Real-World Implementation of Digital Pathology: Results From an Intercontinental Survey.

The past 70 years have been characterized by rapid advancements in computer technology, and the health care system has not been immune to this trend. However, anatomical pathology has remained largely an analog discipline. In recent years, this has been changing with the growing adoption of digital pathology, partly driven by the potential of computer-aided diagnosis. As part of an international collaboration, we conducted a comprehensive survey to gain a deeper understanding of the status of digital pathology implementation in Europe and Asia. A total of 127 anatomical pathology laboratories participated in the survey, including 75 from Europe and 52 from Asia, with 72 laboratories having established digital pathology workflow and 55 without digital pathology. Laboratories using digital pathology for diagnostic (n = 29) and nondiagnostic (n = 43) purposes were thoroughly questioned about their implementation strategies and institutional experiences, including details on equipment, storage, integration with laboratory information system, computer-aided diagnosis, and the costs of going digital. The impact of the digital pathology workflow was also evaluated, focusing on turnaround time, specimen traceability, quality control, and overall satisfaction. Laboratories without access to digital pathology were asked to provide insights into their perceptions of the technology, expectations, barriers to adoption, and potential facilitators. Our findings indicate that although digital pathology is still the future for many, it is already the present for some. This decade may be a time when anatomical pathology finally embraces digital revolution on a larger scale.

Quantitative assessment of myocardial fibrosis by digital image analysis: An adjunctive tool for pathologist "ground truth".

AIMS: Myocardial fibrosis (MF) is a common pathological process in a wide range of cardiovascular diseases. Its quantity has diagnostic and prognostic relevance. We aimed to assess if the complementary use of an automated artificial intelligence software might improve the precision of the pathologist´s quantification of MF on endomyocardial biopsies (EMB). METHODS AND RESULTS: Intraoperative EMB samples from 30 patients with severe aortic stenosis submitted to surgical aortic valve replacement were analysed. Tissue sections were stained with Masson´s trichrome for collagen/fibrosis and whole slide images (WSI) from the experimental glass slides were obtained at a resolution of 0.5 µm using a digital microscopic scanner. Three experienced pathologists made a first quantification of MF excluding the subendocardium. After two weeks, an algorithm for Masson´s trichrome brightfield WSI (at QuPath software) was applied and the automatic quantification was revealed to the pathologists, who were asked to reassess MF, blinded to their first evaluation. The impact of the automatic algorithm on the inter-observer agreement was evaluated using Bland-Altman type methodology. Median values of MF on EMB were 8.33% [IQR 5.00-12.08%] and 13.60% [IQR 7.32-21.2%], respectively for the first pathologist´s and automatic algorithm quantification, being highly correlated (R2: 0.79; p < 0.001). Interobserver discordance was relevant, particularly for higher percentages of MF. The knowledge of the automatic quantification significantly improved the overall pathologist´s agreement, which became unaffected by the degree of MF severity. CONCLUSIONS: The use of an automated artificial intelligence software for MF quantification on EMB samples improves the reproducibility of measurements by experienced pathologists. By improving the reliability of the quantification of myocardial tissue components, this adjunctive tool may facilitate the implementation of imaging-pathology correlation studies.