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CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study

BACKGROUND: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. METHODS: A total of 164 patients confirmed COVID-19 were retrospectivel...

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Autores principales: Hu, Xiaofei, Zeng, Wenbing, Zhang, Yuhan, Zhen, Zhiming, Zheng, Yalan, Cheng, Lin, Wang, Xianqi, Luo, Haoran, Zhang, Shu, Wu, Zifeng, Sun, Zeyu, Li, Xiuli, Cao, Yang, Xu, Ming, Wang, Jian, Chen, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7656439/
https://www.ncbi.nlm.nih.gov/pubmed/33209367
http://dx.doi.org/10.21037/jtd-20-1584
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author Hu, Xiaofei
Zeng, Wenbing
Zhang, Yuhan
Zhen, Zhiming
Zheng, Yalan
Cheng, Lin
Wang, Xianqi
Luo, Haoran
Zhang, Shu
Wu, Zifeng
Sun, Zeyu
Li, Xiuli
Cao, Yang
Xu, Ming
Wang, Jian
Chen, Wei
author_facet Hu, Xiaofei
Zeng, Wenbing
Zhang, Yuhan
Zhen, Zhiming
Zheng, Yalan
Cheng, Lin
Wang, Xianqi
Luo, Haoran
Zhang, Shu
Wu, Zifeng
Sun, Zeyu
Li, Xiuli
Cao, Yang
Xu, Ming
Wang, Jian
Chen, Wei
author_sort Hu, Xiaofei
collection PubMed
description BACKGROUND: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. METHODS: A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed. RESULTS: It was observed that patients in the severe type group were older than the mild type group. Round lesions, Fan-shaped lesions, crazy-paving pattern, fibrosis, “white lung”, pleural thickening, pleural indentation, mediastinal lymphadenectasis were more common in the CT images of severe patients than in the mild ones. A higher total lung severity score and scores of each lobe were observed in the severe group, with higher scores in bilateral lower lobes of both groups. Further analysis showed that the volume and number of pneumonia lesions and consolidation lesions in overall lung were higher in the severe group, and showed a wider distribution in the lower lobes of bilateral lung in both groups. CONCLUSIONS: Chest CT of patients with severe COVID-19 pneumonia showed more consolidative and progressive lesions. With the assistance of AI, CT could evaluate the clinical severity of COVID-19 pneumonia more precisely and help the early diagnosis and surveillance of the patients.
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spelling pubmed-76564392020-11-17 CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study Hu, Xiaofei Zeng, Wenbing Zhang, Yuhan Zhen, Zhiming Zheng, Yalan Cheng, Lin Wang, Xianqi Luo, Haoran Zhang, Shu Wu, Zifeng Sun, Zeyu Li, Xiuli Cao, Yang Xu, Ming Wang, Jian Chen, Wei J Thorac Dis Original Article BACKGROUND: The study is designed to explore the chest CT features of different clinical types of coronavirus disease 2019 (COVID-19) pneumonia based on a Chinese multicenter dataset using an artificial intelligence (AI) system. METHODS: A total of 164 patients confirmed COVID-19 were retrospectively enrolled from 6 hospitals. All patients were divided into the mild type (136 cases) and the severe type (28 cases) according to their clinical manifestations. The total CT severity score and quantitative CT features were calculated by AI pneumonia detection and evaluation system with correction by radiologists. The clinical and CT imaging features of different types were analyzed. RESULTS: It was observed that patients in the severe type group were older than the mild type group. Round lesions, Fan-shaped lesions, crazy-paving pattern, fibrosis, “white lung”, pleural thickening, pleural indentation, mediastinal lymphadenectasis were more common in the CT images of severe patients than in the mild ones. A higher total lung severity score and scores of each lobe were observed in the severe group, with higher scores in bilateral lower lobes of both groups. Further analysis showed that the volume and number of pneumonia lesions and consolidation lesions in overall lung were higher in the severe group, and showed a wider distribution in the lower lobes of bilateral lung in both groups. CONCLUSIONS: Chest CT of patients with severe COVID-19 pneumonia showed more consolidative and progressive lesions. With the assistance of AI, CT could evaluate the clinical severity of COVID-19 pneumonia more precisely and help the early diagnosis and surveillance of the patients. AME Publishing Company 2020-10 /pmc/articles/PMC7656439/ /pubmed/33209367 http://dx.doi.org/10.21037/jtd-20-1584 Text en 2020 Journal of Thoracic Disease. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Hu, Xiaofei
Zeng, Wenbing
Zhang, Yuhan
Zhen, Zhiming
Zheng, Yalan
Cheng, Lin
Wang, Xianqi
Luo, Haoran
Zhang, Shu
Wu, Zifeng
Sun, Zeyu
Li, Xiuli
Cao, Yang
Xu, Ming
Wang, Jian
Chen, Wei
CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title_full CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title_fullStr CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title_full_unstemmed CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title_short CT imaging features of different clinical types of COVID-19 calculated by AI system: a Chinese multicenter study
title_sort ct imaging features of different clinical types of covid-19 calculated by ai system: a chinese multicenter study
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7656439/
https://www.ncbi.nlm.nih.gov/pubmed/33209367
http://dx.doi.org/10.21037/jtd-20-1584
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