Digital Pathology: Advantages, Limitations and Emerging Perspectives
1
Diagnostic and Research Institute of Pathology, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria
2
Department of Pathology, Ordensklinikum/Hospital of the Sisters of Charity, Seilerstätte 4, 4010 Linz, Austria
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2020, 9(11), 3697; https://doi.org/10.3390/jcm9113697
Received: 8 October 2020
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Revised: 27 October 2020
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Accepted: 13 November 2020
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Published: 18 November 2020
(This article belongs to the Special Issue Augmented Reality and Artificial Intelligence in Interventional Radiology: Present and Future Perspectives)
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.
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Keywords:
digital pathology; machine learning; artificial intelligence; whole slide imaging; occupational health; computer vision syndrome; automation
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MDPI and ACS Style
Jahn, S.W.; Plass, M.; Moinfar, F. Digital Pathology: Advantages, Limitations and Emerging Perspectives. J. Clin. Med. 2020, 9, 3697. https://doi.org/10.3390/jcm9113697
AMA Style
Jahn SW, Plass M, Moinfar F. Digital Pathology: Advantages, Limitations and Emerging Perspectives. Journal of Clinical Medicine. 2020; 9(11):3697. https://doi.org/10.3390/jcm9113697
Chicago/Turabian StyleJahn, Stephan W., Markus Plass, and Farid Moinfar. 2020. "Digital Pathology: Advantages, Limitations and Emerging Perspectives" Journal of Clinical Medicine 9, no. 11: 3697. https://doi.org/10.3390/jcm9113697
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