Integration of digital pathology workflow in the anatomic pathology laboratory
Language English Country Czech Republic Media print
Document type Journal Article, Review
PubMed
40456622
PII: 140209
Knihovny.cz E-resources
- Keywords
- Digital Pathology, artificial intelligence, machine learning, whole slide image,
- MeSH
- Pathology, Clinical * methods MeSH
- Humans MeSH
- Microscopy MeSH
- Image Processing, Computer-Assisted * MeSH
- Workflow * MeSH
- Telepathology MeSH
- Artificial Intelligence MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
The application of digital pathology and artificial intelligence in anatomical pathology represents a revolutionary step towards the modernization of diagnostic processes. Digitalization, primarily based on creation and subsequent use of whole slide imaging, enables generating of full digital images of histological slides, offering potential benefits in diagnostic accuracy and accessibility. Unlike traditional microscopy, digital pathology also facilitates telemedicine and remote consultation, opening new possibilities for collaboration and sharing of expertise at both national and international levels. However, implementing a digital workflow requires substantial investments in scanners, software platforms, high-capacity storage, and IT infrastructure. Despite considerable costs of implementation, it brings numerous advantages, including time savings, opportunities for centralized diagnostics, and a reduction in sample transport costs. This paper focuses on the practical aspects of implementing digital pathology in pathology laboratories, emphasizing the benefits, risks, and technological requirements associated with digitalized workflows. It also discusses crucial roles of validation and verification, which are essential for ensuring a diagnostic accuracy of digital images compared to conventional microscopy. The article presents digital pathology as a dynamically evolving field with high potential for personalized medicine, improved diagnostic accuracy, and support for remote collaboration, addressing the growing demands of modern medicine.