Waite Stephen, Davenport Matthew S, Graber Mark L, Banja John D, Sheppard Brian, Bruno Michael A
Departments of Radiology and Internal Medicine, SUNY Downstate Medical Center, 450 Clarkson Ave, Brooklyn, NY 11203.
Departments of Radiology and Urology, Ronald Weiser Center for Prostate Cancer, Michigan Medicine, Ann Arbor, MI.
AJR Am J Roentgenol. 2024 Dec;223(6):e2431686. doi: 10.2214/AJR.24.31686. Epub 2024 Sep 18.
Radiologists' traditional role in the diagnostic process is to respond to specific clinical questions and reduce uncertainty enough to permit treatment decisions to be made. This charge is rapidly evolving due to forces such as artificial intelligence (AI), big data (opportunistic imaging, imaging prognostication), and advanced diagnostic technologies. A new modernistic paradigm is emerging whereby radiologists, in conjunction with computer algorithms, will be tasked with extracting as much information from imaging data as possible, often without a specific clinical question being posed and independent of any stated clinical need. In addition, AI algorithms are increasingly able to predict long-term outcomes using data from seemingly normal examinations, enabling AI-assisted prognostication. As these algorithms become a standard component of radiology practice, the sheer amount of information they demand will increase the need for streamlined workflows, communication, and data management techniques. In addition, the provision of such information raises reimbursement, liability, and access issues. Guidelines will be needed to ensure that all patients have access to the benefits of this new technology and guarantee that mined data do not inadvertently create harm. In this Review, we discuss the challenges and opportunities relevant to radiologists in this changing landscape, with an emphasis on ensuring that radiologists provide high-value care.
放射科医生在诊断过程中的传统角色是回答特定的临床问题,并将不确定性降低到足以做出治疗决策的程度。由于人工智能(AI)、大数据(机会性成像、成像预后)和先进诊断技术等因素,这一职责正在迅速演变。一种新的现代范式正在出现,即放射科医生将与计算机算法一起,负责从成像数据中提取尽可能多的信息,通常无需提出特定的临床问题,也独立于任何既定的临床需求。此外,人工智能算法越来越能够利用看似正常检查的数据预测长期结果,实现人工智能辅助预后。随着这些算法成为放射科实践的标准组成部分,它们所需的大量信息将增加对简化工作流程、沟通和数据管理技术的需求。此外,提供此类信息还会引发报销、责任和获取问题。需要制定指导方针,以确保所有患者都能受益于这项新技术,并保证挖掘的数据不会无意中造成伤害。在本综述中,我们讨论了在这一不断变化的形势下与放射科医生相关的挑战和机遇,重点是确保放射科医生提供高价值的医疗服务。