Role of High-Resolution Computed Tomography in Differentiating Post-COVID-19 Pulmonary Fibrosis from Fibrosing Interstitial Lung Diseases

Background: It is important to distinguish between various causes of pulmonary fibrosis, including post-COVID-19 pulmonary fibrosis and fibrosing interstitial lung diseases (FILDs), such as idiopathic pulmonary fibrosis (IPF), sarcoidosis, connective tissue diseases as well as fibrotic hypersensitivity pneumonitis. The current study aimed for differentiation between post-COVID-19 pulmonary fibrosis and FILDs using high resolution computed tomography (HRCT). Methods: We conducted this retrospective study on 36 patients, divided into two groups: group I: 18 patients diagnosed with post-COVID-19 pulmonary fibrosis and group II: 18 patients diagnosed with FILDs. All patients underwent HRCT of the chest. The following HRCT pulmonary features were recorded and compared between the two patients’ groups: lung volume, reticulations, subpleural sparing sign, subpleural fibrosis, traction bronchiectasis, honeycombing, GGO, nodules, cysts, consolidation, mosaic attenuation, and emphysema. Results: Mild fibrosis was more common in post-COVID-19 patients (66.7%) vs. FILDs (11.1%, P=0.002), while severe fibrosis predominated in FILDs (66.7% vs. 5.6%, P<0.001). Subpleural fibrosis was more frequent in FILDs (94.4% vs. 33.3%, P<0.001), whereas subpleural sparing was more common post-COVID-19 (66.7% vs. 5.6%, P<0.001). HRCT showed significant axial and zonal distribution differences (P<0.001), with lower zonal involvement more common post-COVID-19 (50% vs. 11.1%, P=0.03), and diffuse distribution more frequent in FILDs (77.8% vs. 38.9%, P=0.02). Subpleural fibrosis and diffuse axial distribution were independent predictors of post-COVID-19 fibrosis. Conclusion: HRCT can efficiently ‎differentiate between post-COVID-19 pulmonary fibrosis and FILDs.‎ On HRCT, subpleural fibrosis and diffuse axial distribution of the pulmonary fibrosis can used as independent predictors of post-COVID-19 fibrosis.