Diagnostic Interstitial Lung Diseases in Patients Having Normal Chest Radiograph through High Resolution Computed Tomography

Abstract

Background: In Pakistan, the main cause of death is interstitial lung disease (ILD) i.e., 4.75%. In interstitial lung disease majority of the patients is about the age of 57.5 years. The age group maybe varying between the ages of 46 and 65 year. Female gender is more predominantly i.e., 65.6% in all types of ILD except the interstitial pulmonary fibrosis (P< 0.001).

Objective: The aim of our study is to diagnose interstitial lung diseases in patients having normal chest radiograph through high resolution computed tomography.

Study design: Our study design was cross-sectional descriptive study.

Material and method: The descriptive cross-sectional study was conducted in which data of 100 patients were taken. The data was collected from the Radiology department of Sheikh Zayed Hospital Rahim Yar Khan. After informed consent, data was collected through CT Toshiba 164 slices.

Result: 100 patients were included in our study out of which 61 were females and 39 were male’s with the mean age of 49.32 years. The chest radiograph of the patients having ILD shows the patchy ground glass opacities (39.0%), consolidation of the lungs (21.0%), reticular shadowing (16.0%) and the pleural effusion (24.0%) while on the high-resolution computed tomography the patients were represented with ground glass haze (42.0%), calcific foci (21.0%), nodular lesion (16.0%), consolidation of the lungs (30.0%) and pleural effusion (22.0%).

Conclusion: Chest radiograph nearly misses common radiographical features which are suggestive of interstitial lung disease but can be seen on High Resolution Computed Tomography (HRCT) due to its high resolution. So, it can be concluded that the HRCT is more efficient and authentic diagnostic equipment in assessing the Interstitial Lung Disease as compared to the chest radiograph.

Keywords: Interstitial lung disease, Chest radiograph, Computed tomography, High resolution computed tomography.

DOI: 10.7176/JHMN/91-04

Publication date:July 31^st 2021