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     «

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; Klim...     »

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.      «

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...     »