Jahn Stephan W, Plass Markus, Moinfar Farid
Diagnostic and Research Institute of Pathology, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria.
Department of Pathology, Ordensklinikum/Hospital of the Sisters of Charity, Seilerstätte 4, 4010 Linz, Austria.
J Clin Med. 2020 Nov 18;9(11):3697. doi: 10.3390/jcm9113697.
Digital pathology is on the verge of becoming a mainstream option for routine diagnostics. Faster whole slide image scanning has paved the way for this development, but implementation on a large scale is challenging on technical, logistical, and financial levels. Comparative studies have published reassuring data on safety and feasibility, but implementation experiences highlight the need for training and the knowledge of pitfalls. Up to half of the pathologists are reluctant to sign out reports on only digital slides and are concerned about reporting without the tool that has represented their profession since its beginning. Guidelines by international pathology organizations aim to safeguard histology in the digital realm, from image acquisition over the setup of work-stations to long-term image archiving, but must be considered a starting point only. Cost-efficiency analyses and occupational health issues need to be addressed comprehensively. Image analysis is blended into the traditional work-flow, and the approval of artificial intelligence for routine diagnostics starts to challenge human evaluation as the gold standard. Here we discuss experiences from past digital pathology implementations, future possibilities through the addition of artificial intelligence, technical and occupational health challenges, and possible changes to the pathologist's profession.
数字病理学即将成为常规诊断的主流选择。更快的全切片图像扫描为这一发展铺平了道路，但在技术、后勤和财务层面上进行大规模实施具有挑战性。比较研究已经发表了关于安全性和可行性的可靠数据，但实施经验凸显了培训的必要性以及对潜在问题的了解。多达一半的病理学家不愿仅根据数字切片签署报告，并且担心在没有自病理学诞生以来一直代表其职业的工具的情况下进行报告。国际病理学组织发布的指南旨在在数字领域保护组织学，从图像采集到工作站设置再到长期图像存档，但这些指南只能被视为一个起点。成本效益分析和职业健康问题需要得到全面解决。图像分析已融入传统工作流程，人工智能在常规诊断中的应用开始挑战作为金标准的人类评估。在此，我们讨论过去数字病理学实施的经验、通过添加人工智能带来的未来可能性、技术和职业健康挑战以及病理学家职业可能发生的变化。
