Radiologic Analysis of Ct Imaging Patterns and Clinical Correlations in Hospitalized Pediatric Covid-19 Patients Publisher



Aghabeygiha M¹ ; Fahimzad SA¹ ; Behzad S² ; Zadeh RH³ ; Sheikhzadeh F⁴ ; Tamaddon Y⁵ ; Hajipour M⁶ ; Zadeh RH³ ; Neyriz A⁸ ; Pak N⁹ ; Shirvani A⁶ ; Hosseini A⁶ ; Khalili M¹⁰
Source: Frontiers in Radiology Published:2025

Abstract

Background and objective: COVID-19 has emerged as a global pandemic affecting individuals of all ages. The disease can lead to severe complications and even death, particularly due to pulmonary involvement. Contrary to popular belief, children can also experience significant complications from COVID-19. To date, there have been limited studies focusing on pulmonary manifestations in pediatric patients with COVID-19. This study aims to investigate the imaging patterns (CT scans) in children diagnosed with COVID-19 in Iran. Materials and methods: This retrospective study analyzed data from hospitalized children with COVID-19 in Tehran from March 2020 to September 2020. Information collected included demographic details (sex and age), previous medical history, clinical manifestations, vital signs at admission, laboratory findings, and imaging results, including CT scan and chest x-ray. Results: 252 patients were included, with a mean age of 71.2 ± 59.42 months; 58.3% were male. Fever was the most prevalent symptom, occurring in 67.4% of cases. The most common underlying condition was oncological disorders, present in 85% of patients. Notably, 52% required admission to the ICU, and 1.8% needed intubation. CT scans revealed that the most frequent lung involvement patterns were mixed patterns and consolidation, with bilateral involvement being the most common. The mean CT score was calculated at 3 ± 4. Abnormal CT findings were associated with a poorer prognosis, and correlations were observed between specific CT findings and clinical manifestations. Conclusion: Chest CT manifestations offer valuable insights for assessing pediatric patients with COVID-19, especially in severe cases and those with pre-existing health conditions. Integrating clinical evaluations with radiological scoring systems facilitates early identification of disease severity. 2025 Aghabeygiha, Fahimzad, Behzad, Zadeh, Sheikhzadeh, Tamaddon, Hajipour, Zadeh, Neyriz, Pak, Shirvani, Hosseini and Khalili.