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鉴别 2019 新型冠状病毒病(COVID-19)与流感肺炎的特征性 CT 表现。

Characteristic CT findings distinguishing 2019 novel coronavirus disease (COVID-19) from influenza pneumonia.

机构信息

Department of Radiology, Minhang Hospital, Fudan University, 170 Xinsong Road, Shanghai, 201199, People's Republic of China.

Department of Clinical Laboratory, Minhang Hospital, Fudan University, 170 Xinsong Road, 201199, Shanghai, People's Republic of China.

出版信息

Eur Radiol. 2020 Sep;30(9):4910-4917. doi: 10.1007/s00330-020-06880-z. Epub 2020 Apr 22.


DOI:10.1007/s00330-020-06880-z
PMID:32323011
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7175830/
Abstract

OBJECTIVES: To investigate the different CT characteristics which may distinguish influenza from 2019 coronavirus disease (COVID-19). METHODS: A total of 13 confirmed patients with COVID-19 were enrolled from January 16, 2020, to February 25, 2020. Furthermore, 92 CT scans of confirmed patients with influenza pneumonia, including 76 with influenza A and 16 with influenza B, scanned between January 1, 2019, to February 25, 2020, were retrospectively reviewed. Pulmonary lesion distributions, number, attenuation, lobe predomination, margin, contour, ground-glass opacity involvement pattern, bronchial wall thickening, air bronchogram, tree-in-bud sign, interlobular septal thickening, intralobular septal thickening, and pleural effusion were evaluated in COVID-19 and influenza pneumonia cohorts. RESULTS: Peripheral and non-specific distributions in COVID-19 showed a markedly higher frequency compared with the influenza group (p < 0.05). Most lesions in COVID-19 showed balanced lobe localization, while in influenza pneumonia they were predominantly located in the inferior lobe (p < 0.05). COVID-19 presented a clear lesion margin and a shrinking contour compared with influenza pneumonia (p < 0.05). COVID-19 had a patchy or combination of GGO and consolidation opacities, while a cluster-like pattern and bronchial wall thickening were more frequently seen in influenza pneumonia (p < 0.05). The lesion number and attenuation, air bronchogram, tree-in-bud sign, interlobular septal thickening, and intralobular septal thickening were not significantly different between the two groups (all p > 0.05). CONCLUSIONS: Though viral pneumonias generally show similar imaging features, there are some characteristic CT findings which may help differentiating COVID-19 from influenza pneumonia. KEY POINTS: • CT can play an early warning role in the diagnosis of COVID-19 in the case of no epidemic exposure. • CT could be used for the differential diagnosis of influenza and COVID-19 with satisfactory accuracy. • COVID-19 had a patchy or combination of GGO and consolidation opacities with peripheral distribution and balanced lobe predomination.

摘要

目的:探讨可能有助于鉴别流感与 2019 冠状病毒病(COVID-19)的不同 CT 特征。

方法:2020 年 1 月 16 日至 2 月 25 日期间共纳入 13 例确诊 COVID-19 患者。此外,回顾性分析了 2019 年 1 月 1 日至 2020 年 2 月 25 日期间确诊的 92 例流感肺炎患者的 CT 扫描结果,其中流感 A 病毒 76 例,流感 B 病毒 16 例。评估 COVID-19 和流感肺炎组的肺部病变分布、数量、衰减、优势叶、边缘、轮廓、磨玻璃影(GGO)累及模式、支气管壁增厚、空气支气管征、树芽征、小叶间隔增厚、细支气管壁增厚和胸腔积液。

结果:COVID-19 的外周和非特异性分布较流感组更为常见(p<0.05)。COVID-19 病变多呈均衡叶位分布,而流感肺炎病变主要位于下叶(p<0.05)。与流感肺炎相比,COVID-19 的病变边界清晰,轮廓缩小(p<0.05)。COVID-19 呈斑片状或 GGO 与实变影混合影,而流感肺炎更常见呈簇状影和支气管壁增厚(p<0.05)。两组病变数量和衰减、空气支气管征、树芽征、小叶间隔增厚和细支气管壁增厚差异均无统计学意义(均 p>0.05)。

结论:尽管病毒性肺炎的影像学特征一般相似,但 COVID-19 与流感肺炎之间仍存在一些特征性 CT 表现,有助于鉴别诊断。

重点:

  • CT 可在无流行病史的情况下对 COVID-19 起到早期预警作用。
  • CT 有助于对流感和 COVID-19 进行鉴别诊断,且具有较高的准确性。
  • COVID-19 呈外周分布和均衡叶位优势,病变为斑片状或 GGO 与实变影混合影。

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[2]
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[10]
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[2]
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[3]
Differences in clinical characteristics between coronavirus disease 2019 (COVID-19) and influenza: a systematic review and meta-analysis.

NPJ Prim Care Respir Med. 2025-1-28

[4]
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[5]
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[6]
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[7]
COVID-19 diagnostic approaches with an extensive focus on computed tomography in accurate diagnosis, prognosis, staging, and follow-up.

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[8]
CT Examinations for COVID-19: A Systematic Review of Protocols, Radiation Dose, and Numbers Needed to Diagnose and Predict.

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[9]
Radiological Findings in SARS-CoV-2 Viral Pneumonia Compared to Other Viral Pneumonias: A Single-Centre Study.

Can J Infect Dis Med Microbiol. 2022-9-29

[10]
Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study.

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本文引用的文献

[1]
CT image visual quantitative evaluation and clinical classification of coronavirus disease (COVID-19).

Eur Radiol. 2020-3-25

[2]
Coronavirus disease 2019: initial chest CT findings.

Eur Radiol. 2020-3-24

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Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review.

Eur Radiol. 2020-3-19

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World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19).

Int J Surg. 2020-2-26

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Eur Radiol. 2020-2-13

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Radiology. 2020-4

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Evolution of CT Manifestations in a Patient Recovered from 2019 Novel Coronavirus (2019-nCoV) Pneumonia in Wuhan, China.

Radiology. 2020-4

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Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China.

JAMA. 2020-3-17

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