Shokrollah Hafez EFTEKHARI, Anahita AZINFAR, Masoud Mahdavi RASHED, Mahdi Abdollahi KARIZNO
Thoracic Research and Practice - 2026;27(4):200-206
OBJECTIVE: Accurate diagnosis of pulmonary cavitary lesions in children is essential for effective treatment and prevention of complications. While chest X-rays are commonly used, they lack the precision needed for detailed lesion characterization. Non-contrast high-resolution computed tomography (CT) scans offer superior imaging capabilities, particularly for cavitary lesions, though their use in pediatric patients must be balanced against radiation exposure risks. This study evaluates the diagnostic utility of non-contrast CT in distinguishing among hydatid cysts, necrotizing pneumonia, and lung abscesses by incorporating both clinical and imaging data. MATERIAL AND METHODS: Conducted as a cross-sectional study at Akbar Hospital (Mashhad University of Medical Sciences) from 2021 to 2023, the study included pediatric patients who presented with pulmonary symptoms and underwent non-contrast lung CT. Statistical analyses involved chi-square tests for categorical variables and t-tests or non-parametric equivalents for continuous data. Diagnostic metrics such as sensitivity, specificity, predictive values, and accuracy were calculated. RESULTS: Key radiological features that identify necrotizing pneumonia with high sensitivity and specificity include irregular lesion borders and fully aerated lesions. Additional indicators, such as pleural effusion heterogeneity and pneumothorax, further enhanced diagnostic accuracy. Hydatid cysts were reliably diagnosed by the presence of floating membranes and associated cystic structures, each demonstrating 100% specificity. In contrast, lung abscesses lacked distinctive imaging features, underscoring the need for further research. CONCLUSION: Non-contrast CT is a valuable diagnostic tool for pediatric cavitary pulmonary lesions, particularly necrotizing pneumonia and hydatid cysts. The findings support the adoption of standardized imaging protocols to improve diagnostic precision and clinical outcomes.
