Diagnosis of any disease requires careful assessment. Diagnostic procedures
might play a pivotal role in making the treatment protocols more powerful/potent
efficient, and effective by highlighting the clinical findings of the disease. Along with
other diagnostic techniques, a computed tomography (CT) scan has been employed to
diagnose coronavirus disease-19 (COVID-19) patients since the outbreak of this
disease and therefore promises it as a crucial diagnostic tool. A CT-scan is a
specialized medical imaging technique that produces cross-sectional images of specific
areas of a targeted object utilizing a combination of multiple X-ray measurements
taken from multiple angles. CT scan help diagnose COVID-19 individuals display
severe clinical features and advanced forms of the disease. Pulmonary CT images of
COVID-19 patients had common diagnostic manifestations such as ground-glass
opacities (GGO), consolidation, reticular pattern, and fibrosis. It also includes nodular
lesions reversed halo sign. and thickening of the pleura as the less common findings.
The receiver operative characteristic (ROC) curve has been successfully applied for
determining the accuracy of the CT-scan-based diagnosis of COVID-19. Artificial
intelligence (AI) techniques, particularly deep learning, are extensively used for
processing and evaluating imaging data, thereby improving the diagnostic performance
of radiologists and clinicians. Despite its emergence as an effective method for
screening COVID-19 patients, a CT scan is not recommended as a primary tool for
diagnosing COVID-19 and must be used with utmost caution as it may cause the
transmission of COVID-19 pathogen in the current epidemic. Overall, the current
chapter focuses on CT-scan implications in diagnosing the COVID-19 infection and its
comparison with the other diagnostic tools.
Keywords: Computed Tomography, Consolidation, Coronavirus, COVID-19,
Disease, Ground-Glass Opacity, Imaging, Receiver Operative Characteristic.