Synapse - Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center

Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center Journal Article

Authors:	Schüffler, P. J.; Geneslaw, L.; Yarlagadda, D. V. K.; Hanna, M. G.; Samboy, J.; Stamelos, E.; Vanderbilt, C.; Philip, J.; Jean, M. H.; Corsale, L.; Manzo, A.; Paramasivam, N. H. G.; Ziegler, J. S.; Gao, J.; Perin, J. C.; Kim, Y. S.; Bhanot, U. K.; Roehrl, M. H. A.; Ardon, O.; Chiang, S.; Giri, D. D.; Sigel, C. S.; Tan, L. K.; Murray, M.; Virgo, C.; England, C.; Yagi, Y.; Sirintrapun, S. J.; Klimstra, D.; Hameed, M.; Reuter, V. E.; Fuchs, T. J.
Article Title:	Integrated digital pathology at scale: A solution for clinical diagnostics and cancer research at a large academic medical center
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. © 2021 The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association.
Keywords:	artificial intelligence; digital pathology; whole slide imaging; computational pathology; honest broker, pathology
Journal Title:	Journal of the American Medical Informatics Association
Volume:	28
Issue:	9
ISSN:	1067-5027
Publisher:	Oxford University Press
Date Published:	2021-09-01
Start Page:	1874
End Page:	1884
Language:	English
DOI:	10.1093/jamia/ocab085
PUBMED:	34260720
PROVIDER:	scopus
PMCID:	PMC8344580
DOI/URL:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85114328858&doi=10.1093%2fjamia%2focab085&partnerID=40&md5=1695ee84a5c40d7ec36eb43ce6c31731
Notes:	Article -- Export Date: 1 October 2021 -- Source: Scopus