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Updated: Dec 12, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Computed tomography surveillance helps tracking COVID-19 outbreak
Akihiro Machitori1, Tomoyuki Noguchi2,3,4, Yusuke Kawata1
1Department of Radiology, National Center for Global Health and Medicine, Kohnodai Hospital, 1-7-1 Kohnodai, Ichikawa City, Chiba Province, 272-8516, Japan.
Purpose:
To reveal that a computed tomography surveillance program (CT-surveillance) could demonstrate the epidemiologic features of COVID-19 infection and simultaneously investigate the type and frequency of CT findings using clinical CT data.
Materials And Methods:
We targeted individuals with possible CT findings of viral pneumonia. Using an online questionnaire, we asked Japanese board-certified radiologists to register their patients' information including patient age and sex, the CT examination date, the results of PCR test for COVID-19 infection, CT findings, and the postal code of the medical institution that performed the CT. We compared the diurnal patient number and the cumulative regional distribution map of registrations in CT-surveillance to those of the PCR-positive patient surveillance (PCR-surveillance).
Results:
A total of 637 patients was registered from January 1 to April 17, 2020 for CT-surveillance. Their PCR test results were positive (n = 62.5-398%), negative (n = 8.9-57%), unknown (n = 26.2-167%), and other disease (n = 2.4-15%). An age peak at 60-69 years and male dominance were observed in CT-surveillance. The most common CT finding was bilaterally distributed ground-glass opacities. The diurnal number and the cumulative regional distribution map by CT-surveillance showed tendencies that were similar to those revealed by PCR-surveillance.
Conclusion:
Using clinical CT data, CT-surveillance program delineated the epidemiologic features of COVID-19 infection.
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