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"Multimodal" Imaging Performance and Clinical Application of Coronavirus Disease 2019 (COVID-19) (preprint)
researchsquare; 2020.
Preprint in English | PREPRINT-RESEARCHSQUARE | ID: ppzbmed-10.21203.rs.3.rs-132295.v1
ABSTRACT

Background:

To investigate the diagnostic value of three different examination methods of chest radiography (CXR), digital tomosynthesis (DTS) and Computed tomography (CT) scan on the diagnosis of novel coronavirus pneumonia (COVID-19).

Methods:

A retrospective analysis of three examination methods of chest CXR, DTS, and CT scan of COVID-19 pneumonia patients diagnosed in our hospital from January, 23, 2020 to February, 29, 2020. And we compared three different imaging methods to COVID-19 display ability of pneumonia intrapulmonary lesions.

Results:

A total of 37 patients diagnosed as COVID-19 by nucleic acid testing were included. The CXR group (10/37) and DTS group (21/28) of 37 patients with COVID-19 pneumonia showed significant differences in intrapulmonary ground glass opacities (P<0.05); DTS group (21/28) and CT group (25/27) showed no statistically significant differences in intrapulmonary ground glass opacities (P> 0.05).

Conclusion:

Comparison of the three imaging methods of COVID-19 pneumonia, the diagnostic efficiency of CXR is low, which is easy to be false negative and miss lesions; diagnostic resolutions of DTS are higher than CXR, which can improve the ability to display the fine structure of intrapulmonary lesions; CT scan shows the intrapulmonary of COVID-19 pneumonia low-density ground glass opacities and internal structures have equal capacity compared with DTS. Therefore, DTS and CT are the best choices for the image diagnosis of COVID-19 pneumonia.
Subject(s)

Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Pneumonia / Coronavirus Infections / COVID-19 Language: English Year: 2020 Document Type: Preprint

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Full text: Available Collection: Preprints Database: PREPRINT-RESEARCHSQUARE Main subject: Pneumonia / Coronavirus Infections / COVID-19 Language: English Year: 2020 Document Type: Preprint