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CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)

OBJECTIVES: To explore the relationship between the imaging manifestations and clinical classification of COVID-19. METHODS: We conducted a retrospective single-center study on patients with COVID-19 from Jan. 18, 2020 to Feb. 7, 2020 in Zhuhai, China. Patients were divided into 3 types based on Chi...

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Autores principales: Li, Kunwei, Fang, Yijie, Li, Wenjuan, Pan, Cunxue, Qin, Peixin, Zhong, Yinghua, Liu, Xueguo, Huang, Mingqian, Liao, Yuting, Li, Shaolin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095246/
https://www.ncbi.nlm.nih.gov/pubmed/32215691
http://dx.doi.org/10.1007/s00330-020-06817-6
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author Li, Kunwei
Fang, Yijie
Li, Wenjuan
Pan, Cunxue
Qin, Peixin
Zhong, Yinghua
Liu, Xueguo
Huang, Mingqian
Liao, Yuting
Li, Shaolin
author_facet Li, Kunwei
Fang, Yijie
Li, Wenjuan
Pan, Cunxue
Qin, Peixin
Zhong, Yinghua
Liu, Xueguo
Huang, Mingqian
Liao, Yuting
Li, Shaolin
author_sort Li, Kunwei
collection PubMed
description OBJECTIVES: To explore the relationship between the imaging manifestations and clinical classification of COVID-19. METHODS: We conducted a retrospective single-center study on patients with COVID-19 from Jan. 18, 2020 to Feb. 7, 2020 in Zhuhai, China. Patients were divided into 3 types based on Chinese guideline: mild (patients with minimal symptoms and negative CT findings), common, and severe-critical (patients with positive CT findings and different extent of clinical manifestations). CT visual quantitative evaluation was based on summing up the acute lung inflammatory lesions involving each lobe, which was scored as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%), respectively. The total severity score (TSS) was reached by summing the five lobe scores. The consistency of two observers was evaluated. The TSS was compared with the clinical classification. ROC was used to test the diagnosis ability of TSS for severe-critical type. RESULTS: This study included 78 patients, 38 males and 40 females. There were 24 mild (30.8%), 46 common (59.0%), and 8 severe-critical (10.2%) cases, respectively. The median TSS of severe-critical-type group was significantly higher than common type (p < 0.001). The ICC value of the two observers was 0.976 (95% CI 0.962–0.985). ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918. The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. CONCLUSIONS: The proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool. The CT visual quantitative analysis has high consistency and can reflect the clinical classification of COVID-19. KEY POINTS: • CT visual quantitative evaluation has high consistency (ICC value of 0.976) among the observers. The median TSS of severe-critical type group was significantly higher than common type (p < 0.001). • ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918 (95% CI 0.843–0.994). The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. • The proportion of confirmed COVID-19 patients with normal chest CT was relatively high (30.8%); CT was not a suitable screening modality
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spelling pubmed-70952462020-03-26 CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19) Li, Kunwei Fang, Yijie Li, Wenjuan Pan, Cunxue Qin, Peixin Zhong, Yinghua Liu, Xueguo Huang, Mingqian Liao, Yuting Li, Shaolin Eur Radiol Chest OBJECTIVES: To explore the relationship between the imaging manifestations and clinical classification of COVID-19. METHODS: We conducted a retrospective single-center study on patients with COVID-19 from Jan. 18, 2020 to Feb. 7, 2020 in Zhuhai, China. Patients were divided into 3 types based on Chinese guideline: mild (patients with minimal symptoms and negative CT findings), common, and severe-critical (patients with positive CT findings and different extent of clinical manifestations). CT visual quantitative evaluation was based on summing up the acute lung inflammatory lesions involving each lobe, which was scored as 0 (0%), 1 (1–25%), 2 (26–50%), 3 (51–75%), or 4 (76–100%), respectively. The total severity score (TSS) was reached by summing the five lobe scores. The consistency of two observers was evaluated. The TSS was compared with the clinical classification. ROC was used to test the diagnosis ability of TSS for severe-critical type. RESULTS: This study included 78 patients, 38 males and 40 females. There were 24 mild (30.8%), 46 common (59.0%), and 8 severe-critical (10.2%) cases, respectively. The median TSS of severe-critical-type group was significantly higher than common type (p < 0.001). The ICC value of the two observers was 0.976 (95% CI 0.962–0.985). ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918. The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. CONCLUSIONS: The proportion of clinical mild-type patients with COVID-19 was relatively high; CT was not suitable for independent screening tool. The CT visual quantitative analysis has high consistency and can reflect the clinical classification of COVID-19. KEY POINTS: • CT visual quantitative evaluation has high consistency (ICC value of 0.976) among the observers. The median TSS of severe-critical type group was significantly higher than common type (p < 0.001). • ROC analysis showed the area under the curve (AUC) of TSS for diagnosing severe-critical type was 0.918 (95% CI 0.843–0.994). The TSS cutoff of 7.5 had 82.6% sensitivity and 100% specificity. • The proportion of confirmed COVID-19 patients with normal chest CT was relatively high (30.8%); CT was not a suitable screening modality Springer Berlin Heidelberg 2020-03-25 2020 /pmc/articles/PMC7095246/ /pubmed/32215691 http://dx.doi.org/10.1007/s00330-020-06817-6 Text en © European Society of Radiology 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Chest
Li, Kunwei
Fang, Yijie
Li, Wenjuan
Pan, Cunxue
Qin, Peixin
Zhong, Yinghua
Liu, Xueguo
Huang, Mingqian
Liao, Yuting
Li, Shaolin
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title_full CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title_fullStr CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title_full_unstemmed CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title_short CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19)
title_sort ct image visual quantitative evaluation and clinical classification of coronavirus disease (covid-19)
topic Chest
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7095246/
https://www.ncbi.nlm.nih.gov/pubmed/32215691
http://dx.doi.org/10.1007/s00330-020-06817-6
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