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Published on: July 30, 2009
Insights Into MRI Neuroimaging Patterns of COVID-19 in Children: A Retrospective Comprehensive Analysis
Mohamad Gamal Nada1, Yassir Edrees Almalki2, Mohammad Abd Alkhalik Basha1
1Department of Diagnostic Radiology, Faculty of Human Medicine, Zagazig University, Zagazig, Egypt.
Rationale And Objectives:
Neurological complications associated with coronavirus disease (COVID-19) have been reported in children; however, data on neuroimaging findings remain limited. This study aimed to comprehensively examine neuroimaging patterns of COVID-19 in children and their relationship with clinical outcomes.
Materials And Methods:
This retrospective cross-sectional study involved reviewing the medical records and MRI scans of 95 children who developed new neurological symptoms within 2-4 weeks of clinical and laboratory confirmation of COVID-19. Patients were categorized into four groups based on guidelines approved by the Centers for Disease Control and Prevention (CDC). Initial brain/spinal MRI was performed. Images were reviewed by three blinded radiologists, and the findings were analyzed and categorized based on the observed patterns in the brain and spinal cord. Follow-up MRI was performed and analyzed to track lesion progression.
Results:
Encephalopathy was the most common neurological symptom (50.5%). The most common initial MRI involvement patterns were non-confluent multifocal hyperintense white matter (WM) lesions (36.8%) and ischemia (18.9%). Most patients who underwent follow-up MRI (n = 56) showed complete resolution (69.9%); however, some patients developed encephalomalacia and myelomalacia (23.2% and 7.1%, respectively). Non-confluent hyperintense WM lesions were associated with good outcomes (45.9%, P = 0.014), whereas ischemia and hemorrhage were associated with poor outcomes (44.1%, P < 0.001).
Conclusion:
This study revealed diverse neuroimaging patterns in pediatric COVID-19 patients. Non-confluent WM lesions were associated with good outcomes, whereas ischemia and hemorrhage were associated with poorer prognoses. Understanding these patterns is crucial for their early detection, accurate diagnosis, and appropriate management.
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