Computed Tomography Spectrum of Complications in Usual Interstitial Pneumonia Pattern in a Tertiary Care Hospital: A Descriptive Cross- sectional Study

Idiopathic pulmonary fibrosis is the most prevalent form of interstitial lung disease, which presents as usual interstitial pneumonia on histopathology and imaging. It leads to significant lung scarring, damage, and fibrosis and is associated with a high degree of mortality, repeated hospital admissions, and oxygen dependence. Many complications are associated with idiopathic pulmonary fibrosis, which further increases the morbidity of patients. High-resolution computed tomography chest is the imaging modality of choice for usual interstitial pneumonia tracking its progression, evaluating treatment response, and detecting potential complications. This descriptive cross-sectional study was approved by the Institutional Ethics Committee (Reference number: IEC-INT/2023/Study-1256). Departmental computed tomography report database from November, 2017 to June, 2018 was reviewed and scans with imaging features consistent with the 'usual interstitial pneumonia' pattern were identified. Total sampling method was used and two independent radiologists, blinded to the patient's clinical information, reviewed the high-resolution computed tomography chest scans to assess for imaging features of usual interstitial pneumonia and associated complications. Data was collected and analyzed using Microsoft Excel. There were 65 patients reported as unusual interstitial pneumonia pattern. Emphysema and pneumothorax were identified in 4 (6.15%) and 1 (1.53%) scans, respectively. Two (3.08%) scans showed features of pulmonary arterial hypertension. Ten (15.38%) scans exhibited findings consistent with co-existent or superimposed pulmonary infection. Additionally, features of lung malignancy were identified in high-resolution computed tomography scans of 5 (7.69%) patients. Patients with UIP often experience severe lung scarring, and frequent complications, and require regular chest CT scans to monitor disease progression and identify potential complications.