The critical role of standards for AI in digital pathology

Background: The field of pathology has not yet fully realized the potential of artificial intelligence (AI) and digital pathology. Adoption must be driven by demonstrable utility, and successful implementation depends on interoperability and sustainability, which require established standards. We address the imminent challenges facing the field of AI in digital pathology, which currently suffers from a lack of coordinated and adopted standards. Methods: We conducted several roundtable discussions with key opinion leaders from multiple sectors across the healthcare ecosystem. Based on how standards are used, we distinguish different areas of practice (relevance, endorsement, and utility) and emphasize the importance of standards. Results: Our roundtable discussion centered on one key theme: successfully implementing AI in digital pathology depends on achieving a certain level of uniformity across practices. We derive an approach to describe the critical role of standards consisting of seven interdependent areas of practice: value recognition, existing standards, dependencies for AI, failures, management of standards, trends, and a roadmap for accelerated and sustainable adoption. The promise of standards and our approach can be understood as the interconnection of these areas. We address imminent challenges surrounding the field of digital pathology by providing an approach for interoperable, coordinated, and sustainable use of standards across diverse practice settings. Conclusion: With the concepts and frameworks outlined in this article, we highlight the importance of standards in pathology and their crucial role in driving computational advances and enabling AI solutions to enhance patient care.