1. Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center
- Author
-
Yukako Yagi, Evangelos Stamelos, D Vijay K Yarlagadda, Christine England, Melissa Murray, Allyne Manzo, Thomas J. Fuchs, Chad M. Vanderbilt, Luke Geneslaw, Michael H.A. Roehrl, Victor E. Reuter, Jennifer Samboy, S. Joseph Sirintrapun, Dilip Giri, Jianjiong Gao, Marc-Henri Jean, Juan C Perin, David S. Klimstra, Lorraine Corsale, Meera Hameed, Peter J. Schüffler, Carlie S. Sigel, Matthew G. Hanna, John Philip, John Ziegler, Lee K. Tan, Neeraj H G Paramasivam, U. Bhanot, Orly Ardon, Young Suk Kim, Christina Virgo, and Sarah Chiang
- Subjects
Male ,0301 basic medicine ,AcademicSubjects/SCI01060 ,Computer science ,Health Informatics ,Research and Applications ,03 medical and health sciences ,Computational pathology ,0302 clinical medicine ,Blueprint ,Neoplasms ,Humans ,Use case ,Pandemics ,AcademicSubjects/MED00580 ,Academic Medical Centers ,Pathology, Clinical ,business.industry ,COVID-19 ,Digital pathology ,honest broker, pathology ,artificial intelligence ,ddc ,whole slide imaging ,030104 developmental biology ,Workflow ,030220 oncology & carcinogenesis ,Scale (social sciences) ,Cancer research ,Honest Broker ,AcademicSubjects/SCI01530 ,digital pathology ,business ,Quality assurance ,Medical Informatics ,computational pathology - Abstract
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.
- Published
- 2021
- Full Text
- View/download PDF