Purpose or Case Report: Introduction:
Artificial intelligence (AI) is set to transform pediatric interventional radiology (PIR) by enhancing precision, improving diagnostics, and streamlining workflows. Given the complexities of smaller anatomy and higher risks in pediatric patients, AI's integration into imaging and procedural planning will significantly support growth and improve outcomes in the next decade. This abstract outlines key areas where AI will impact PIR.
Key Areas:
Enhanced Imaging and Diagnosis:
AI algorithms will enable faster and more accurate identification of anatomical structures and abnormalities in pediatric patients. Automated image processing can highlight critical features, assisting interventional radiologists in making informed decisions. This technology will provide detailed anatomical maps to guide minimally invasive interventions.
Procedure Optimization:
AI will enhance procedure planning and execution by predicting complications and recommending optimal techniques. AI-powered navigation systems integrated with real-time imaging will assist radiologists in navigating complex anatomical pathways, reducing procedure times and minimizing radiation exposure. Automated measurement tools will further personalize treatment.
Improved Decision-Making:
AI can analyze data from previous procedures to support decision-making, helping radiologists choose the best treatment based on predictive analytics. Machine learning models can identify trends and suggest personalized interventions, standardizing best practices and improving success rates in pediatric interventions.
Workflow Efficiency:
AI-driven automation will streamline tasks such as scheduling, imaging analysis, and report generation, allowing radiologists to focus more on patient care. By predicting resource needs and optimizing timing, AI will enhance workflow efficiency and facilitate multidisciplinary collaboration.
Education and Training:
AI will revolutionize education in pediatric interventional radiology. Virtual reality (VR) and AI-based simulation platforms will enable trainees to practice complex procedures in realistic environments, providing real-time feedback and personalized learning pathways.
Conclusion:
AI’s integration into pediatric interventional radiology will enhance imaging, optimize procedures, and streamline workflows. By leveraging AI’s capabilities, PIR can achieve greater precision, reduce risks, and improve outcomes for pediatric patients, driving growth and advancement in the field.
Methods & Materials:
Results:
Conclusions: