Back

Exploring the adoption of digital pathology in clinical settings - Insights from a cross-continent study

Pinto, D. G.; Bychkov, A.; Tsuyama, N.; Fukuoka, J.; Eloy, C.

2023-04-03 pathology
10.1101/2023.04.03.23288066 medRxiv
Show abstract

The last seventy years have been characterized by rapid advancements in computer technology, and the healthcare system has not been immune to this trend. However, anatomic 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 anatomic 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 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 while digital pathology is still the future for many, it is already the present for some. This decade may be a time when anatomic pathology finally embraces the digital revolution on a large scale. HIGHLIGHTSO_LILarger labs adopt digital pathology more C_LIO_LIFull digital transition is still rare nowadays C_LIO_LIMany initial concerns have not materialized after implementation C_LIO_LIMost non-digital laboratories plan to go digital soon C_LI

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.