About this Research Topic
Pediatrics neuroradiology is a subspeciality of radiology that focuses on the use of advanced neuroimaging techniques to study brain growth and to diagnose diseases and malformations in neonates, infants, toddlers, children, and adolescents. Recent technical and methodological developments, and the use of artificial intelligence (AI) has improved the field of pediatric neuroradiology, resulting in enhanced diagnostic care, personalized treatments, and better patient outcomes. Pediatric neuroradiology plays a key role in diagnosing, characterizing, and monitoring the progression of neurological disorders in children. A wide variety of imaging techniques including magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound (US) are employed for the evaluation of conditions common among children. One of the most challenging aspects of pediatric neuroradiology is the need for age-specific considerations for processing and interpreting imaging exams in relation to different age groups due to the dynamic and ongoing development of the brain from neonacy to adolescence. This requires knowledge of early developing patterns in neurotypical subjects and development milestones.
The objective of this Research Topic is to highlight recent advances in pediatric neuroradiology that encompass novel approaches in neuroimaging, post-acquisition image processing techniques, medical image analysis, neurodevelopmental studies, and disease diagnosis. This Research Topic will provide the platform to bring together research content related to the human brain during developmental years, allowing better understanding of the normal and deviated brain growth.
We welcome research articles, reviews, or case reports covering the following topics, but are not limited to:
• Use of AI or machine learning to develop methods for post-acquisition image processing, image analysis, or computer aided diagnosis among pediatric cohorts.
• Quality control and artifacts correction in pediatric neuroimaging data.
• Development of data harmonization approaches and standardization of preprocessing pipelines.
• Structural, diffusion, or functional imaging to investigate brain structure and functional connectivity.
• Computational methods for studying neurodevelopment, identifying critical imaging biomarkers, and investigating the impact of socioeconomic status on brain development.
The objective of this Research Topic is to highlight recent advances in pediatric neuroradiology that encompass novel approaches in neuroimaging, post-acquisition image processing techniques, medical image analysis, neurodevelopmental studies, and disease diagnosis. This Research Topic will provide the platform to bring together research content related to the human brain during developmental years, allowing better understanding of the normal and deviated brain growth.
We welcome research articles, reviews, or case reports covering the following topics, but are not limited to:
• Use of AI or machine learning to develop methods for post-acquisition image processing, image analysis, or computer aided diagnosis among pediatric cohorts.
• Quality control and artifacts correction in pediatric neuroimaging data.
• Development of data harmonization approaches and standardization of preprocessing pipelines.
• Structural, diffusion, or functional imaging to investigate brain structure and functional connectivity.
• Computational methods for studying neurodevelopment, identifying critical imaging biomarkers, and investigating the impact of socioeconomic status on brain development.
Keywords: Pediatrics, Neuroimaging, Radiology, Development, Disease diagnosis
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
