Applications of CT in the Early Prediction of Different Clinical Types of COVID -19 Pneumonia

Yun-hui YANG; Bo HE; Ding-yun YOU; Jun-tao YANG; Qian GAO

doi:10.12259/j.issn.2095-610X.S20210524

Volume 42 Issue 5

May 2021

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Article Navigation > Journal of Kunming Medical University > 2021 > 42(5): 131-137

Yun-hui YANG, Bo HE, Ding-yun YOU, Jun-tao YANG, Qian GAO. Applications of CT in the Early Prediction of Different Clinical Types of COVID -19 Pneumonia[J]. Journal of Kunming Medical University, 2021, 42(5): 131-137. doi: 10.12259/j.issn.2095-610X.S20210524

Citation:

Yun-hui YANG, Bo HE, Ding-yun YOU, Jun-tao YANG, Qian GAO. Applications of CT in the Early Prediction of Different Clinical Types of COVID -19 Pneumonia[J]. Journal of Kunming Medical University, 2021, 42(5): 131-137. doi: 10.12259/j.issn.2095-610X.S20210524

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Applications of CT in the Early Prediction of Different Clinical Types of COVID -19 Pneumonia

doi: 10.12259/j.issn.2095-610X.S20210524

1.
Dept. of Medical Imaging，The People’s Hospital of Xishuangbanna Dai Autonomous Prefecture，Xishuangbanna Yunnan 666100
2.
Dept. of Medical Imaging，The 1st Affiliated Hospital of Kunming Medical University，Kunming Yunnan 650032
3.
School of Public Health，Kunming Medical University，Kunming Yunnan 650500
4.
Dept. of Radiology，The People’s Hospital of Dali Bai Autonomous Prefecture，Dali Yunnan 671000，China

Received Date: 2021-01-17
Available Online: 2021-06-03
Publish Date: 2021-05-20

Abstract

Abstract

Objective To investigate the clinical and CT image characteristics of COVID-19 pneumonia, and the predictive value of CT in the early stage of different clinical types. Methods Chest CT and clinical data of confirmed 143 patients with COVID-19 pneumonia in January to February 2020 were enrolled. According to the diagnosis and treatment of COVID-19 pneumonia（trial version 7）, all the patients were classified into the mild （n = 28）, common （n = 92）, severe （n = 36）, and critical （n = 5） type, and their clinical findings and CT findings were analyzed. CT features included lesions' distribution, density, extension, shape, interior/ periphery features, vascular changes. Then the prediction performance of image features were analyzed. Results The main clinical manifestations were fever （60/143, 41.9%） and cough （57/143, 39.9%）. High fever was more common seen in severe patients. Severe and critical types were more common in elderly patients. And the total number of lymphocytes reduced （0.6±0.2x10^9/L） in critical patients. Except for mild patients, there were 6 cases without the obvious abnormality in the first CT diagnosis. In the remaining 109 cases, the number of pulmonary segments involved in the first CT examination of severe patients was significantly higher than that of common patients （5.88 ± 6）（P < 0.001）. Severe and critical COVID-19 showed wedge-shape （59/109, 54.1%） or Ficus crown sign （35/109, 32.1%） lesions more frequently than in common COVID-19 and the thickening of blood vessels （87/109, 79.8%） and vascular clustering signs （65/109, 59.6%） in / around the lesions were more likely to occur in severe and critical types （P < 0.05）. There was no significant difference in the number of lesions, lesion density, lesion morphology （round, irregular） and internal/peripheral features of the lesion （crazy-paving sign, halo sign, bronchiectasis）（P > 0.05）. Area under the curve （AUC） of the number of involved lung segments, wedge-shape and Ficus crown sign （AUC: 0.769, 0.759, 0.697, respectively） were higher compared with that of thickening of blood vessels and vascular clustering signs （AUC: 0.626, 0.667, respectively）. Combined model resulted in a further increased diagnostic performance （AUC: 0.854）. Conclusion Chest CT findings not only play an important role in the early diagnosis of COVID-19, but also can evaluate the severity and prognosis of patients.
- COVID-19 pneumonia,
- Computed tomography,
- Clinical types

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References(13)

References

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