Receive a weekly summary and discussion of the top papers of the week by leading researchers in the field.

In Journal of the American Medical Informatics Association : JAMIA

OBJECTIVE : Broad adoption of digital pathology (DP) is still lacking, and examples for DP connecting diagnostic, research, and educational use cases are missing. We blueprint a holistic DP solution at a large academic medical center ubiquitously integrated into clinical workflows; researchapplications including molecular, genetic, and tissue databases; and educational processes.

MATERIALS AND METHODS : We built a vendor-agnostic, integrated viewer for reviewing, annotating, sharing, and quality assurance of digital slides in a clinical or research context. It is the first homegrown viewer cleared by New York State provisional approval in 2020 for primary diagnosis and remote sign-out during the COVID-19 (coronavirus disease 2019) pandemic. We further introduce an interconnected Honest Broker for BioInformatics Technology (HoBBIT) to systematically compile and share large-scale DP research datasets including anonymized images, redacted pathology reports, and clinical data of patients with consent.

RESULTS : The solution has been operationally used over 3 years by 926 pathologists and researchers evaluating 288 903 digital slides. A total of 51% of these were reviewed within 1 month after scanning. Seamless integration of the viewer into 4 hospital systems clearly increases the adoption of DP. HoBBIT directly impacts the translation of knowledge in pathology into effective new health measures, including artificial intelligence-driven detection models for prostate cancer, basal cell carcinoma, and breast cancer metastases, developed and validated on thousands of cases.

CONCLUSIONS : We highlight major challenges and lessons learned when going digital to provide orientation for other pathologists. Building interconnected solutions will not only increase adoption of DP, but also facilitate next-generation computational pathology at scale for enhanced cancer research.

Schüffler Peter J, Geneslaw Luke, Yarlagadda D Vijay K, Hanna Matthew G, Samboy Jennifer, Stamelos Evangelos, Vanderbilt Chad, Philip John, Jean Marc-Henri, Corsale Lorraine, Manzo Allyne, Paramasivam Neeraj H G, Ziegler John S, Gao Jianjiong, Perin Juan C, Kim Young Suk, Bhanot Umeshkumar K, Roehrl Michael H A, Ardon Orly, Chiang Sarah, Giri Dilip D, Sigel Carlie S, Tan Lee K, Murray Melissa, Virgo Christina, England Christine, Yagi Yukako, Sirintrapun S Joseph, Klimstra David, Hameed Meera, Reuter Victor E, Fuchs Thomas J

2021-Jul-14

artificial intelligence, computational pathology, digital pathology, honest broker, pathology, whole slide imaging