AI in Neuroradiology: Research, Implementation and Ethics (2025)-WEB2922-2025

Video Transcription

Video Summary

The webinar moderated by Max Wintermark from the Radiological Society of North America explores the role of AI in neuroradiology, focusing on its research, implementation, and ethical considerations. The panel features experts like Dr. Yvonne Louis, Luciano Prevedello, and Mark Colley, who discuss the significant contributions and challenges of AI in the field.<br /><br />Dr. Yvonne Louis discusses upstream AI, focusing on how AI can influence image acquisition and reconstruction, enhancing patient comfort and image quality. Despite strides in AI-assisted imaging, concerns about algorithm reliability and the need to balance clinical needs with technological capabilities persist.<br /><br />Luciano Prevedello provides insights into downstream AI applications, stressing the importance of selecting clinically valuable AI tools and considering human performance and model development's role in implementation success. Challenges such as data bias and the need for ongoing model testing and improvement are highlighted, demonstrating the complexity of integrating AI into clinical practice.<br /><br />Mark Colley addresses ethical aspects, emphasizing the inherent bias in AI algorithms. He presents an example from UCSF to illustrate how AI biases can perpetuate healthcare inequities. With focus on risk assessment, he underscores the necessity of careful evaluation and monitoring of AI tools to ensure safe and effective clinical applications.<br /><br />The discussion also touches on obstacles such as stakeholder buy-in, reimbursement issues, and the necessity for comprehensive training data sets. Suzy Bash and other panelists emphasize the ROI of AI tools and the need for continued evaluation to ensure quality and practicality in radiology practices. The webinar calls attention to the nuanced balance between technological advancement and practical, patient-centered outcomes in AI's future in neuroradiology.

Keywords

AI in neuroradiology

ethical considerations

image acquisition

algorithm reliability

data bias

clinical practice

healthcare inequities

stakeholder buy-in

reimbursement issues

radiology practices