Digital Pathology Association White Paper Defines Best Practices and Regulatory Recommendations for Computational Pathology
This consensus white paper from the Digital Pathology Association establishes terminology, infrastructure requirements, and best practices for computational pathology applied to histology images. It addresses training-data acquisition, quality assessment, cybersecurity, and ethical considerations, and offers targeted recommendations for regulators, vendors, and practitioners to accelerate responsible adoption.
The original study
Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association.
- Authors
- Abels E, Pantanowitz L, Aeffner F, Zarella MD, van der Laak J, Bui MM, et al.
- Journal
- The Journal of pathology
- Type
- Journal Article, Practice Guideline, Review
- PMID
- 31355445
Original abstract
In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber-security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.