Pulmonary High Resolution Computed Tomography Findings of COVID-19 Patients Using CO-RADS Classification: A Study on Pakistani Population

Abstract

Background: This study aimed to use high-resolution computed tomography (HRCT) and the CO-RADS grading system to diagnose COVID-19 patients and determine severity.

Methodology: A retrospective study analyzed data from 280 patients at Aziz Bhatti Shaheed Hospital Gujrat between January and August 2021. Informed consent and ethical approval were secured. Data collection used a 64-slice multi-detector CT scanner, including patients with positive and negative COVID-19 polymerase chain reaction (PCR) findings. Data were analyzed using SPSS version 23.

Results: The study included more males (170, 60.7%) than females (110, 39.3%), with the most affected age group being 45-64 years. HRCT findings showed ground glass opacities in 212 cases (35.6%), consolidations in 158 cases (26.5%), Crazy paving sign in 54 cases (9.1%), pulmonary lesions in 54 cases (9.1%), interstitial lung disease in 42 cases (7.0%), pulmonary infiltrates in 32 cases (5.4%), atelectasis in 26 cases (4.4%), and pulmonary fibrosis in 18 cases (3.0%). CO-RADS classification results were: CO-RADS 1 (5, 1.8%), CO-RADS 2 (11, 3.9%), CO-RADS 3 (101, 36.1%), CO-RADS 4 (68, 24.3%), CO-RADS 5 (56, 20%), and CO-RADS 6 (39, 13.9%). PCR results were positive only in severe cases (starting from CO-RADS 2), while HRCT detected pulmonary findings even in less severe cases (starting from CO-RADS 1).

Conclusion: High-resolution computed tomography accurately and quickly identifies COVID-19 infections, even when PCR findings are negative. The CO-RADS technique effectively determines the severity and spread of COVID-19. CO-RADS 3 was the most frequently reported category, with typical findings including peripheral ground glass opacities and bilateral pleural consolidations.