REVIEW   Free access

Journal of Radiological Review 2021 September;8(3):186-94

DOI: 10.23736/S2723-9284.21.00146-2

Copyright © 2021 EDIZIONI MINERVA MEDICA

language: English

CT classification system of COVID-19 patients: a review of the literature

Eleonora BICCI ✉, Federica FLAMMIA, Diletta COZZI, Edoardo CAVIGLI, Silvia LUVARÀ, Silvia PRADELLA, Vittorio MIELE

Department of Emergency Medicine and Radiodiagnostics, Careggi University Hospital, Florence, Italy

Coronavirus disease 2019 (COVID-19) is an infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that lead to a pandemic status declared by the World Health Organization (WHO) on March 12^th, 2020. Real time reverse transcription polymerase chain reaction (RT-PCR) of viral nucleic acid is currently considered the gold standard for the diagnosis. However, computed tomography (CT), given its high sensitivity, is considered a necessary tool in order to assess pulmonary involvement and extent of disease. Therefore, validating a standardized assessment of pulmonary involvement of COVID-19, using CT classifications, is becoming increasingly important during this pandemic. Different classifications have been created in order to standardize chest CT findings of patients with COVID-19 pneumonia, including the COVID-19 Reporting and Data System (CO-RADS) created by The Dutch Radiological Society, the Radiological Society of North America (RSNA) chest CT classification system, and the COVID-19 imaging reporting and data system (COVID-RADS). Chest CT classifications demonstrated excellent sensitivities and positive predictive values for detection of COVID on imaging, although they differ in stratification into different categories based on the increasingly typical features of COVID-19 infection. The categories most suggestive of pulmonary involvement often show high association with positive RT-PCR test. CT classifications, based on quantitative parameters, is an effective and important method for assessing the severity of pulmonary involvement by COVID-19 that can reduce observer variation, improve communication and reproducibility, capable of providing additional guidance for planning clinical treatment strategies.

KEY WORDS: COVID-19; X-ray computed tomography; Classification; Thorax