Department of Pathology & Laboratory Medicine, Memorial Sloan-Kettering Cancer Center, New York, New York.
The Wisconsin State Laboratory of Hygiene and Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin.
J Am Soc Cytopathol. 2024 Mar-Apr;13(2):97-110. doi: 10.1016/j.jasc.2023.11.005. Epub 2023 Dec 3.
Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.
数字细胞学和人工智能(AI)在细胞学实验室中的应用越来越广泛。然而,关于当前临床现状的同行评审真实世界数据和文献仍然缺乏。美国细胞病理学学会与国际细胞学学会和数字病理学协会联合成立了一个特别工作组,由 20 名成员组成,他们在数字细胞学方面具有专业知识和/或兴趣,特别是细胞学全玻片扫描和 AI 应用。该小组的目的是研究将数字细胞学,特别是细胞学全玻片扫描和 AI 应用纳入实验室工作流程的可行性。反过来,也评估了对细胞病理学家、细胞学专家(细胞技术专家)和细胞学部门的影响。该工作组审查了数字细胞学的现有文献,进行了全球调查,并与多家行业企业代表就数字细胞学和 AI 进行了虚拟圆桌讨论。本白皮书分为两部分,总结了全球细胞学实践中数字细胞学和 AI 实践的现状。本白皮书的第 1 部分作为单独的论文呈现,详细介绍了将数字细胞学纳入实践的审查和最佳实践建议。本白皮书的第 2 部分全面回顾了细胞学实践中的人工智能,以及最佳实践建议和法律考虑因素。此外,还报告了细胞学全球调查结果,重点介绍了各个实验室目前的人工智能实践以及当前的态度。