Teleradiology, Edge Computing, and the Internet of Things in Radiology: A RRA Perspective on Decentralized...

Radiology is undergoing a fundamental transformation driven by the convergence of teleradiology, edge computing, and the Internet of Things (IoT). These technologies are reshaping traditional imaging workflows by enabling data to be acquired, processed, and interpreted in near real time across distributed networks. This shift from centralized, linear systems to decentralized, intelligent architectures enhance diagnostic responsiveness, improves access to subspecialty care, and supports more personalized and context-aware decision-making. IoT devices, ranging from mobile X-ray units to AI-enabled ultrasound systems, extend diagnostic capabilities to the point of care, while edge computing reduces latency and safeguards sensitive data through localized processing. Teleradiology integrates these tools by enabling remote interpretation and cross-institutional collaboration, expanding coverage and facilitating workflow scalability. Together, these technologies form an interdependent ecosystem that is particularly impactful in rural, low-bandwidth, and resource-constrained environments. However, their integration also raises new ethical, regulatory, and operational challenges, including concerns about algorithm transparency, data security, and workforce identity. As part 4 of the Radiology Research Alliance (RRA) review series on emerging technologies, this paper explores the opportunities and challenges of decentralized diagnostics and their implications for the future of radiology practice.