Digital innovations for sustainable radiology: Reducing waste, emissions, and inefficiencies in imaging workflows

Abstract

Healthcare systems worldwide face growing pressure to reduce environmental impact while maintaining high-quality, cost-effective care. Radiology, a particularly resource-intensive discipline, contributes significantly to healthcare-related emissions and operational inefficiencies. At the same time, digital technologies—such as artificial intelligence (AI), structured reporting, and smart scheduling—offer powerful tools to address both ecological and economic challenges. For example, AI-driven protocol optimization has been shown to cut energy consumption by up to 56% and examination time by 55%, directly aligning sustainability with operational efficiency. Using radiology as a representative case, this article examines how these innovations can reduce environmental waste, imaging overuse, and workflow inefficiencies, offering a scalable blueprint for healthcare-wide transformation. This commentary draws on a targeted review of recent literature, supplemented by practical insights from clinical radiology practice.