Radiology's Information Architecture Could Migrate to One Emulating That of Smartphones

Area of Science:

• Radiology and Medical Imaging
• Health Informatics
• Artificial Intelligence in Medicine

Background:

• Diagnostic radiology (DxR) has historically adapted to technological advancements.
• The current landscape, termed "globotics transition," necessitates a new IT and informatics infrastructure.
• DxR faces the dual challenge of adopting both sustaining and disruptive artificial intelligence (AI) innovations.

Purpose of the Study:

• To outline the necessary IT and informatics infrastructure for integrating AI into DxR.
• To explore how AI can enhance critical communication functions within Picture Archiving and Communication Systems (PACS).
• To identify how DxR can leverage AI to increase the speed and scope of information and patient flow.

Main Methods:

• Conceptualizing a hierarchical IT architecture optimized for communication and integration, akin to smartphone architecture.
• Proposing DxR's role as an artificial selection force in shaping AI development.
• Analyzing the potential for new IT architectures to stimulate market competition and innovation.

Main Results:

• The integration of AI requires a shift towards a hierarchical IT architecture to manage increased information flow.
• Flexible, communication-optimized architectures can foster competition among PACS companies, AI firms, and new entrants.
• This co-evolution can lead to a modern communication medium that enhances information absorption and clinical value.

Conclusions:

• DxR must proactively develop an IT infrastructure capable of integrating AI to manage increasing data and patient volumes.
• Adopting new, flexible IT architectures is crucial for DxR to remain indispensable and drive innovation.
• The strategic integration of AI promises to significantly enhance efficiency and clinical value in diagnostic radiology.