Aggarwal Arpit, Bharadwaj Satvika, Corredor Germán, Pathak Tilak, Badve Sunil, Madabhushi Anant
Wallace H. Coulter Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA, USA.
Atlanta Veterans Affairs Medical Center, Atlanta, GA, USA.
Nat Rev Clin Oncol. 2025 Apr;22(4):283-291. doi: 10.1038/s41571-025-00991-6. Epub 2025 Feb 11.
The past decade has seen the introduction of artificial intelligence (AI)-based approaches aimed at optimizing several workflows across many medical specialties. In clinical oncology, the most promising applications include those involving image analysis, such as digital pathology. In this Perspective, we provide a comprehensive examination of the developments in AI in digital pathology between 2019 and 2024. We evaluate the current landscape from the lens of technological innovations, regulatory trends, deployment and implementation, reimbursement and commercial implications. We assess the technological advances that have driven improvements in AI, enabling more robust and scalable solutions for digital pathology. We also examine regulatory developments, in particular those affecting in-house devices and laboratory-developed tests, which are shaping the landscape of AI-based tools in digital pathology. Finally, we discuss the role of reimbursement frameworks and commercial investment in the clinical adoption of AI-based technologies. In this Perspective, we highlight both the progress and challenges in AI-driven digital pathology over the past 5 years, outlining the path forward for its adoption into routine practice in clinical oncology.
在过去十年中,基于人工智能(AI)的方法被引入,旨在优化多个医学专业的多种工作流程。在临床肿瘤学中,最有前景的应用包括那些涉及图像分析的应用,如数字病理学。在这篇观点文章中,我们全面审视了2019年至2024年间数字病理学中人工智能的发展情况。我们从技术创新、监管趋势、部署与实施、报销及商业影响等角度评估当前形势。我们评估推动人工智能进步的技术进展,这些进展为数字病理学带来了更强大、更具可扩展性的解决方案。我们还研究监管动态,特别是那些影响内部设备和实验室研发测试的动态,它们正在塑造数字病理学中基于人工智能工具的格局。最后,我们讨论报销框架和商业投资在基于人工智能技术的临床应用中的作用。在这篇观点文章中,我们强调了过去五年人工智能驱动的数字病理学的进展与挑战,概述了其在临床肿瘤学中被纳入常规实践的前进道路。