David Y. Zhang , Arsha Venkat , Hamdi Khasawneh , Rasoul Sali , Valerio Zhang , Zhiheng Pei
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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. 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引用次数: 0
摘要
廉价技术的出现极大地影响了数字病理学的实践,使其在病理学界的应用日益广泛。这篇综述文章旨在概述数字病理学的最新发展、人工智能(AI)在该领域应用的前沿进展以及美国的相关监管框架。文章内容基于对原始研究文章和美国联邦官方指南的全面分析。我们的研究结果表明,几种经 FDA 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工作流程中奠定坚实的基础,这可能会在未来降低设备和运营成本。尽管数据隐私问题和算法偏差等挑战依然存在,但人工智能尤其正在改变形态学诊断的自动化方式,特别是在前列腺癌和结直肠癌等癌症的筛查活动中。美国食品和药物管理局(FDA)、CMS/CLIA 和 CAP 的标准所形成的监管环境正在不断发展,以适应这些创新,同时确保安全性和可靠性。CMS/CLIA 已发布政策,允许病理学家使用数字病理进行远程审查和诊断。此外,为补充现有病理 CPT 代码而设计的新数字病理 CPT 代码的引入也促进了报销流程。总之,这些进步预示着病理学进入了一个新时代,有望通过数字和人工智能技术提高诊断精度和效率,从而改善患者护理并促进教育和研究活动。
Implementation of Digital Pathology and Artificial Intelligence in Routine Pathology Practice
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.
期刊介绍:
Laboratory Investigation is an international journal owned by the United States and Canadian Academy of Pathology. Laboratory Investigation offers prompt publication of high-quality original research in all biomedical disciplines relating to the understanding of human disease and the application of new methods to the diagnosis of disease. Both human and experimental studies are welcome.