Zhang David Y, Venkat Arsha, Khasawneh Hamdi, Sali Rasoul, Zhang Valerio, Pei Zhiheng
Department of Computation, NovinoAI, Fort Lauderdale, Florida; Department of Veterans Affairs New York Harbor Healthcare System, New York, New York.
School of Medicine, New York Medical College, New York, New York.
Lab Invest. 2024 Sep;104(9):102111. doi: 10.1016/j.labinv.2024.102111. Epub 2024 Jul 23.
The advent of affordable technology has significantly influenced the practice of digital pathology, leading to its growing adoption within the pathology community. This review article aimed to outline the latest developments in digital pathology, the cutting-edge advancements in artificial intelligence (AI) applications within this field, and the pertinent United States regulatory frameworks. The content is based on a thorough analysis of original research articles and official United States Federal guidelines. Findings from our review indicate that several Food and Drug Administration-approved digital scanners and image management systems are establishing a solid foundation for the seamless integration of advanced technologies into everyday pathology workflows, which may reduce device and operational costs in the future. AI is particularly transforming the way morphologic diagnoses are automated, notably in cancers like prostate and colorectal, within screening initiatives, albeit challenges such as data privacy issues and algorithmic biases remain. The regulatory environment, shaped by standards from the Food and Drug Administration, Centers for Medicare & Medicaid Services/Clinical Laboratory Improvement Amendments, and College of American Pathologists, is evolving to accommodate these innovations while ensuring safety and reliability. Centers for Medicare & Medicaid Services/Clinical Laboratory Improvement Amendments have issued policies to allow pathologists to review and render diagnoses using digital pathology remotely. Moreover, the introduction of new digital pathology Current Procedural Terminology codes designed to complement existing pathology Current Procedural Terminology codes is facilitating reimbursement processes. Overall, these advancements are heralding a new era in pathology that promises enhanced diagnostic precision and efficiency through digital and AI technologies, potentially improving patient care as well as bolstering educational and research activities.
价格亲民的技术的出现对数字病理学的实践产生了重大影响,促使其在病理学领域的应用日益广泛。这篇综述文章旨在概述数字病理学的最新发展、该领域人工智能(AI)应用的前沿进展以及美国相关的监管框架。内容基于对原创研究文章和美国联邦官方指南的全面分析。我们的综述结果表明,一些获得美国食品药品监督管理局批准的数字扫描仪和图像管理系统正在为将先进技术无缝集成到日常病理学工作流程奠定坚实基础,这可能在未来降低设备和运营成本。人工智能尤其正在改变形态学诊断自动化的方式,特别是在前列腺癌和结直肠癌等癌症的筛查举措中,尽管数据隐私问题和算法偏差等挑战依然存在。由美国食品药品监督管理局、医疗保险和医疗补助服务中心/临床实验室改进修正案以及美国病理学家学会的标准所塑造的监管环境正在不断演变,以适应这些创新,同时确保安全性和可靠性。医疗保险和医疗补助服务中心/临床实验室改进修正案已发布政策,允许病理学家使用数字病理学进行远程审查和诊断。此外,旨在补充现有病理学现行程序术语代码的新数字病理学现行程序术语代码的引入,正在促进报销流程。总体而言,这些进展预示着病理学的一个新时代,有望通过数字和人工智能技术提高诊断的准确性和效率, potentially improving patient care as well as bolstering educational and research activities.(原文最后一句中“potentially improving patient care as well as bolstering educational and research activities”表述有误,正确的应该是“potentially improving patient care as well as bolstering educational and research activities”,可直译为“潜在地改善患者护理以及加强教育和研究活动”) 这可能会改善患者护理,并加强教育和研究活动。