57.8%) of the lung area on the CT images and projected images, respectively. The radiographs had a median sensitivity of 25% and specificity of 90% among radiologists. Nineteen of 186 opacities were visible on chest radiographs, and a median area of 55.8% of the projected images was identifiable on radiographs. Logistic regression analysis showed that QCT(mass) (P < .001) and combined opacity volume (P < .001) significantly affected opacity visibility on radiographs. CONCLUSION: QCT(mass) varied among patients with COVID-19. Chest radiographs had high specificity for detecting lung opacities in COVID-19 but a low sensitivity. QCT(mass) and combined opacity volume were significant determinants of opacity visibility on radiographs. Earlier incorrect version appeared online. This article was corrected on April 6, 2020 and December 14, 2020. Supplemental material is available for this article. © RSNA, 2020 Radiological Society of North America 2020-03-30 /pmc/articles/PMC7233433/ /pubmed/33778565 http://dx.doi.org/10.1148/ryct.2020200107 Text en 2020 by the Radiological Society of North America, Inc. |
spellingShingle | Original Research Choi, Hyewon Qi, Xiaolong Yoon, Soon Ho Park, Sang Joon Lee, Kyung Hee Kim, Jin Yong Lee, Young Kyung Ko, Hongseok Kim, Ki Hwan Park, Chang Min Kim, Yun-Hyeon Lei, Junqiang Hong, Jung Hee Kim, Hyungjin Hwang, Eui Jin Yoo, Seung Jin Nam, Ju Gang Lee, Chang Hyun Goo, Jin Mo Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title | Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title_full | Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title_fullStr | Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title_full_unstemmed | Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title_short | Extension of Coronavirus Disease 2019 on Chest CT and Implications for Chest Radiographic Interpretation |
title_sort | extension of coronavirus disease 2019 on chest ct and implications for chest radiographic interpretation |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7233433/ https://www.ncbi.nlm.nih.gov/pubmed/33778565 http://dx.doi.org/10.1148/ryct.2020200107 |
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