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

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.