北京首例由输入病例导致社区感染的新型冠状病毒肺炎患者：深度学习CT辅助诊断的作用

李大胜; 王大为; 王娜娜; 徐海旺; 黄河; 董建平; 夏晨

doi:10.24920/003788

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北京首例由输入病例导致社区感染的新型冠状病毒肺炎患者：深度学习CT辅助诊断的作用

中国医学科学杂志（英文版） 2021年36卷第1期页码：66-71

Case Report | Updated：2024-04-10

- 北京首例由输入病例导致社区感染的新型冠状病毒肺炎患者：深度学习CT辅助诊断的作用
- Affiliations：
  
  1. 1Department of Radiology, Beijing Haidian Section of Peking University Third Hospital (Beijing Haidian Hospital), Beijing 100080, China
  2. 2Institute of Advanced Research, Infervision Medical Technology Co., Ltd., Beijing 100025, China
  3. 3Department of Infection, Beijing Haidian Section of Peking University Third Hospital (Beijing Haidian Hospital), Beijing 100080, China;
- Author bio：
  
  *Dasheng Li, E-mail: 724501143@qq.com; Tel: 86-10-82693260.
- Funds：
- DOI：10.24920/003788
  中图分类号：
- 收稿日期：2020-05-28，
  
  录用日期：2020-7-16，
  
  网络出版日期：2021-03-31，
  
  纸质出版日期：2021-03-31
- Accepted：
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李大胜, 王大为, 王娜娜, 等. 北京首例由输入病例导致社区感染的新型冠状病毒肺炎患者：深度学习CT辅助诊断的作用[J]. 中国医学科学杂志（英文版）, 2021,36(1):66-71.

Li Dasheng, Wang Dawei, Wang Nana, et al. An Insight of the First Community Infected COVID-19 Patient in Beijing by Imported Case: Role of Deep Learning-Assisted CT Diagnosis[J]. Chinese medical sciences journal, 2021, 36(1): 66-71.
李大胜, 王大为, 王娜娜, 等. 北京首例由输入病例导致社区感染的新型冠状病毒肺炎患者：深度学习CT辅助诊断的作用[J]. 中国医学科学杂志（英文版）, 2021,36(1):66-71. DOI： 10.24920/003788.

Li Dasheng, Wang Dawei, Wang Nana, et al. An Insight of the First Community Infected COVID-19 Patient in Beijing by Imported Case: Role of Deep Learning-Assisted CT Diagnosis[J]. Chinese medical sciences journal, 2021, 36(1): 66-71. DOI： 10.24920/003788.

摘要

在新型冠状病毒肺炎（COVID-19）全球大流行的时代

输入型COVID-19病例给许多国家的疫情防控带来巨大挑战。对于COVID-19的检测和诊断

胸部CT检查可以作为核酸检测结果的有效补充手段。我们报道了中国北京第一例由输入型病例获得COVID-19感染的患者。我们发现胸部CT上结节性病变是该COVID-19患者的早期影像学表现

深度学习（deep learning

DL）辅助诊断系统定量监测患者肺部病变的发展情况

并及时预警为疑似肺炎

由此我们迅速对该患者进行了医学隔离。经核酸检测

患者最终被确诊为COVID-19

因而社区传播获得了及时的控制。本文进一步讨论了基于DL的CT辅助诊断系统在协助医生筛查和预警COVID-19疑似病例过程中的作用。

Abstract

In the era of coronavirus disease 2019 (COVID-19) pandemic

imported COVID-19 cases pose great challenges to many countries. Chest CT examination is considered to be complementary to nucleic acid test for COVID-19 detection and diagnosis. We report the first community infected COVID-19 patient by an imported case in Beijing

which manifested as nodular lesions on chest CT imaging at the early stage. Deep Learning (DL)-based diagnostic systems quantitatively monitored the progress of pulmonary lesions in 6 days and timely made alert for suspected pneumonia

so that prompt medical isolation was taken. The patient was confirmed as COVID-19 case after nucleic acid test

for which the community transmission was prevented timely. The roles of DL-assisted diagnosis in helping radiologists screening suspected COVID cases were discussed.

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