Wichtmann Barbara D, Paech Daniel, Pianykh Oleg S, Huang Susie Y, Seltzer Steven E, Brink James, Fennessy Fiona M
Department of Radiology, Mass General Brigham, Boston, MA, USA.
Clinic of Neuroradiology, University Hospital Bonn, Bonn, Germany.
Eur Radiol. 2025 Jun 27. doi: 10.1007/s00330-025-11745-4.
Radiology has evolved from the pioneering days of X-ray imaging to a field rich in advanced technologies on the cusp of a transformative future driven by artificial intelligence (AI). As imaging workloads grow in volume and complexity, and economic as well as environmental pressures intensify, visionary leadership is needed to navigate the unprecedented challenges and opportunities ahead. Leveraging its strengths in automation, accuracy and objectivity, AI will profoundly impact all aspects of radiology practice-from workflow management, to imaging, diagnostics, reporting and data-driven analytics-freeing radiologists to focus on value-driven tasks that improve patient care. However, successful AI integration requires strong leadership and robust governance structures to oversee algorithm evaluation, deployment, and ongoing maintenance, steering the transition from static to continuous learning systems. The vision of a "diagnostic cockpit" that integrates multidimensional data for quantitative precision diagnoses depends on visionary leadership that fosters innovation and interdisciplinary collaboration. Through administrative automation, precision medicine, and predictive analytics, AI can enhance operational efficiency, reduce administrative burden, and optimize resource allocation, leading to substantial cost reductions. Leaders need to understand not only the technical aspects but also the complex human, administrative, and organizational challenges of AI's implementation. Establishing sound governance and organizational frameworks will be essential to ensure ethical compliance and appropriate oversight of AI algorithms. As radiology advances toward this AI-driven future, leaders must cultivate an environment where technology enhances rather than replaces human skills, upholding an unwavering commitment to human-centered care. Their vision will define radiology's pioneering role in AI-enabled healthcare transformation. KEY POINTS: Question Artificial intelligence (AI) will transform radiology, improving workflow efficiency, reducing administrative burden, and optimizing resource allocation to meet imaging workloads' increasing complexity and volume. Findings Strong leadership and governance ensure ethical deployment of AI, steering the transition from static to continuous learning systems while fostering interdisciplinary innovation and collaboration. Clinical relevance Visionary leaders must harness AI to enhance, rather than replace, the role of professionals in radiology, advancing human-centered care while pioneering healthcare transformation.
放射学已从X射线成像的开创时期发展成为一个拥有丰富先进技术的领域,正处于由人工智能(AI)驱动的变革性未来的风口浪尖。随着成像工作量在数量和复杂性上的增加,以及经济和环境压力的加剧,需要有远见的领导力来应对前所未有的挑战和机遇。人工智能凭借其在自动化、准确性和客观性方面的优势,将深刻影响放射学实践的各个方面——从工作流程管理到成像、诊断、报告以及数据驱动的分析——使放射科医生能够专注于提高患者护理质量的价值驱动型任务。然而,成功整合人工智能需要强大的领导力和健全的治理结构,以监督算法评估、部署和持续维护,引领从静态学习系统向持续学习系统的转变。整合多维数据以进行定量精确诊断的“诊断驾驶舱”愿景,取决于能够促进创新和跨学科合作的有远见的领导力。通过行政自动化、精准医学和预测分析,人工智能可以提高运营效率、减轻行政负担并优化资源分配,从而大幅降低成本。领导者不仅需要了解人工智能实施的技术方面,还需要了解其复杂的人文、行政和组织挑战。建立健全的治理和组织框架对于确保人工智能算法的道德合规和适当监督至关重要。随着放射学朝着这个由人工智能驱动的未来发展,领导者必须营造一个技术增强而非取代人类技能的环境,坚定不移地致力于以患者为中心的护理。他们的愿景将定义放射学在人工智能驱动的医疗保健转型中的先锋作用。要点:问题人工智能(AI)将改变放射学,提高工作流程效率,减轻行政负担,并优化资源分配,以应对成像工作量日益增加的复杂性和数量。发现强大的领导力和治理确保人工智能的道德部署,引领从静态学习系统向持续学习系统的转变,同时促进跨学科创新和合作。临床意义有远见的领导者必须利用人工智能来增强而非取代放射学专业人员的作用,在推动医疗保健转型的同时推进以患者为中心的护理。