[Correlation between clinical classification of COVID-19 and imaging characteristics of MSCT volume scanning of the lungs].

Objective: To investigate the correlation between the clinical classification of coronavirus disease 2019 (COVID-19) and the imaging characteristics of multislice spiral computed tomography (MSCT) volume scanning of the lungs.

Methods: The clinical data and thoracic MSCT volume scanning data were analyzed retrospectively for 102 patients with COVID-19 diagnosed and hospitalized in the First Affiliated Hospital of Bengbu Medical College between January 18 and February 26, 2020. According to the Fifth Edition of the Diagnosis and Treatment Guidelines by the National Health Commission, the patients were divided into common type, severe type and critical type. The imaging characteristics including the lung sides of the lesions, lung segment involved, lesion distribution, and lesion number and density were compared among the patients with different clinical types of COVID-19.

Results: Seventy-seven of the patients had common type, 18 had severe type and 7 had critical type of COVID-19. The main clinical manifestations included fever, cough and fatigue. Severe and critical types were more frequently seen in elderly patients, who were more prone to show such symptoms as asthenia, breathing difficulty and dyspnea. Two patients presented with no obvious abnormality in the first CT examinations; in the remaining 100 patients, 89.0% had bilateral lung lesions, 16.0% had diffuse lesions, involving a mean of 6.56±4.22 lung segments. Compared with the patients with the common type, the severe and critical patients had a significantly greater number of lung segments involved ( < 0.05), and were also more likely to show diffuse lesions ( < 0.05). The lesion side, lesion number or lesion density did not differ significantly among the patients with different clinical types of COVID-19 ( > 0.05).

Conclusions: MSCT volume scanning not only allows early diagnosis of COVID-19 but also provides evidence for evaluating the severity of COVID-19 to assist in the clinical treatment of the patients.