Computed tomography surveillance helps tracking COVID-19 outbreak

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.