New possibilities come with new challenges: extensive investments in IT-infrastructure and services, best practices for safe implementation, regulatory requirements, AI as an unaccountable “black-box”, working extensive screen times (occupational medicine), questions of cost-efficacy, and transformation of the profession by automation. Most fascinating of all, images can now be evaluated by ML for features beyond the assessment of traditional histopathology (artificial intelligence (AI)), such as to directly link images to clinical data (e.g., prognosis, mutations). Digital images lend themselves to computational pathology (CPATH), both for basic measuring and counting and for advanced machine learning (ML) tasks. They can be superimposed or linked beyond what physical glass slides would permit to facilitate spatial correlation across slides and stains. Digital images and video streams can be shared in real-time, thus bridging physical distance (telepathology) between local hospitals, colleges (second-opinion), teachers and students, and between home and workplace (home-office). The advent of digitized images to pathology has propelled this traditional field into what is now described as digital pathology (DP). Histopathology is a diagnostic discipline founded on the visual interpretation of cellular biology captured in images. 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. 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. Cost-efficiency analyses and occupational health issues need to be addressed comprehensively. 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. 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. Comparative studies have published reassuring data on safety and feasibility, but implementation experiences highlight the need for training and the knowledge of pitfalls. 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. Digital pathology is on the verge of becoming a mainstream option for routine diagnostics.
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