Digital pathology imaging artificial intelligence in cancer research and clinical trials: An NCI workshop report

Abstract

Digital pathology imaging (DPI) is a rapidly advancing field with increasing relevance to cancer diagnosis, research, and clinical trials through large-scale image analysis and artificial intelligence (AI) integration. Despite these advances, regulatory adoption in digital pathology (DP) has lagged; to date, only three AI/ML Software as a Medical Device tool have received FDA clearance, highlighting a validation dataset gap rather than an absence of regulatory pathways. On March 6-7, 2024, the National Cancer Institute held a virtual workshop titled "Digital Pathology Imaging-Artificial Intelligence in Cancer Research and Clinical Trials," bringing together experts in pathology, radiology, oncology, data science, and regulatory fields to assess current challenges, practical solutions, and future directions. This report summarizes expert opinions on key issues related to the use of DPI in cancer research and clinical trials, including data standardization, de-identification, and the application of Digital Imaging and Communication in Medicine (DICOM) standards. Key topics included data standardization, image quality assurance, validation strategies, AI applications, integration in clinical trials, biobanking, intellectual property, investigators' needs, and lessons from digital cytology and radiology domains. Solutions discussed included adoption of open standards such as DICOM, centralized imaging portals, and scalable cloud-based platforms. The expert consensus outlined in this report is intended to guide the development of DPI infrastructure, standardization, support AI validation, and align regulatory and data-sharing practices to advance precision oncology.

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