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Imaging Features in COVID-19 Patients: Analysis of Data from Patients in Non-Pandemic Areas

20 Pages Posted: 10 Mar 2020

See all articles by Shengkun Peng

Shengkun Peng

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

Lingai Pan

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

Shaojin Zhang

Pidu District People’s Hospital - Department of Radiology

Yalong Liu

Wenjiang District People’s Hospital - Department of Radiology

Hua Zhang

Pidu District People’s Hospital - Department of Critical Care Medicine

Liming Tan

Wenjiang District People’s Hospital - Department of Critical Care Medicine

Yang Guo

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

Xiaobo Huang

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

Jie Zeng

University of Electronic Science and Technology of China (UESTC) - Department of Cardiology

Hong Pu

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

More...

Abstract

Purpose: To describe the imaging characteristics in COVID-19 Patients from non-pandemic regions to improve understanding of the disease

Methods: We reviewed chest CT scans of 30 COVID-19 patients from three hospitals in Sichuan province, China.

Results: Typical CT manifestations include the involvement of multiple lobes, mostly in the peripheral zone of the lungs, and subpleural distribution. GGO, crazy paving or mixed GGO and consolidation is the most common signs. Few patients can present small amount of pleural effusion. It is worth noting that none of the lung cavities, tree buds, and lymphadenopathy appeared. The follow-up imaging findings of some patients showed progress when the initial CT score reached 7.

Conclusion: The CT scan still play an important role in screening the COVID-19, most of the images present positive signs, mainly subpleural, multiple GGO. CT might can predict the severity or whether the patient will progress to severe illness. A small number of patients may be missed if they are based on CT findings alone, which should be closely combined with the patient's epidemiological history and nucleic acid test.

Funding Statement: None.

Declaration of Interests: The authors declare that they have no conflicts of interest in relation to this study.

Ethics Approval Statement: The study was approved by the medical ethics committees of Sichuan Provincial People’s Hospital, and informed consent from the patient or legal representative was obtained.

Keywords: COVID-19, computed tomography, GGO

Suggested Citation

Peng, Shengkun and Pan, Lingai and Zhang, Shaojin and Liu, Yalong and Zhang, Hua and Tan, Liming and Guo, Yang and Huang, Xiaobo and Zeng, Jie and Pu, Hong, Imaging Features in COVID-19 Patients: Analysis of Data from Patients in Non-Pandemic Areas (3/1/2020). Available at SSRN: https://ssrn.com/abstract=3548786 or http://dx.doi.org/10.2139/ssrn.3548786

Shengkun Peng

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

No.4, Section 2, North Jianshe Road
Chengdu, Chengdu 610031
China

Lingai Pan

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

No.4, Section 2, North Jianshe Road
Chengdu, Chengdu 610031
China

Shaojin Zhang

Pidu District People’s Hospital - Department of Radiology

China

Yalong Liu

Wenjiang District People’s Hospital - Department of Radiology

China

Hua Zhang

Pidu District People’s Hospital - Department of Critical Care Medicine

China

Liming Tan

Wenjiang District People’s Hospital - Department of Critical Care Medicine

China

Yang Guo

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

No.4, Section 2, North Jianshe Road
Chengdu, Chengdu 610031
China

Xiaobo Huang

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital

No.4, Section 2, North Jianshe Road
Chengdu, Chengdu 610031
China

Jie Zeng

University of Electronic Science and Technology of China (UESTC) - Department of Cardiology ( email )

Sichuan, 610072
China

Hong Pu (Contact Author)

University of Electronic Science and Technology of China (UESTC) - Sichuan Provincial People’s Hospital ( email )

No.4, Section 2, North Jianshe Road
Chengdu, Chengdu 610031
China

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