Opportunities and Challenges of Artificial Intelligence in Pediatric Radiology

Dear Colleagues,

According to the 2024 survey conducted among European Society of Radiology (ESR) members by the European Network for the Assessment of Imaging in Medicine (EuroAIM) and the European Society of Medical Imaging Informatics (EuSoMII), about 50% of respondents have already used artificial intelligence (AI) in their radiology practice, and another quarter plans to implement it. More than half of the respondents reported being very satisfied or satisfied with the AI software, while 12% were very unsatisfied or unsatisfied.

Its subspecialty, pediatric radiology, is also aligned with this trend, with the popularity of AI steadily increasing. For example, between February 2024 and September 2025, the number of USA Food and Drug Administration (FDA)-approved AI products for pediatric radiology more than doubled (from 13 to 30). This underscores the need for further research to better understand the opportunities and challenges of AI use in pediatric radiology.

This Special Issue invites researchers, academics, and clinicians to publish high-quality research and review articles on the development and/or application of AI across various aspects of pediatric radiology workflows. Topics may include examination scheduling, protocol automation, radiation dose optimization, image quality enhancement, image segmentation, triage, computer-aided diagnosis, report generation, radiomics, and clinical decision support. Additionally, investigations or reviews addressing ethical and safety issues related to AI in pediatric radiology are welcome.

By contributing to this Special Issue, authors will help broaden and strengthen the existing evidence base for AI in pediatric radiology, benefiting patients, researchers, academic and clinical communities, policymakers, and other influential bodies.

Dr. Curtise K. C. Ng
Guest Editor

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