REVIEW   Free access

Journal of Radiological Review 2021 September;8(3):206-10

DOI: 10.23736/S2723-9284.21.00150-4

Copyright © 2021 EDIZIONI MINERVA MEDICA

language: English

Chest computed tomography and COVID-19: imaging features, sensitivity, specificity and prognostic role in patients with COVID-19

Valeria PAGLIEI ¹ ✉, Riccardo MONTI ¹, Pierpaolo PALUMBO ^{1, 2, 3}, Federico BRUNO ^{1, 2}, Francesco ARRIGONI ^{1, 3}, Ernesto DI CESARE ⁴, Alessandra SPLENDIANI ¹, Antonio BARILE ¹, Carlo MASCIOCCHI ¹

¹ Department of Applied Medical Sciences and Biotechnology, University of L’Aquila, L’Aquila, Italy; ² Italian Society of Medical and Interventional Radiology, SIRM Foundation, Milan, Italy; ³ Abruzzo Health Unit 1, Department of Diagnostic Imaging, Area of Cardiovascular and Interventional Imaging, L’Aquila, Italy; ⁴ Department of Clinical Medicine, Public Health, Life and Environmental Science, University of L’Aquila, L’Aquila, Italy

Since SARS-CoV-2 infection has been spreading worldwide, chest-CT has gained an increasing importance the clinical management of infected people. The aim of this review is to illustrate the role of chest-CT in diagnosing COVID-19 as well as in predicting the course of the respiratory involvement. Chest-CT imaging features has been identified and described in the scientific literature, with GGOs, consolidation, “crazy-paving” pattern, vessel enlargement and air bronchogram being considered the most common findings. Considering the high sensitivity, chest Computed tomography provided a useful tool to assess the severity of the disease. Additionally, the observation of certain features on scans performed upon admission may enable clinicians to predict the patients’ prognosis. Unfortunately, despite showing a high sensitivity in comparison to the results of Real-time reverse transcription-polymerase chain reaction, the specificity is low. For this reason, its use in the diagnosis and management of people affected is still limited to particular circumstances.

KEY WORDS: Tomography, X-ray computed; COVID-19; Respiratory tract diseases