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COVID-19

Dandelion and focal crazy paving signs: the lung CT based predictors for evaluation of the severity of coronavirus disease

, , , , , & show all
Pages 219-224 | Received 20 Jul 2020, Accepted 01 Nov 2020, Published online: 26 Nov 2020
 

Abstract

Purpose

To describe the radiological features of coronavirus disease 19 (COVID-19) and to explore the significant signs that indicate severity of disease.

Materials and methods

We collected data retrospectively of 180 cases of COVID-19, from 15 January 2020 to 31 March 2020, from both the Wuhan Zhongnan and Beijing Ditan Hospitals, including 103 cases of mild and 77 cases of severe pneumonia. All patients had their first chest computed tomography scan within five days of symptom onset. The dandelion sign was defined by a focal ground glass opacity (GGO) with a central thickening of the airway wall, and the focal crazy paving sign was defined by a focal GGO with thickening of the interlobular septa.

Results

Consolidation presented in only 4.9% (5/103) of the mild pneumonia cases, which was significantly lower than that in severe pneumonia cases (70.1% 54/77), p < .001). Multifocal distribution and pure GGOs were observed more frequently in severe cases of pneumonia (p < .05). The dandelion sign was present in 86.4% (89/103) of the mild pneumonia cases, significantly more frequent than those with severe pneumonia (13.0% [10/77], p < .001). The focal crazy paving sign presented in 65.0% (67/103) of the mild pneumonia cases and was significantly more frequent than in severe cases (23.4% [18/77], p < .001). The hospital stay duration of the mild pneumonia group (13.6 ± 7.2 days) was significantly shorter than the severe pneumonia group (26.6 ± 11.7 days, p < .001)

Conclusions

Consolidation, pure GGO and multifocal distribution on a CT scan were associated with severe COVID-19. The dandelion and focal crazy paving signs indicate mild COVID-19.

Transparency

Declaration of funding

This work was supported by the Ministry of Science and Technology of the People's Republic of China (Grant No. 2020YFC0845500) and the Science and Technology Department of Hubei Province (2020FCA039).

Declaration of financial/other relationships

No potential conflict of interest was reported by the authors. CMRO peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Acknowledgements

None reported.

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